Principal Components of All Data
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This module generates a series of high level plots that describe the data overall and may be useful for identifying anomalous data and/or covariates.
- Heatmaps
- PCA
- Study design
- Other QC
Heatmap of Raw Data
More Plot Information Detected/undetected calls
Heatmap of Raw Data
Heatmap of the raw counts. The plot is meant to provide an overview of how robust the raw expression levels are across samples and gene sets. Datasets that entirely lack higher level expressions (e.g. counts > 100) may indicate experimental failure or low input. The detected/undetected calls links to a .csv file stating whether each probe is above background, with 0/1 indicating below/above background. If the user has not specified a detection threshold, probes are called detected if they have more than double the counts of the median negative control.
Heatmap of All Data
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Heatmap of All Data
Heatmap of the normalized data, scaled to give all genes equal variance, generated via unsupervised clustering. Orange indicates high expression; blue indicates low expression. This plot is meant to provide a high level exploratory view of the data.
Pairwise comparisons of all covariates in the analysis. The type of plot is dependent on the types of variables compared; A categorical vs. categorical covariate plot is shown as a bar chart of counts (Y axis). Continuous vs. categorical covariates generate a boxplot with whiskers denoting 1.5 IQR. Continuous vs. continuous covariates are compared via a scatter plot. Variables that are correlated with a biological variable of interest are potential confounders that may influence downstream analyses. Additionally, bar plots and histograms show the distributions of categorical and continuous variables, respectively.
Variance vs. Mean normalized signal plot across all targets/probes
More Plot Information Mean and Variance statistics across all genes
Variance vs. Mean normalized signal plot across all targets/probes
Each gene's variance in the log-scaled, normalized data is plotted against its mean value across all samples. Highly variable genes are indicated by gene name. Housekeeping genes are color coded according to their use in (or omission from) normalization.
p-value distribution plots
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p-value distribution plots
For each covariate included in the analysis, a histogram of p-values testing each gene's univariate association with the chosen covariate is displayed. Covariates with largely flat histograms have minimal association with gene expression; covariates with histograms with significantly more mass on the left are either associated with the expression of many genes or are confounded with a covariate that is associated with the expression. Low p-values indicate strong evidence for an association.
- Heatmaps
- PCA
Heatmap of CC.PLS.Apop Data
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Heatmap of CC.PLS.Apop Data
Heatmap of the normalized data, scaled to give all genes equal variance, generated via unsupervised clustering. Orange indicates high expression; blue indicates low expression. This plot is meant to provide a high level exploratory view of the data.
Principal Components of CC.PLS.Apop Data
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Principal Components of CC.PLS.Apop Data
Principal component analysis maps high-dimensional datasets onto a smaller number of highly informative dimensions. Here, the first four principal components of the gene expression data are plotted against each other and colored by the values of the selected covariate. This plot may be used to identify clusters in the data and to identify variables associated with prominent signal in the data. Variables that are associated with these leading principal components should be considered in downstream analyses.
- Heatmaps
- PCA
Heatmap of ChromMod Data
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Heatmap of ChromMod Data
Heatmap of the normalized data, scaled to give all genes equal variance, generated via unsupervised clustering. Orange indicates high expression; blue indicates low expression. This plot is meant to provide a high level exploratory view of the data.
Principal Components of ChromMod Data
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Principal Components of ChromMod Data
Principal component analysis maps high-dimensional datasets onto a smaller number of highly informative dimensions. Here, the first four principal components of the gene expression data are plotted against each other and colored by the values of the selected covariate. This plot may be used to identify clusters in the data and to identify variables associated with prominent signal in the data. Variables that are associated with these leading principal components should be considered in downstream analyses.
- Heatmaps
- PCA
Heatmap of DNARepair Data
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Heatmap of DNARepair Data
Heatmap of the normalized data, scaled to give all genes equal variance, generated via unsupervised clustering. Orange indicates high expression; blue indicates low expression. This plot is meant to provide a high level exploratory view of the data.
Principal Components of DNARepair Data
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Principal Components of DNARepair Data
Principal component analysis maps high-dimensional datasets onto a smaller number of highly informative dimensions. Here, the first four principal components of the gene expression data are plotted against each other and colored by the values of the selected covariate. This plot may be used to identify clusters in the data and to identify variables associated with prominent signal in the data. Variables that are associated with these leading principal components should be considered in downstream analyses.
- Heatmaps
- PCA
Heatmap of Driver Gene Data
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Heatmap of Driver Gene Data
Heatmap of the normalized data, scaled to give all genes equal variance, generated via unsupervised clustering. Orange indicates high expression; blue indicates low expression. This plot is meant to provide a high level exploratory view of the data.
Principal Components of Driver Gene Data
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Principal Components of Driver Gene Data
Principal component analysis maps high-dimensional datasets onto a smaller number of highly informative dimensions. Here, the first four principal components of the gene expression data are plotted against each other and colored by the values of the selected covariate. This plot may be used to identify clusters in the data and to identify variables associated with prominent signal in the data. Variables that are associated with these leading principal components should be considered in downstream analyses.
- Heatmaps
- PCA
Heatmap of HH Data
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Heatmap of HH Data
Heatmap of the normalized data, scaled to give all genes equal variance, generated via unsupervised clustering. Orange indicates high expression; blue indicates low expression. This plot is meant to provide a high level exploratory view of the data.
Principal Components of HH Data
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Principal Components of HH Data
Principal component analysis maps high-dimensional datasets onto a smaller number of highly informative dimensions. Here, the first four principal components of the gene expression data are plotted against each other and colored by the values of the selected covariate. This plot may be used to identify clusters in the data and to identify variables associated with prominent signal in the data. Variables that are associated with these leading principal components should be considered in downstream analyses.
- Heatmaps
- PCA
Heatmap of JAK-STAT Data
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Heatmap of JAK-STAT Data
Heatmap of the normalized data, scaled to give all genes equal variance, generated via unsupervised clustering. Orange indicates high expression; blue indicates low expression. This plot is meant to provide a high level exploratory view of the data.
Principal Components of JAK-STAT Data
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Principal Components of JAK-STAT Data
Principal component analysis maps high-dimensional datasets onto a smaller number of highly informative dimensions. Here, the first four principal components of the gene expression data are plotted against each other and colored by the values of the selected covariate. This plot may be used to identify clusters in the data and to identify variables associated with prominent signal in the data. Variables that are associated with these leading principal components should be considered in downstream analyses.
- Heatmaps
- PCA
Heatmap of MAPK Data
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Heatmap of MAPK Data
Heatmap of the normalized data, scaled to give all genes equal variance, generated via unsupervised clustering. Orange indicates high expression; blue indicates low expression. This plot is meant to provide a high level exploratory view of the data.
Principal Components of MAPK Data
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Principal Components of MAPK Data
Principal component analysis maps high-dimensional datasets onto a smaller number of highly informative dimensions. Here, the first four principal components of the gene expression data are plotted against each other and colored by the values of the selected covariate. This plot may be used to identify clusters in the data and to identify variables associated with prominent signal in the data. Variables that are associated with these leading principal components should be considered in downstream analyses.
- Heatmaps
- PCA
Heatmap of Notch Data
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Heatmap of Notch Data
Heatmap of the normalized data, scaled to give all genes equal variance, generated via unsupervised clustering. Orange indicates high expression; blue indicates low expression. This plot is meant to provide a high level exploratory view of the data.
Principal Components of Notch Data
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Principal Components of Notch Data
Principal component analysis maps high-dimensional datasets onto a smaller number of highly informative dimensions. Here, the first four principal components of the gene expression data are plotted against each other and colored by the values of the selected covariate. This plot may be used to identify clusters in the data and to identify variables associated with prominent signal in the data. Variables that are associated with these leading principal components should be considered in downstream analyses.
- Heatmaps
- PCA
Heatmap of PI3K Data
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Heatmap of PI3K Data
Heatmap of the normalized data, scaled to give all genes equal variance, generated via unsupervised clustering. Orange indicates high expression; blue indicates low expression. This plot is meant to provide a high level exploratory view of the data.
Principal Components of PI3K Data
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Principal Components of PI3K Data
Principal component analysis maps high-dimensional datasets onto a smaller number of highly informative dimensions. Here, the first four principal components of the gene expression data are plotted against each other and colored by the values of the selected covariate. This plot may be used to identify clusters in the data and to identify variables associated with prominent signal in the data. Variables that are associated with these leading principal components should be considered in downstream analyses.
- Heatmaps
- PCA
Heatmap of RAS Data
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Heatmap of RAS Data
Heatmap of the normalized data, scaled to give all genes equal variance, generated via unsupervised clustering. Orange indicates high expression; blue indicates low expression. This plot is meant to provide a high level exploratory view of the data.
Principal Components of RAS Data
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Principal Components of RAS Data
Principal component analysis maps high-dimensional datasets onto a smaller number of highly informative dimensions. Here, the first four principal components of the gene expression data are plotted against each other and colored by the values of the selected covariate. This plot may be used to identify clusters in the data and to identify variables associated with prominent signal in the data. Variables that are associated with these leading principal components should be considered in downstream analyses.
- Heatmaps
- PCA
Heatmap of TGF-B Data
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Heatmap of TGF-B Data
Heatmap of the normalized data, scaled to give all genes equal variance, generated via unsupervised clustering. Orange indicates high expression; blue indicates low expression. This plot is meant to provide a high level exploratory view of the data.
Principal Components of TGF-B Data
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Principal Components of TGF-B Data
Principal component analysis maps high-dimensional datasets onto a smaller number of highly informative dimensions. Here, the first four principal components of the gene expression data are plotted against each other and colored by the values of the selected covariate. This plot may be used to identify clusters in the data and to identify variables associated with prominent signal in the data. Variables that are associated with these leading principal components should be considered in downstream analyses.
- Heatmaps
- PCA
Heatmap of TXmisReg Data
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Heatmap of TXmisReg Data
Heatmap of the normalized data, scaled to give all genes equal variance, generated via unsupervised clustering. Orange indicates high expression; blue indicates low expression. This plot is meant to provide a high level exploratory view of the data.
Principal Components of TXmisReg Data
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Principal Components of TXmisReg Data
Principal component analysis maps high-dimensional datasets onto a smaller number of highly informative dimensions. Here, the first four principal components of the gene expression data are plotted against each other and colored by the values of the selected covariate. This plot may be used to identify clusters in the data and to identify variables associated with prominent signal in the data. Variables that are associated with these leading principal components should be considered in downstream analyses.
- Heatmaps
- PCA
Heatmap of Wnt Data
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Heatmap of Wnt Data
Heatmap of the normalized data, scaled to give all genes equal variance, generated via unsupervised clustering. Orange indicates high expression; blue indicates low expression. This plot is meant to provide a high level exploratory view of the data.
Principal Components of Wnt Data
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Principal Components of Wnt Data
Principal component analysis maps high-dimensional datasets onto a smaller number of highly informative dimensions. Here, the first four principal components of the gene expression data are plotted against each other and colored by the values of the selected covariate. This plot may be used to identify clusters in the data and to identify variables associated with prominent signal in the data. Variables that are associated with these leading principal components should be considered in downstream analyses.
Displays plots that detail the impact of normalization on the data.
- Analyte:
- mRNA
Pairwise Variance during HK Selection
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Pairwise Variance during HK Selection
Displays the geNorm pairwise variation statistic after successive genes are removed. This statistic cannot be computed for the final two genes, which are therefore not displayed. The ideal normalization gene set will minimize the pairwise variation statistic.
Normalization Summary: mRNA
More Plot Information Log2 Normalized All Data Log2 Normalized mRNA Data Download HK Genes
Normalization Summary: mRNA
The lower the MSE of reference profile the higher quality of normalization. The more positive normalization factor, the higher counts were registered for the sample and vice versa
Pathway scores condense each sample's gene expression profile into a small set of pathway scores. An experiment can then be explored through the lens of pathway scores instead of in the much higher-dimension lens of gene expression values. Pathway scores are fit using the first principal component of each gene set's data. They are oriented such that increasing score corresponds to mostly increasing expression (specifically, each pathway score has positive weights for at least half its genes). Summary plots explore the joint behavior of pathways, and Covariates plots compare pathway scores to covariates.
- Summary
- Covariates
Heatmap of Pathway scores
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Heatmap of Pathway scores
Heatmap showing pathway score. This plot is a high level overview of how the pathway scores change across samples. Use it to understand how which pathway scores cluster together and which samples exhibit similar pathway score profiles. Orange indicates high scores; blue indicates low scores. Scores are displayed on the same scale via a Z-transformation.
Heatmap of Correlation Matrix of Pathway scores
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Heatmap of Correlation Matrix of Pathway scores
Heatmap showing the correlation matrix of pathway scores. Red and blue indicate positive and negative correlation, respectively.
CC.PLS.Apop measurements vs. other pathway scores
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CC.PLS.Apop measurements vs. other pathway scores
Each panel plots CC.PLS.Apop against another pathway score. Points are colored by Subtype.
ChromMod measurements vs. other pathway scores
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ChromMod measurements vs. other pathway scores
Each panel plots ChromMod against another pathway score. Points are colored by Subtype.
DNARepair measurements vs. other pathway scores
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DNARepair measurements vs. other pathway scores
Each panel plots DNARepair against another pathway score. Points are colored by Subtype.
Driver Gene measurements vs. other pathway scores
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Driver Gene measurements vs. other pathway scores
Each panel plots Driver Gene against another pathway score. Points are colored by Subtype.
HH measurements vs. other pathway scores
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HH measurements vs. other pathway scores
Each panel plots HH against another pathway score. Points are colored by Subtype.
JAK-STAT measurements vs. other pathway scores
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JAK-STAT measurements vs. other pathway scores
Each panel plots JAK-STAT against another pathway score. Points are colored by Subtype.
MAPK measurements vs. other pathway scores
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MAPK measurements vs. other pathway scores
Each panel plots MAPK against another pathway score. Points are colored by Subtype.
Notch measurements vs. other pathway scores
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Notch measurements vs. other pathway scores
Each panel plots Notch against another pathway score. Points are colored by Subtype.
PI3K measurements vs. other pathway scores
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PI3K measurements vs. other pathway scores
Each panel plots PI3K against another pathway score. Points are colored by Subtype.
RAS measurements vs. other pathway scores
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RAS measurements vs. other pathway scores
Each panel plots RAS against another pathway score. Points are colored by Subtype.
TGF-B measurements vs. other pathway scores
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TGF-B measurements vs. other pathway scores
Each panel plots TGF-B against another pathway score. Points are colored by Subtype.
TXmisReg measurements vs. other pathway scores
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TXmisReg measurements vs. other pathway scores
Each panel plots TXmisReg against another pathway score. Points are colored by Subtype.
Wnt measurements vs. other pathway scores
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Wnt measurements vs. other pathway scores
Each panel plots Wnt against another pathway score. Points are colored by Subtype.
Pathway scores vs. Subtype
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Pathway scores vs. Subtype
Plots the pathway scores against Subtype. The pathway scores are plotted to show how they vary across different values of Subtype conditions. Lines show each pathway's average score across values of Subtype.
CC.PLS.Apop pathway scores vs. Subtype
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CC.PLS.Apop pathway scores vs. Subtype
Plots CC.PLS.Apop pathway scores against Subtype.
ChromMod pathway scores vs. Subtype
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ChromMod pathway scores vs. Subtype
Plots ChromMod pathway scores against Subtype.
DNARepair pathway scores vs. Subtype
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DNARepair pathway scores vs. Subtype
Plots DNARepair pathway scores against Subtype.
Driver Gene pathway scores vs. Subtype
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Driver Gene pathway scores vs. Subtype
Plots Driver Gene pathway scores against Subtype.
HH pathway scores vs. Subtype
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HH pathway scores vs. Subtype
Plots HH pathway scores against Subtype.
JAK-STAT pathway scores vs. Subtype
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JAK-STAT pathway scores vs. Subtype
Plots JAK-STAT pathway scores against Subtype.
MAPK pathway scores vs. Subtype
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MAPK pathway scores vs. Subtype
Plots MAPK pathway scores against Subtype.
Notch pathway scores vs. Subtype
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Notch pathway scores vs. Subtype
Plots Notch pathway scores against Subtype.
PI3K pathway scores vs. Subtype
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PI3K pathway scores vs. Subtype
Plots PI3K pathway scores against Subtype.
RAS pathway scores vs. Subtype
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RAS pathway scores vs. Subtype
Plots RAS pathway scores against Subtype.
TGF-B pathway scores vs. Subtype
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TGF-B pathway scores vs. Subtype
Plots TGF-B pathway scores against Subtype.
TXmisReg pathway scores vs. Subtype
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TXmisReg pathway scores vs. Subtype
Plots TXmisReg pathway scores against Subtype.
Wnt pathway scores vs. Subtype
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Wnt pathway scores vs. Subtype
Plots Wnt pathway scores against Subtype.
Genes are tested for differential expression in response to each selected covariate. For each gene, a single linear regression is fit using all selected covariates to predict expression. This approach eliminates confounding due to measured covariates and isolates the independent association of each covariate with gene expression, measuring each variable's association with a gene after holding all other variables constant.
- Subtype:
- SubtypeA
- SubtypeB
- SubtypeC
- SubtypeD
Volcano Plot: SubtypeA
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Volcano Plot: SubtypeA
Volcano plot displaying each gene's -log10(p-value) and log2 fold change with the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds. The 40 most statistically significant genes are named.
DE Results: SubtypeA
More Plot Information Download CSV DataLog2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets probe.ID MAML2-mRNA -1.97 0.18 -2.32 -1.61 4.47e-15 1.78e-11 Notch NM_032427.1:4125 KIT-mRNA -3.12 0.436 -3.98 -2.27 2.68e-09 5.33e-06 Driver Gene, PI3K, RAS NM_000222.1:5 PPARG-mRNA -2.27 0.368 -2.99 -1.55 1.01e-07 0.000118 TXmisReg NM_015869.3:1035 IL11RA-mRNA -1.51 0.246 -1.99 -1.03 1.19e-07 0.000118 JAK-STAT NM_147162.1:400 CDKN2C-mRNA -1.81 0.301 -2.4 -1.22 1.97e-07 0.000155 CC.PLS.Apop, TXmisReg NM_001262.2:1295 JUN-mRNA -2.21 0.371 -2.94 -1.48 2.33e-07 0.000155 MAPK, Wnt NM_002228.3:140 COMP-mRNA 4.54 0.791 2.99 6.09 4.86e-07 0.000263 PI3K NM_000095.2:1744 INHBA-mRNA 3.28 0.574 2.16 4.41 5.29e-07 0.000263 TGF-B NM_002192.2:490 CDKN1C-mRNA -2.27 0.412 -3.07 -1.46 1.19e-06 0.000491 CC.PLS.Apop NM_000076.2:1605 NTRK2-mRNA -3.27 0.595 -4.43 -2.1 1.24e-06 0.000491 MAPK NM_001007097.1:1605 SPRY2-mRNA -1.82 0.342 -2.49 -1.15 2.22e-06 0.000804 JAK-STAT NM_005842.2:85 FGF10-mRNA -2.17 0.418 -2.99 -1.35 3.51e-06 0.00116 MAPK, PI3K, RAS NM_004465.1:85 RUNX1T1-mRNA -1.85 0.372 -2.58 -1.12 7.5e-06 0.0023 TXmisReg NM_004349.2:1085 KLF4-mRNA -1.88 0.383 -2.63 -1.13 9.02e-06 0.00256 Driver Gene NM_004235.4:1980 PDGFRA-mRNA -1.78 0.369 -2.5 -1.05 1.31e-05 0.00345 Driver Gene, MAPK, PI3K, RAS NM_006206.3:1925 ID4-mRNA -2.28 0.476 -3.21 -1.34 1.46e-05 0.00345 TGF-B NM_001546.2:2048 PLD1-mRNA -1.48 0.309 -2.08 -0.872 1.47e-05 0.00345 RAS NM_002662.3:1265 TGFBR2-mRNA -1.24 0.265 -1.75 -0.717 2.15e-05 0.00461 MAPK, TGF-B, TXmisReg NM_001024847.1:1760 UBE2T-mRNA 1.83 0.393 1.06 2.6 2.2e-05 0.00461 DNARepair NM_014176.3:595 MAP2K6-mRNA -1.7 0.369 -2.42 -0.976 2.71e-05 0.00538 MAPK NM_002758.3:555 DE Results: SubtypeA
Table presenting the most statistically significantly differentially expressed genes with the selected covariate. 'Estimated log fold-change' estimates a gene's differential expression. For categorical covariates, a gene is estimated to have 2^(log fold change) times its expression in baseline samples, holding all other variables in the analysis constant. If the covariate is continuous, for each unit increase in the selected covariate, a gene's expression is estimated to increase by 2^(log fold change)-fold, holding all other variables in the analysis constant. The 95% confidence interval for the log fold change is also presented, along with a p-value and an adjusted p-value or FDR if requested.
Volcano Plot: SubtypeB
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Volcano Plot: SubtypeB
Volcano plot displaying each gene's -log10(p-value) and log2 fold change with the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds. The 40 most statistically significant genes are named.
DE Results: SubtypeB
More Plot Information Download CSV DataLog2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets probe.ID MAML2-mRNA -2.13 0.169 -2.46 -1.8 2.19e-17 8.69e-14 Notch NM_032427.1:4125 SPRY2-mRNA -3.04 0.322 -3.67 -2.41 6.99e-13 1.39e-09 JAK-STAT NM_005842.2:85 KIT-mRNA -3.78 0.41 -4.58 -2.97 1.68e-12 2.22e-09 Driver Gene, PI3K, RAS NM_000222.1:5 IL11RA-mRNA -2 0.232 -2.45 -1.54 1.42e-11 1.41e-08 JAK-STAT NM_147162.1:400 UBE2T-mRNA 2.99 0.37 2.26 3.71 9.89e-11 7.25e-08 DNARepair NM_014176.3:595 HIST1H3H-mRNA 2.86 0.355 2.16 3.55 1.09e-10 7.25e-08 TXmisReg NM_003536.2:355 SFRP1-mRNA -5.83 0.735 -7.27 -4.39 1.65e-10 9.39e-08 Wnt NM_003012.3:3320 IGF1-mRNA -3.19 0.406 -3.99 -2.4 2.05e-10 1.01e-07 PI3K, RAS, TXmisReg NM_000618.3:491 PPARG-mRNA -2.7 0.347 -3.38 -2.02 2.86e-10 1.01e-07 TXmisReg NM_015869.3:1035 FGF10-mRNA -3.06 0.394 -3.83 -2.29 2.99e-10 1.01e-07 MAPK, PI3K, RAS NM_004465.1:85 RUNX1T1-mRNA -2.72 0.35 -3.4 -2.03 3.11e-10 1.01e-07 TXmisReg NM_004349.2:1085 ITGA7-mRNA -3.16 0.407 -3.96 -2.36 3.14e-10 1.01e-07 PI3K NM_002206.1:1170 LIFR-mRNA -3.17 0.409 -3.97 -2.37 3.3e-10 1.01e-07 JAK-STAT NM_002310.3:2995 NTRK2-mRNA -4.28 0.561 -5.38 -3.19 4.75e-10 1.35e-07 MAPK NM_001007097.1:1605 ID4-mRNA -3.34 0.449 -4.22 -2.46 9.52e-10 2.52e-07 TGF-B NM_001546.2:2048 TSPAN7-mRNA -2.81 0.394 -3.58 -2.04 3.03e-09 7.53e-07 TXmisReg NM_004615.3:725 NGFR-mRNA -3.46 0.495 -4.43 -2.49 5.34e-09 1.25e-06 PI3K, RAS, TXmisReg NM_002507.1:2705 CCNA2-mRNA 2.06 0.297 1.48 2.65 6.1e-09 1.28e-06 CC.PLS.Apop NM_001237.2:1210 TGFBR2-mRNA -1.73 0.249 -2.22 -1.24 6.13e-09 1.28e-06 MAPK, TGF-B, TXmisReg NM_001024847.1:1760 EGFR-mRNA -3.46 0.506 -4.46 -2.47 8.82e-09 1.75e-06 Driver Gene, MAPK, PI3K, RAS NM_201282.1:360 DE Results: SubtypeB
Table presenting the most statistically significantly differentially expressed genes with the selected covariate. 'Estimated log fold-change' estimates a gene's differential expression. For categorical covariates, a gene is estimated to have 2^(log fold change) times its expression in baseline samples, holding all other variables in the analysis constant. If the covariate is continuous, for each unit increase in the selected covariate, a gene's expression is estimated to increase by 2^(log fold change)-fold, holding all other variables in the analysis constant. The 95% confidence interval for the log fold change is also presented, along with a p-value and an adjusted p-value or FDR if requested.
Volcano Plot: SubtypeC
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Volcano Plot: SubtypeC
Volcano plot displaying each gene's -log10(p-value) and log2 fold change with the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds. The 40 most statistically significant genes are named.
DE Results: SubtypeC
More Plot Information Download CSV DataLog2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets probe.ID EZH2-mRNA 2.92 0.314 2.31 3.54 1.15e-12 4.59e-09 Driver Gene NM_004456.3:190 CCNA2-mRNA 2.88 0.32 2.25 3.5 3.45e-12 6.71e-09 CC.PLS.Apop NM_001237.2:1210 FANCA-mRNA 2.85 0.323 2.22 3.49 6.54e-12 6.71e-09 DNARepair NM_000135.2:265 RUNX1T1-mRNA -3.32 0.377 -4.06 -2.58 6.75e-12 6.71e-09 TXmisReg NM_004349.2:1085 UBE2T-mRNA 3.4 0.398 2.62 4.18 1.73e-11 1.38e-08 DNARepair NM_014176.3:595 FGF10-mRNA -3.42 0.423 -4.25 -2.59 9.23e-11 5.8e-08 MAPK, PI3K, RAS NM_004465.1:85 PPARG-mRNA -3.01 0.373 -3.74 -2.28 1.02e-10 5.8e-08 TXmisReg NM_015869.3:1035 IL11RA-mRNA -1.97 0.25 -2.46 -1.48 1.93e-10 9.06e-08 JAK-STAT NM_147162.1:400 ZBTB16-mRNA -4.63 0.589 -5.79 -3.48 2.05e-10 9.06e-08 TXmisReg NM_006006.4:1585 TTK-mRNA 2.32 0.304 1.73 2.92 4.85e-10 1.93e-07 CC.PLS.Apop NM_003318.3:1200 SUV39H2-mRNA 2.06 0.272 1.52 2.59 6.14e-10 2.22e-07 ChromMod NM_024670.3:2035 GHR-mRNA -3.77 0.514 -4.78 -2.76 1.42e-09 4.69e-07 JAK-STAT, PI3K NM_000163.2:1835 PDGFD-mRNA -3.02 0.414 -3.83 -2.21 1.65e-09 4.92e-07 PI3K, RAS NM_025208.4:1120 IGF1-mRNA -3.17 0.436 -4.03 -2.32 1.85e-09 4.92e-07 PI3K, RAS, TXmisReg NM_000618.3:491 LIFR-mRNA -3.2 0.44 -4.06 -2.34 1.85e-09 4.92e-07 JAK-STAT NM_002310.3:2995 PKMYT1-mRNA 2.37 0.336 1.71 3.03 4.07e-09 9.61e-07 CC.PLS.Apop NM_004203.3:780 CDKN1C-mRNA -2.94 0.418 -3.76 -2.13 4.1e-09 9.61e-07 CC.PLS.Apop NM_000076.2:1605 HGF-mRNA -2.07 0.294 -2.64 -1.49 4.53e-09 9.76e-07 PI3K, RAS NM_000601.4:550 HIST1H3H-mRNA 2.68 0.382 1.93 3.43 4.66e-09 9.76e-07 TXmisReg NM_003536.2:355 ITGA7-mRNA -3.03 0.438 -3.89 -2.17 6.69e-09 1.33e-06 PI3K NM_002206.1:1170 DE Results: SubtypeC
Table presenting the most statistically significantly differentially expressed genes with the selected covariate. 'Estimated log fold-change' estimates a gene's differential expression. For categorical covariates, a gene is estimated to have 2^(log fold change) times its expression in baseline samples, holding all other variables in the analysis constant. If the covariate is continuous, for each unit increase in the selected covariate, a gene's expression is estimated to increase by 2^(log fold change)-fold, holding all other variables in the analysis constant. The 95% confidence interval for the log fold change is also presented, along with a p-value and an adjusted p-value or FDR if requested.
Volcano Plot: SubtypeD
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Volcano Plot: SubtypeD
Volcano plot displaying each gene's -log10(p-value) and log2 fold change with the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds. The 40 most statistically significant genes are named.
DE Results: SubtypeD
More Plot Information Download CSV DataLog2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets probe.ID MAML2-mRNA -1.8 0.176 -2.15 -1.46 4.48e-14 1.78e-10 Notch NM_032427.1:4125 ERBB2-mRNA 4.62 0.51 3.62 5.62 2.79e-12 5.56e-09 Driver Gene NM_004448.2:2380 KIT-mRNA -3.33 0.426 -4.17 -2.5 2.48e-10 3.29e-07 Driver Gene, PI3K, RAS NM_000222.1:5 SPRY2-mRNA -2.57 0.334 -3.23 -1.92 3.91e-10 3.89e-07 JAK-STAT NM_005842.2:85 UBE2T-mRNA 2.87 0.385 2.11 3.62 9.29e-10 6.58e-07 DNARepair NM_014176.3:595 EZH2-mRNA 2.26 0.303 1.66 2.85 1e-09 6.58e-07 Driver Gene NM_004456.3:190 IL11RA-mRNA -1.78 0.241 -2.26 -1.31 1.16e-09 6.58e-07 JAK-STAT NM_147162.1:400 PKMYT1-mRNA 2.34 0.324 1.7 2.98 2.24e-09 1.12e-06 CC.PLS.Apop NM_004203.3:780 HIST1H3H-mRNA 2.61 0.369 1.89 3.33 3.81e-09 1.68e-06 TXmisReg NM_003536.2:355 FGF10-mRNA -2.87 0.409 -3.68 -2.07 4.51e-09 1.79e-06 MAPK, PI3K, RAS NM_004465.1:85 NTRK2-mRNA -3.99 0.583 -5.13 -2.84 9.06e-09 3.28e-06 MAPK NM_001007097.1:1605 LIFR-mRNA -2.89 0.425 -3.73 -2.06 1.04e-08 3.45e-06 JAK-STAT NM_002310.3:2995 TTK-mRNA 1.98 0.294 1.41 2.56 1.28e-08 3.54e-06 CC.PLS.Apop NM_003318.3:1200 CCNA2-mRNA 2.08 0.309 1.47 2.69 1.32e-08 3.54e-06 CC.PLS.Apop NM_001237.2:1210 ITGA7-mRNA -2.85 0.424 -3.68 -2.02 1.34e-08 3.54e-06 PI3K NM_002206.1:1170 H2AFX-mRNA 2.15 0.33 1.5 2.79 2.95e-08 7.32e-06 DNARepair NM_002105.2:1392 CDKN2C-mRNA -1.91 0.295 -2.49 -1.33 3.37e-08 7.57e-06 CC.PLS.Apop, TXmisReg NM_001262.2:1295 RUNX1T1-mRNA -2.36 0.364 -3.07 -1.64 3.43e-08 7.57e-06 TXmisReg NM_004349.2:1085 CCNB1-mRNA 2.36 0.368 1.64 3.08 4.18e-08 8.75e-06 CC.PLS.Apop NM_031966.2:715 CDKN1C-mRNA -2.58 0.404 -3.38 -1.79 4.41e-08 8.78e-06 CC.PLS.Apop NM_000076.2:1605 DE Results: SubtypeD
Table presenting the most statistically significantly differentially expressed genes with the selected covariate. 'Estimated log fold-change' estimates a gene's differential expression. For categorical covariates, a gene is estimated to have 2^(log fold change) times its expression in baseline samples, holding all other variables in the analysis constant. If the covariate is continuous, for each unit increase in the selected covariate, a gene's expression is estimated to increase by 2^(log fold change)-fold, holding all other variables in the analysis constant. The 95% confidence interval for the log fold change is also presented, along with a p-value and an adjusted p-value or FDR if requested.
The results of differential expression testing are summarized at the gene set level. Each gene set's most differentially expressed genes are identified, and the extent of differential expression in each gene set is summarized using a 'global significance score'.
Global Significance Scores
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Global Significance Scores
Heatmap displaying each sample's global significance scores. Global significance statistics measure the extent of differential expression of a gene set's genes with a covariate, ignoring whether each gene within the set is up- or down-regulated. Orange denotes gene sets whose genes exhibit extensive differential expression with the covariate, blue denotes gene sets with less differential expression.
Directed Global Significance Scores
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Directed Global Significance Scores
Heatmap displaying each sample's directed global significance scores. Directed global significance statistics measure the extent to which a gene set's genes are up- or down-regulated with the variable. Red denotes gene sets whose genes exhibit extensive over-expression with the covariate, blue denotes gene sets with extensive under-expression.
Undirected and Directed global significance scores table
More Plot Information Download CSV DataUndirected Subtype: differential expression in A vs. baseline of Normal Undirected Subtype: differential expression in B vs. baseline of Normal Undirected Subtype: differential expression in C vs. baseline of Normal Undirected Subtype: differential expression in D vs. baseline of Normal Directed Subtype: differential expression in A vs. baseline of Normal Directed Subtype: differential expression in B vs. baseline of Normal Directed Subtype: differential expression in C vs. baseline of Normal Directed Subtype: differential expression in D vs. baseline of Normal CC.PLS.Apop 1.804 2.664 3.168 2.824 -0.135 1.182 2.226 1.796 ChromMod 1.375 2.097 2.858 2.225 0.322 -0.699 1.906 1.418 DNARepair 1.74 2.756 3.39 2.911 0.865 2.235 2.874 2.426 Driver Gene 1.95 2.495 2.659 2.583 -1.011 -1.317 0.207 1.014 HH 1.557 2.195 2.145 1.966 -0.905 -1.782 -1.376 -0.97 JAK-STAT 2.317 3.258 3.074 2.879 -1.571 -2.681 -2.532 -2.078 MAPK 2.013 2.583 2.521 2.406 -1.237 -2.056 -1.95 -1.642 Notch 2.869 3.558 2.705 2.998 -2.816 -3.48 -2.446 -2.772 PI3K 2.131 2.977 2.745 2.697 -1.125 -2.033 -1.941 -1.365 RAS 2.226 3.136 2.876 2.742 -1.653 -2.691 -2.324 -1.927 TGF-B 2.195 2.948 2.792 2.362 -0.78 -1.953 -1.562 -1.172 TXmisReg 2.264 3.285 3.132 2.885 -1.551 -2.304 -2.181 -1.609 Wnt 1.814 2.499 2.164 2.2 -1.241 -2.051 -1.438 -1.49 Undirected and Directed global significance scores table
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
- Subtype:
- SubtypeA
- SubtypeB
- SubtypeC
- SubtypeD
Volcano Plot: SubtypeA
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Volcano Plot: SubtypeA
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - CC.PLS.Apop genes - SubtypeA
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all CDKN2C-mRNA -1.81 0.301 -2.4 -1.22 1.97e-07 0.000155 CC.PLS.Apop, TXmisReg NS_CANCERPATH_C2535 CDKN2C mRNA 0 CC.PLS.Apop;TXmisReg hsa04110;hsa05166;hsa05202 CDKN2C chartreuse1 16 -6.01328903654485 CDKN1C-mRNA -2.27 0.412 -3.07 -1.46 1.19e-06 0.000491 CC.PLS.Apop NS_CANCERPATH_C2535 CDKN1C mRNA 0 CC.PLS.Apop hsa04110 CDKN1C chartreuse1 16 -5.50970873786408 PIK3R1-mRNA -1.47 0.322 -2.1 -0.838 3.11e-05 0.00562 CC.PLS.Apop, Driver Gene, JAK-STAT, PI3K, RAS NS_CANCERPATH_C2535 PIK3R1 mRNA 0 CC.PLS.Apop;RAS;PI3K;JAK-STAT;Driver Gene hsa04012;hsa04014;hsa04015;hsa04022;hsa04024;hsa04062;hsa04066;hsa04068;hsa04070;hsa04071;hsa04072;hsa04150;hsa04151;hsa04152;hsa04210;hsa04211;hsa04261;hsa04370;hsa04380;hsa04510;hsa04550;hsa04611;hsa04620;hsa04630;hsa04650;hsa04660;hsa04662;hsa04664;hsa04666;hsa04668;hsa04670;hsa04722;hsa04725;hsa04750;hsa04810;hsa04910;hsa04914;hsa04915;hsa04917;hsa04919;hsa04921;hsa04923;hsa04930;hsa04931;hsa04932;hsa04933;hsa04960;hsa04973;hsa05100;hsa05142;hsa05145;hsa05146;hsa05160;hsa05161;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05220;hsa05221;hsa05222;hsa05223;hsa05230;hsa05231 PIK3R1 chartreuse1 16 -4.56521739130435 CDC14B-mRNA -1.17 0.275 -1.71 -0.635 8.39e-05 0.0108 CC.PLS.Apop NS_CANCERPATH_C2535 CDC14B mRNA 0 CC.PLS.Apop hsa04110 CDC14B chartreuse2 16 -4.25454545454545 PKMYT1-mRNA 1.18 0.331 0.534 1.83 0.000775 0.0656 CC.PLS.Apop NS_CANCERPATH_C2535 PKMYT1 mRNA 0 CC.PLS.Apop hsa04110;hsa04114;hsa04914 PKMYT1 chartreuse3 16 3.56495468277946 ABL1-mRNA -0.846 0.249 -1.33 -0.359 0.00129 0.103 CC.PLS.Apop, Driver Gene, RAS NS_CANCERPATH_C2535 ABL1 mRNA 0 CC.PLS.Apop;RAS;Driver Gene hsa04012;hsa04014;hsa04110;hsa04360;hsa04722;hsa05130;hsa05131;hsa05200;hsa05206;hsa05220;hsa05416 ABL1 chartreuse4 16 -3.39759036144578 MYC-mRNA -1.91 0.567 -3.02 -0.794 0.00146 0.112 CC.PLS.Apop, JAK-STAT, MAPK, PI3K, TGF-B, TXmisReg, Wnt NS_CANCERPATH_C2535 MYC mRNA 0 CC.PLS.Apop;PI3K;JAK-STAT;MAPK;TGF-B;TXmisReg;Wnt hsa04010;hsa04012;hsa04110;hsa04151;hsa04310;hsa04350;hsa04390;hsa04550;hsa04630;hsa04919;hsa05161;hsa05166;hsa05169;hsa05200;hsa05202;hsa05205;hsa05206;hsa05210;hsa05213;hsa05216;hsa05219;hsa05220;hsa05221;hsa05222;hsa05230 MYC chartreuse4 16 -3.36860670194004 CDKN2D-mRNA 1.28 0.388 0.518 2.04 0.00178 0.127 CC.PLS.Apop NS_CANCERPATH_C2535 CDKN2D mRNA 0 CC.PLS.Apop hsa04068;hsa04110 CDKN2D chartreuse4 16 3.29896907216495 MYD88-mRNA 0.729 0.224 0.29 1.17 0.00198 0.138 CC.PLS.Apop, Driver Gene NS_CANCERPATH_C2535 MYD88 mRNA 0 CC.PLS.Apop;Driver Gene hsa04064;hsa04210;hsa04620;hsa05132;hsa05133;hsa05134;hsa05140;hsa05142;hsa05143;hsa05144;hsa05145;hsa05152;hsa05161;hsa05162;hsa05164;hsa05168 MYD88 chartreuse4 16 3.25446428571429 CCNE2-mRNA 1.17 0.368 0.448 1.89 0.00249 0.165 CC.PLS.Apop, PI3K NS_CANCERPATH_C2535 CCNE2 mRNA 0 CC.PLS.Apop;PI3K hsa04110;hsa04114;hsa04115;hsa04151;hsa05161;hsa05162;hsa05200;hsa05203;hsa05206;hsa05215;hsa05222 CCNE2 chartreuse4 16 3.17934782608696 PIK3R5-mRNA 0.867 0.277 0.324 1.41 0.00288 0.181 CC.PLS.Apop, JAK-STAT, PI3K, RAS NS_CANCERPATH_C2535 PIK3R5 mRNA 0 CC.PLS.Apop;RAS;PI3K;JAK-STAT hsa04012;hsa04014;hsa04015;hsa04022;hsa04024;hsa04062;hsa04066;hsa04068;hsa04070;hsa04071;hsa04072;hsa04150;hsa04151;hsa04152;hsa04210;hsa04211;hsa04261;hsa04370;hsa04380;hsa04510;hsa04550;hsa04611;hsa04620;hsa04630;hsa04650;hsa04660;hsa04662;hsa04664;hsa04666;hsa04668;hsa04670;hsa04722;hsa04725;hsa04750;hsa04810;hsa04910;hsa04914;hsa04915;hsa04917;hsa04919;hsa04921;hsa04923;hsa04930;hsa04931;hsa04932;hsa04933;hsa04960;hsa04973;hsa05100;hsa05142;hsa05145;hsa05146;hsa05160;hsa05161;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05220;hsa05221;hsa05222;hsa05223;hsa05230;hsa05231 PIK3R5 chartreuse4 16 3.12996389891697 PTTG2-mRNA 1.15 0.367 0.427 1.86 0.00292 0.181 CC.PLS.Apop NS_CANCERPATH_C2535 PTTG2 mRNA 0 CC.PLS.Apop hsa04110;hsa04114;hsa05166 PTTG2 chartreuse4 16 3.13351498637602 PRKAR1B-mRNA -1.03 0.336 -1.69 -0.375 0.00332 0.187 CC.PLS.Apop NS_CANCERPATH_C2535 PRKAR1B mRNA 0 CC.PLS.Apop hsa04210;hsa04910 PRKAR1B chartreuse4 16 -3.06547619047619 IKBKB-mRNA 0.771 0.256 0.269 1.27 0.00403 0.211 CC.PLS.Apop, MAPK, PI3K, RAS NS_CANCERPATH_C2535 IKBKB mRNA 0 CC.PLS.Apop;RAS;PI3K;MAPK hsa04010;hsa04014;hsa04062;hsa04064;hsa04068;hsa04150;hsa04151;hsa04210;hsa04380;hsa04620;hsa04621;hsa04622;hsa04623;hsa04660;hsa04662;hsa04668;hsa04722;hsa04910;hsa04920;hsa04930;hsa04931;hsa04932;hsa05120;hsa05131;hsa05142;hsa05145;hsa05160;hsa05161;hsa05164;hsa05166;hsa05168;hsa05169;hsa05200;hsa05206;hsa05212;hsa05215;hsa05220;hsa05221;hsa05222 IKBKB chartreuse4 16 3.01171875 FASLG-mRNA 0.836 0.284 0.279 1.39 0.0049 0.24 CC.PLS.Apop, MAPK, PI3K, RAS NS_CANCERPATH_C2535 FASLG mRNA 0 CC.PLS.Apop;RAS;PI3K;MAPK hsa04010;hsa04014;hsa04060;hsa04068;hsa04151;hsa04210;hsa04650;hsa04722;hsa04932;hsa04940;hsa05142;hsa05143;hsa05161;hsa05162;hsa05164;hsa05168;hsa05200;hsa05205;hsa05320;hsa05330;hsa05332 FASLG chartreuse4 16 2.94366197183099 BAX-mRNA 0.607 0.212 0.19 1.02 0.00615 0.278 CC.PLS.Apop NS_CANCERPATH_C2535 BAX mRNA 0 CC.PLS.Apop hsa04071;hsa04115;hsa04141;hsa04210;hsa04211;hsa04722;hsa04932;hsa04933;hsa05014;hsa05016;hsa05020;hsa05152;hsa05161;hsa05166;hsa05200;hsa05203;hsa05210 BAX chartreuse4 16 2.86320754716981 NFKBIA-mRNA -0.857 0.311 -1.47 -0.249 0.00793 0.329 CC.PLS.Apop NS_CANCERPATH_C2535 NFKBIA mRNA 0 CC.PLS.Apop hsa04024;hsa04062;hsa04064;hsa04210;hsa04380;hsa04620;hsa04621;hsa04622;hsa04623;hsa04660;hsa04662;hsa04668;hsa04722;hsa04920;hsa04931;hsa05120;hsa05131;hsa05134;hsa05140;hsa05142;hsa05145;hsa05160;hsa05161;hsa05162;hsa05164;hsa05166;hsa05168;hsa05169;hsa05200;hsa05203;hsa05215;hsa05220;hsa05222 NFKBIA chartreuse4 16 -2.7556270096463 CCNB1-mRNA 1.03 0.376 0.297 1.77 0.0082 0.336 CC.PLS.Apop NS_CANCERPATH_C2535 CCNB1 mRNA 0 CC.PLS.Apop hsa04068;hsa04110;hsa04114;hsa04115;hsa04914 CCNB1 chartreuse4 16 2.73936170212766 CCNA2-mRNA 0.851 0.315 0.232 1.47 0.00942 0.374 CC.PLS.Apop NS_CANCERPATH_C2535 CCNA2 mRNA 0 CC.PLS.Apop hsa04110;hsa04152;hsa04914;hsa05161;hsa05169;hsa05203 CCNA2 chartreuse4 16 2.7015873015873 E2F1-mRNA 1 0.372 0.273 1.73 0.00952 0.374 CC.PLS.Apop NS_CANCERPATH_C2535 E2F1 mRNA 0 CC.PLS.Apop hsa04110;hsa05161;hsa05166;hsa05200;hsa05206;hsa05212;hsa05214;hsa05215;hsa05218;hsa05219;hsa05220;hsa05222;hsa05223 E2F1 chartreuse4 16 2.68817204301075 DE Results - CC.PLS.Apop genes - SubtypeA
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
Volcano Plot: SubtypeB
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Volcano Plot: SubtypeB
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - CC.PLS.Apop genes - SubtypeB
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all CCNA2-mRNA 2.06 0.297 1.48 2.65 6.1e-09 1.28e-06 CC.PLS.Apop NS_CANCERPATH_C2535 CCNA2 mRNA 0 CC.PLS.Apop hsa04110;hsa04152;hsa04914;hsa05161;hsa05169;hsa05203 CCNA2 chartreuse1 16 6.93602693602694 PKMYT1-mRNA 2.12 0.312 1.51 2.73 1.08e-08 1.95e-06 CC.PLS.Apop NS_CANCERPATH_C2535 PKMYT1 mRNA 0 CC.PLS.Apop hsa04110;hsa04114;hsa04914 PKMYT1 chartreuse1 16 6.7948717948718 CDKN1C-mRNA -2.6 0.388 -3.36 -1.84 1.49e-08 2.37e-06 CC.PLS.Apop NS_CANCERPATH_C2535 CDKN1C mRNA 0 CC.PLS.Apop hsa04110 CDKN1C chartreuse1 16 -6.70103092783505 PIK3R1-mRNA -1.92 0.303 -2.52 -1.33 5.54e-08 8.16e-06 CC.PLS.Apop, Driver Gene, JAK-STAT, PI3K, RAS NS_CANCERPATH_C2535 PIK3R1 mRNA 0 CC.PLS.Apop;RAS;PI3K;JAK-STAT;Driver Gene hsa04012;hsa04014;hsa04015;hsa04022;hsa04024;hsa04062;hsa04066;hsa04068;hsa04070;hsa04071;hsa04072;hsa04150;hsa04151;hsa04152;hsa04210;hsa04211;hsa04261;hsa04370;hsa04380;hsa04510;hsa04550;hsa04611;hsa04620;hsa04630;hsa04650;hsa04660;hsa04662;hsa04664;hsa04666;hsa04668;hsa04670;hsa04722;hsa04725;hsa04750;hsa04810;hsa04910;hsa04914;hsa04915;hsa04917;hsa04919;hsa04921;hsa04923;hsa04930;hsa04931;hsa04932;hsa04933;hsa04960;hsa04973;hsa05100;hsa05142;hsa05145;hsa05146;hsa05160;hsa05161;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05220;hsa05221;hsa05222;hsa05223;hsa05230;hsa05231 PIK3R1 chartreuse1 16 -6.33663366336634 CCNB1-mRNA 2.24 0.354 1.55 2.93 5.86e-08 8.33e-06 CC.PLS.Apop NS_CANCERPATH_C2535 CCNB1 mRNA 0 CC.PLS.Apop hsa04068;hsa04110;hsa04114;hsa04115;hsa04914 CCNB1 chartreuse1 16 6.32768361581921 CDKN2C-mRNA -1.77 0.284 -2.33 -1.21 8.12e-08 1.06e-05 CC.PLS.Apop, TXmisReg NS_CANCERPATH_C2535 CDKN2C mRNA 0 CC.PLS.Apop;TXmisReg hsa04110;hsa05166;hsa05202 CDKN2C chartreuse1 16 -6.23239436619718 CDC14B-mRNA -1.59 0.259 -2.1 -1.08 1.17e-07 1.33e-05 CC.PLS.Apop NS_CANCERPATH_C2535 CDC14B mRNA 0 CC.PLS.Apop hsa04110 CDC14B chartreuse1 16 -6.13899613899614 TTK-mRNA 1.62 0.283 1.06 2.17 5.53e-07 5.64e-05 CC.PLS.Apop NS_CANCERPATH_C2535 TTK mRNA 0 CC.PLS.Apop hsa04110 TTK chartreuse1 16 5.7243816254417 E2F1-mRNA 1.87 0.351 1.18 2.55 2.24e-06 0.000194 CC.PLS.Apop NS_CANCERPATH_C2535 E2F1 mRNA 0 CC.PLS.Apop hsa04110;hsa05161;hsa05166;hsa05200;hsa05206;hsa05212;hsa05214;hsa05215;hsa05218;hsa05219;hsa05220;hsa05222;hsa05223 E2F1 chartreuse1 16 5.32763532763533 PTTG2-mRNA 1.83 0.346 1.15 2.51 2.38e-06 0.000202 CC.PLS.Apop NS_CANCERPATH_C2535 PTTG2 mRNA 0 CC.PLS.Apop hsa04110;hsa04114;hsa05166 PTTG2 chartreuse1 16 5.28901734104046 CCNE2-mRNA 1.77 0.347 1.09 2.45 4.61e-06 0.000328 CC.PLS.Apop, PI3K NS_CANCERPATH_C2535 CCNE2 mRNA 0 CC.PLS.Apop;PI3K hsa04110;hsa04114;hsa04115;hsa04151;hsa05161;hsa05162;hsa05200;hsa05203;hsa05206;hsa05215;hsa05222 CCNE2 chartreuse1 16 5.10086455331412 CDC6-mRNA 2.03 0.457 1.14 2.93 4.58e-05 0.0025 CC.PLS.Apop NS_CANCERPATH_C2535 CDC6 mRNA 0 CC.PLS.Apop hsa04110 CDC6 chartreuse1 16 4.44201312910284 BAX-mRNA 0.866 0.2 0.473 1.26 6.97e-05 0.00347 CC.PLS.Apop NS_CANCERPATH_C2535 BAX mRNA 0 CC.PLS.Apop hsa04071;hsa04115;hsa04141;hsa04210;hsa04211;hsa04722;hsa04932;hsa04933;hsa05014;hsa05016;hsa05020;hsa05152;hsa05161;hsa05166;hsa05200;hsa05203;hsa05210 BAX chartreuse1 16 4.33 MYD88-mRNA 0.879 0.211 0.465 1.29 0.000117 0.00559 CC.PLS.Apop, Driver Gene NS_CANCERPATH_C2535 MYD88 mRNA 0 CC.PLS.Apop;Driver Gene hsa04064;hsa04210;hsa04620;hsa05132;hsa05133;hsa05134;hsa05140;hsa05142;hsa05143;hsa05144;hsa05145;hsa05152;hsa05161;hsa05162;hsa05164;hsa05168 MYD88 chartreuse1 16 4.16587677725119 CDC25A-mRNA 1.16 0.283 0.608 1.72 0.000143 0.00675 CC.PLS.Apop NS_CANCERPATH_C2535 CDC25A mRNA 0 CC.PLS.Apop hsa04110;hsa04914;hsa05206 CDC25A chartreuse1 16 4.09893992932862 CCND2-mRNA -1.25 0.306 -1.85 -0.652 0.00015 0.00694 CC.PLS.Apop, JAK-STAT, PI3K, TXmisReg, Wnt NS_CANCERPATH_C2535 CCND2 mRNA 0 CC.PLS.Apop;PI3K;JAK-STAT;TXmisReg;Wnt hsa04068;hsa04110;hsa04115;hsa04151;hsa04310;hsa04390;hsa04510;hsa04630;hsa04917;hsa05162;hsa05166;hsa05202;hsa05203;hsa05206 CCND2 chartreuse1 16 -4.08496732026144 PRKAR1B-mRNA -1.27 0.316 -1.89 -0.646 0.000198 0.00897 CC.PLS.Apop NS_CANCERPATH_C2535 PRKAR1B mRNA 0 CC.PLS.Apop hsa04210;hsa04910 PRKAR1B chartreuse2 16 -4.01898734177215 MCM2-mRNA 1.08 0.284 0.526 1.64 0.00037 0.0165 CC.PLS.Apop NS_CANCERPATH_C2535 MCM2 mRNA 0 CC.PLS.Apop hsa03030;hsa04110 MCM2 chartreuse2 16 3.80281690140845 MCM4-mRNA 1.12 0.297 0.539 1.7 0.000415 0.0177 CC.PLS.Apop NS_CANCERPATH_C2535 MCM4 mRNA 0 CC.PLS.Apop hsa03030;hsa04110 MCM4 chartreuse2 16 3.77104377104377 PRKAR2B-mRNA -1.85 0.494 -2.82 -0.882 0.000451 0.0189 CC.PLS.Apop NS_CANCERPATH_C2535 PRKAR2B mRNA 0 CC.PLS.Apop hsa04210;hsa04910 PRKAR2B chartreuse2 16 -3.74493927125506 DE Results - CC.PLS.Apop genes - SubtypeB
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
Volcano Plot: SubtypeC
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Volcano Plot: SubtypeC
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - CC.PLS.Apop genes - SubtypeC
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all CCNA2-mRNA 2.88 0.32 2.25 3.5 3.45e-12 6.71e-09 CC.PLS.Apop NS_CANCERPATH_C2535 CCNA2 mRNA 0 CC.PLS.Apop hsa04110;hsa04152;hsa04914;hsa05161;hsa05169;hsa05203 CCNA2 chartreuse1 16 9 TTK-mRNA 2.32 0.304 1.73 2.92 4.85e-10 1.93e-07 CC.PLS.Apop NS_CANCERPATH_C2535 TTK mRNA 0 CC.PLS.Apop hsa04110 TTK chartreuse1 16 7.63157894736842 PKMYT1-mRNA 2.37 0.336 1.71 3.03 4.07e-09 9.61e-07 CC.PLS.Apop NS_CANCERPATH_C2535 PKMYT1 mRNA 0 CC.PLS.Apop hsa04110;hsa04114;hsa04914 PKMYT1 chartreuse1 16 7.05357142857143 CDKN1C-mRNA -2.94 0.418 -3.76 -2.13 4.1e-09 9.61e-07 CC.PLS.Apop NS_CANCERPATH_C2535 CDKN1C mRNA 0 CC.PLS.Apop hsa04110 CDKN1C chartreuse1 16 -7.03349282296651 CDC25A-mRNA 2.05 0.305 1.45 2.65 1.33e-08 2.41e-06 CC.PLS.Apop NS_CANCERPATH_C2535 CDC25A mRNA 0 CC.PLS.Apop hsa04110;hsa04914;hsa05206 CDC25A chartreuse1 16 6.72131147540984 MCM2-mRNA 2.02 0.306 1.42 2.62 2.03e-08 3.36e-06 CC.PLS.Apop NS_CANCERPATH_C2535 MCM2 mRNA 0 CC.PLS.Apop hsa03030;hsa04110 MCM2 chartreuse1 16 6.60130718954248 CCNE1-mRNA 2.38 0.384 1.62 3.13 9.66e-08 1.24e-05 CC.PLS.Apop, PI3K NS_CANCERPATH_C2535 CCNE1 mRNA 0 CC.PLS.Apop;PI3K hsa04110;hsa04114;hsa04115;hsa04151;hsa05161;hsa05162;hsa05200;hsa05203;hsa05206;hsa05215;hsa05222 CCNE1 chartreuse1 16 6.19791666666667 PIK3R1-mRNA -2.01 0.326 -2.65 -1.37 1.06e-07 1.31e-05 CC.PLS.Apop, Driver Gene, JAK-STAT, PI3K, RAS NS_CANCERPATH_C2535 PIK3R1 mRNA 0 CC.PLS.Apop;RAS;PI3K;JAK-STAT;Driver Gene hsa04012;hsa04014;hsa04015;hsa04022;hsa04024;hsa04062;hsa04066;hsa04068;hsa04070;hsa04071;hsa04072;hsa04150;hsa04151;hsa04152;hsa04210;hsa04211;hsa04261;hsa04370;hsa04380;hsa04510;hsa04550;hsa04611;hsa04620;hsa04630;hsa04650;hsa04660;hsa04662;hsa04664;hsa04666;hsa04668;hsa04670;hsa04722;hsa04725;hsa04750;hsa04810;hsa04910;hsa04914;hsa04915;hsa04917;hsa04919;hsa04921;hsa04923;hsa04930;hsa04931;hsa04932;hsa04933;hsa04960;hsa04973;hsa05100;hsa05142;hsa05145;hsa05146;hsa05160;hsa05161;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05220;hsa05221;hsa05222;hsa05223;hsa05230;hsa05231 PIK3R1 chartreuse1 16 -6.16564417177914 CCNB1-mRNA 2.32 0.381 1.57 3.06 1.4e-07 1.62e-05 CC.PLS.Apop NS_CANCERPATH_C2535 CCNB1 mRNA 0 CC.PLS.Apop hsa04068;hsa04110;hsa04114;hsa04115;hsa04914 CCNB1 chartreuse1 16 6.08923884514436 CHEK1-mRNA 2.03 0.35 1.35 2.72 3.89e-07 4.08e-05 CC.PLS.Apop NS_CANCERPATH_C2535 CHEK1 mRNA 0 CC.PLS.Apop hsa04110;hsa04115;hsa05166;hsa05203 CHEK1 chartreuse1 16 5.8 MYD88-mRNA 1.28 0.227 0.84 1.73 6.52e-07 6.32e-05 CC.PLS.Apop, Driver Gene NS_CANCERPATH_C2535 MYD88 mRNA 0 CC.PLS.Apop;Driver Gene hsa04064;hsa04210;hsa04620;hsa05132;hsa05133;hsa05134;hsa05140;hsa05142;hsa05143;hsa05144;hsa05145;hsa05152;hsa05161;hsa05162;hsa05164;hsa05168 MYD88 chartreuse1 16 5.63876651982379 PTTG2-mRNA 2.09 0.372 1.36 2.82 7.64e-07 7.07e-05 CC.PLS.Apop NS_CANCERPATH_C2535 PTTG2 mRNA 0 CC.PLS.Apop hsa04110;hsa04114;hsa05166 PTTG2 chartreuse1 16 5.61827956989247 E2F1-mRNA 2.09 0.377 1.35 2.83 1.01e-06 8.92e-05 CC.PLS.Apop NS_CANCERPATH_C2535 E2F1 mRNA 0 CC.PLS.Apop hsa04110;hsa05161;hsa05166;hsa05200;hsa05206;hsa05212;hsa05214;hsa05215;hsa05218;hsa05219;hsa05220;hsa05222;hsa05223 E2F1 chartreuse1 16 5.54376657824934 MCM4-mRNA 1.73 0.32 1.1 2.35 1.7e-06 0.000138 CC.PLS.Apop NS_CANCERPATH_C2535 MCM4 mRNA 0 CC.PLS.Apop hsa03030;hsa04110 MCM4 chartreuse1 16 5.40625 PRKDC-mRNA 1.43 0.269 0.906 1.96 2.15e-06 0.000168 CC.PLS.Apop, DNARepair NS_CANCERPATH_C2535 PRKDC mRNA 0 CC.PLS.Apop;DNARepair hsa03450;hsa04110 PRKDC chartreuse1 16 5.31598513011152 CHEK2-mRNA 1.37 0.258 0.867 1.88 2.23e-06 0.00017 CC.PLS.Apop NS_CANCERPATH_C2535 CHEK2 mRNA 0 CC.PLS.Apop hsa04110;hsa04115;hsa05166 CHEK2 chartreuse1 16 5.31007751937985 CDC7-mRNA 2.03 0.396 1.25 2.81 4.56e-06 0.000318 CC.PLS.Apop NS_CANCERPATH_C2535 CDC7 mRNA 0 CC.PLS.Apop hsa04110 CDC7 chartreuse1 16 5.12626262626263 CCNE2-mRNA 1.82 0.373 1.09 2.55 1e-05 0.000675 CC.PLS.Apop, PI3K NS_CANCERPATH_C2535 CCNE2 mRNA 0 CC.PLS.Apop;PI3K hsa04110;hsa04114;hsa04115;hsa04151;hsa05161;hsa05162;hsa05200;hsa05203;hsa05206;hsa05215;hsa05222 CCNE2 chartreuse1 16 4.87935656836461 CDKN2C-mRNA -1.4 0.305 -2 -0.805 2.77e-05 0.00178 CC.PLS.Apop, TXmisReg NS_CANCERPATH_C2535 CDKN2C mRNA 0 CC.PLS.Apop;TXmisReg hsa04110;hsa05166;hsa05202 CDKN2C chartreuse1 16 -4.59016393442623 CDC6-mRNA 2.25 0.491 1.29 3.21 2.92e-05 0.00184 CC.PLS.Apop NS_CANCERPATH_C2535 CDC6 mRNA 0 CC.PLS.Apop hsa04110 CDC6 chartreuse1 16 4.58248472505092 DE Results - CC.PLS.Apop genes - SubtypeC
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
Volcano Plot: SubtypeD
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Volcano Plot: SubtypeD
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - CC.PLS.Apop genes - SubtypeD
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all PKMYT1-mRNA 2.34 0.324 1.7 2.98 2.24e-09 1.12e-06 CC.PLS.Apop NS_CANCERPATH_C2535 PKMYT1 mRNA 0 CC.PLS.Apop hsa04110;hsa04114;hsa04914 PKMYT1 chartreuse1 16 7.22222222222222 TTK-mRNA 1.98 0.294 1.41 2.56 1.28e-08 3.54e-06 CC.PLS.Apop NS_CANCERPATH_C2535 TTK mRNA 0 CC.PLS.Apop hsa04110 TTK chartreuse1 16 6.73469387755102 CCNA2-mRNA 2.08 0.309 1.47 2.69 1.32e-08 3.54e-06 CC.PLS.Apop NS_CANCERPATH_C2535 CCNA2 mRNA 0 CC.PLS.Apop hsa04110;hsa04152;hsa04914;hsa05161;hsa05169;hsa05203 CCNA2 chartreuse1 16 6.73139158576052 CDKN2C-mRNA -1.91 0.295 -2.49 -1.33 3.37e-08 7.57e-06 CC.PLS.Apop, TXmisReg NS_CANCERPATH_C2535 CDKN2C mRNA 0 CC.PLS.Apop;TXmisReg hsa04110;hsa05166;hsa05202 CDKN2C chartreuse1 16 -6.47457627118644 CCNB1-mRNA 2.36 0.368 1.64 3.08 4.18e-08 8.75e-06 CC.PLS.Apop NS_CANCERPATH_C2535 CCNB1 mRNA 0 CC.PLS.Apop hsa04068;hsa04110;hsa04114;hsa04115;hsa04914 CCNB1 chartreuse1 16 6.41304347826087 CDKN1C-mRNA -2.58 0.404 -3.38 -1.79 4.41e-08 8.78e-06 CC.PLS.Apop NS_CANCERPATH_C2535 CDKN1C mRNA 0 CC.PLS.Apop hsa04110 CDKN1C chartreuse1 16 -6.38613861386139 CDC6-mRNA 2.92 0.474 1.99 3.85 1.1e-07 2e-05 CC.PLS.Apop NS_CANCERPATH_C2535 CDC6 mRNA 0 CC.PLS.Apop hsa04110 CDC6 chartreuse1 16 6.16033755274262 CCNE2-mRNA 2.19 0.36 1.48 2.9 1.46e-07 2.37e-05 CC.PLS.Apop, PI3K NS_CANCERPATH_C2535 CCNE2 mRNA 0 CC.PLS.Apop;PI3K hsa04110;hsa04114;hsa04115;hsa04151;hsa05161;hsa05162;hsa05200;hsa05203;hsa05206;hsa05215;hsa05222 CCNE2 chartreuse1 16 6.08333333333333 E2F1-mRNA 2.16 0.365 1.45 2.88 2.53e-07 3.21e-05 CC.PLS.Apop NS_CANCERPATH_C2535 E2F1 mRNA 0 CC.PLS.Apop hsa04110;hsa05161;hsa05166;hsa05200;hsa05206;hsa05212;hsa05214;hsa05215;hsa05218;hsa05219;hsa05220;hsa05222;hsa05223 E2F1 chartreuse1 16 5.91780821917808 CDC14B-mRNA -1.44 0.27 -1.97 -0.913 2.01e-06 2e-04 CC.PLS.Apop NS_CANCERPATH_C2535 CDC14B mRNA 0 CC.PLS.Apop hsa04110 CDC14B chartreuse1 16 -5.33333333333333 PTTG2-mRNA 1.84 0.359 1.14 2.54 4.49e-06 0.00038 CC.PLS.Apop NS_CANCERPATH_C2535 PTTG2 mRNA 0 CC.PLS.Apop hsa04110;hsa04114;hsa05166 PTTG2 chartreuse1 16 5.12534818941504 CHEK2-mRNA 1.22 0.249 0.729 1.71 1.04e-05 0.000777 CC.PLS.Apop NS_CANCERPATH_C2535 CHEK2 mRNA 0 CC.PLS.Apop hsa04110;hsa04115;hsa05166 CHEK2 chartreuse1 16 4.8995983935743 MYD88-mRNA 1.04 0.219 0.612 1.47 1.62e-05 0.00113 CC.PLS.Apop, Driver Gene NS_CANCERPATH_C2535 MYD88 mRNA 0 CC.PLS.Apop;Driver Gene hsa04064;hsa04210;hsa04620;hsa05132;hsa05133;hsa05134;hsa05140;hsa05142;hsa05143;hsa05144;hsa05145;hsa05152;hsa05161;hsa05162;hsa05164;hsa05168 MYD88 chartreuse1 16 4.74885844748858 MCM4-mRNA 1.39 0.309 0.782 1.99 4e-05 0.00253 CC.PLS.Apop NS_CANCERPATH_C2535 MCM4 mRNA 0 CC.PLS.Apop hsa03030;hsa04110 MCM4 chartreuse1 16 4.49838187702265 MCM2-mRNA 1.32 0.296 0.739 1.9 4.38e-05 0.00272 CC.PLS.Apop NS_CANCERPATH_C2535 MCM2 mRNA 0 CC.PLS.Apop hsa03030;hsa04110 MCM2 chartreuse1 16 4.45945945945946 CCNE1-mRNA 1.64 0.371 0.909 2.36 5.2e-05 0.00318 CC.PLS.Apop, PI3K NS_CANCERPATH_C2535 CCNE1 mRNA 0 CC.PLS.Apop;PI3K hsa04110;hsa04114;hsa04115;hsa04151;hsa05161;hsa05162;hsa05200;hsa05203;hsa05206;hsa05215;hsa05222 CCNE1 chartreuse1 16 4.42048517520216 CDC25A-mRNA 1.29 0.294 0.708 1.86 6.03e-05 0.00363 CC.PLS.Apop NS_CANCERPATH_C2535 CDC25A mRNA 0 CC.PLS.Apop hsa04110;hsa04914;hsa05206 CDC25A chartreuse1 16 4.38775510204082 PIK3R1-mRNA -1.3 0.315 -1.92 -0.683 0.000133 0.00749 CC.PLS.Apop, Driver Gene, JAK-STAT, PI3K, RAS NS_CANCERPATH_C2535 PIK3R1 mRNA 0 CC.PLS.Apop;RAS;PI3K;JAK-STAT;Driver Gene hsa04012;hsa04014;hsa04015;hsa04022;hsa04024;hsa04062;hsa04066;hsa04068;hsa04070;hsa04071;hsa04072;hsa04150;hsa04151;hsa04152;hsa04210;hsa04211;hsa04261;hsa04370;hsa04380;hsa04510;hsa04550;hsa04611;hsa04620;hsa04630;hsa04650;hsa04660;hsa04662;hsa04664;hsa04666;hsa04668;hsa04670;hsa04722;hsa04725;hsa04750;hsa04810;hsa04910;hsa04914;hsa04915;hsa04917;hsa04919;hsa04921;hsa04923;hsa04930;hsa04931;hsa04932;hsa04933;hsa04960;hsa04973;hsa05100;hsa05142;hsa05145;hsa05146;hsa05160;hsa05161;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05220;hsa05221;hsa05222;hsa05223;hsa05230;hsa05231 PIK3R1 chartreuse1 16 -4.12698412698413 CHEK1-mRNA 1.28 0.338 0.622 1.95 0.000382 0.0179 CC.PLS.Apop NS_CANCERPATH_C2535 CHEK1 mRNA 0 CC.PLS.Apop hsa04110;hsa04115;hsa05166;hsa05203 CHEK1 chartreuse2 16 3.78698224852071 AKT1-mRNA 1.14 0.308 0.537 1.74 0.000514 0.023 CC.PLS.Apop, Driver Gene, JAK-STAT, MAPK, PI3K, RAS NS_CANCERPATH_C2535 AKT1 mRNA 0 CC.PLS.Apop;RAS;PI3K;JAK-STAT;MAPK;Driver Gene hsa04010;hsa04012;hsa04014;hsa04015;hsa04022;hsa04024;hsa04062;hsa04066;hsa04068;hsa04071;hsa04072;hsa04150;hsa04151;hsa04152;hsa04210;hsa04211;hsa04261;hsa04370;hsa04380;hsa04510;hsa04530;hsa04550;hsa04611;hsa04620;hsa04630;hsa04660;hsa04662;hsa04664;hsa04666;hsa04668;hsa04722;hsa04725;hsa04728;hsa04910;hsa04914;hsa04915;hsa04917;hsa04919;hsa04920;hsa04922;hsa04923;hsa04931;hsa04932;hsa04933;hsa04973;hsa05142;hsa05145;hsa05152;hsa05160;hsa05161;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05205;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05220;hsa05221;hsa05222;hsa05223;hsa05230;hsa05231 AKT1 chartreuse2 16 3.7012987012987 DE Results - CC.PLS.Apop genes - SubtypeD
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
- Subtype:
- SubtypeA
- SubtypeB
- SubtypeC
- SubtypeD
Volcano Plot: SubtypeA
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Volcano Plot: SubtypeA
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - ChromMod genes - SubtypeA
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all RPS6KA5-mRNA -0.896 0.373 -1.63 -0.165 0.02 0.64 ChromMod, MAPK NS_CANCERPATH_C2535 RPS6KA5 mRNA 0 MAPK;ChromMod hsa04010;hsa04261;hsa04668;hsa04713;hsa04722;hsa05206;hsa05219 RPS6KA5 azure4 1 -2.40214477211796 NASP-mRNA -0.727 0.305 -1.32 -0.13 0.0207 0.653 ChromMod NS_CANCERPATH_C2535 NASP mRNA 0 ChromMod NASP azure4 1 -2.38360655737705 ARID1A-mRNA 0.435 0.192 0.0584 0.812 0.0278 0.779 ChromMod, Driver Gene NS_CANCERPATH_C2535 ARID1A mRNA 0 ChromMod;Driver Gene ARID1A azure4 1 2.265625 SUV39H2-mRNA 0.486 0.268 -0.0394 1.01 0.0756 1 ChromMod NS_CANCERPATH_C2535 SUV39H2 mRNA 0 ChromMod hsa00310 SUV39H2 azure4 1 1.8134328358209 HDAC10-mRNA 0.389 0.234 -0.0694 0.847 0.102 1 ChromMod NS_CANCERPATH_C2535 HDAC10 mRNA 0 ChromMod hsa05034;hsa05203 HDAC10 azure4 1 1.66239316239316 WHSC1L1-mRNA 0.479 0.362 -0.231 1.19 0.192 1 ChromMod NS_CANCERPATH_C2535 WHSC1L1 mRNA 0 ChromMod hsa00310 WHSC1L1 azure4 1 1.3232044198895 HDAC1-mRNA 0.241 0.197 -0.145 0.628 0.226 1 CC.PLS.Apop, ChromMod, Notch, TXmisReg NS_CANCERPATH_C2535 HDAC1 mRNA 0 CC.PLS.Apop;TXmisReg;ChromMod;Notch hsa04110;hsa04330;hsa04919;hsa05016;hsa05031;hsa05034;hsa05169;hsa05200;hsa05202;hsa05203;hsa05206;hsa05220 HDAC1 azure4 1 1.22335025380711 BNIP3-mRNA -0.607 0.496 -1.58 0.364 0.226 1 ChromMod NS_CANCERPATH_C2535 BNIP3 mRNA 0 ChromMod hsa04068;hsa05134 BNIP3 azure4 1 -1.22379032258065 HDAC11-mRNA 0.442 0.362 -0.268 1.15 0.228 1 ChromMod NS_CANCERPATH_C2535 HDAC11 mRNA 0 ChromMod hsa05034;hsa05203 HDAC11 azure4 1 1.22099447513812 HDAC6-mRNA -0.358 0.304 -0.953 0.237 0.244 1 ChromMod NS_CANCERPATH_C2535 HDAC6 mRNA 0 ChromMod hsa05034;hsa05203 HDAC6 azure4 1 -1.17763157894737 HDAC4-mRNA -0.346 0.296 -0.926 0.234 0.247 1 ChromMod NS_CANCERPATH_C2535 HDAC4 mRNA 0 ChromMod hsa05034;hsa05169;hsa05203;hsa05206 HDAC4 azure4 1 -1.16891891891892 NSD1-mRNA 0.284 0.25 -0.206 0.774 0.261 1 ChromMod NS_CANCERPATH_C2535 NSD1 mRNA 0 ChromMod hsa00310 NSD1 azure4 1 1.136 HELLS-mRNA 0.242 0.278 -0.303 0.788 0.388 1 ChromMod NS_CANCERPATH_C2535 HELLS mRNA 0 ChromMod HELLS azure4 1 0.870503597122302 PPARGC1A-mRNA -0.339 0.396 -1.12 0.437 0.395 1 ChromMod NS_CANCERPATH_C2535 PPARGC1A mRNA 0 ChromMod hsa04152;hsa04211;hsa04910;hsa04920;hsa04922;hsa04931;hsa05016 PPARGC1A azure4 1 -0.856060606060606 HMGA1-mRNA 0.271 0.33 -0.376 0.917 0.415 1 ChromMod NS_CANCERPATH_C2535 HMGA1 mRNA 0 ChromMod HMGA1 azure4 1 0.821212121212121 HDAC5-mRNA -0.19 0.257 -0.694 0.314 0.463 1 ChromMod NS_CANCERPATH_C2535 HDAC5 mRNA 0 ChromMod hsa05034;hsa05169;hsa05203 HDAC5 azure4 1 -0.739299610894942 MAP3K12-mRNA 0.121 0.302 -0.472 0.714 0.691 1 ChromMod, MAPK NS_CANCERPATH_C2535 MAP3K12 mRNA 0 MAPK;ChromMod hsa04010 MAP3K12 azure4 1 0.400662251655629 CREBBP-mRNA 0.0973 0.267 -0.426 0.621 0.717 1 CC.PLS.Apop, ChromMod, Driver Gene, JAK-STAT, Notch, TGF-B, Wnt NS_CANCERPATH_C2535 CREBBP mRNA 0 CC.PLS.Apop;JAK-STAT;TGF-B;ChromMod;Wnt;Notch;Driver Gene hsa04024;hsa04066;hsa04068;hsa04110;hsa04310;hsa04330;hsa04350;hsa04520;hsa04630;hsa04720;hsa04916;hsa04919;hsa04922;hsa05016;hsa05152;hsa05161;hsa05164;hsa05166;hsa05168;hsa05169;hsa05200;hsa05203;hsa05206;hsa05211;hsa05215 CREBBP azure4 1 0.364419475655431 HDAC2-mRNA 0.0311 0.301 -0.56 0.622 0.918 1 CC.PLS.Apop, ChromMod, Notch, TXmisReg NS_CANCERPATH_C2535 HDAC2 mRNA 0 CC.PLS.Apop;TXmisReg;ChromMod;Notch hsa04110;hsa04330;hsa04919;hsa05016;hsa05034;hsa05169;hsa05200;hsa05202;hsa05203;hsa05220 HDAC2 azure4 1 0.103322259136213 DE Results - ChromMod genes - SubtypeA
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
Volcano Plot: SubtypeB
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Volcano Plot: SubtypeB
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - ChromMod genes - SubtypeB
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all PPARGC1A-mRNA -1.35 0.373 -2.08 -0.62 0.000662 0.0253 ChromMod NS_CANCERPATH_C2535 PPARGC1A mRNA 0 ChromMod hsa04152;hsa04211;hsa04910;hsa04920;hsa04922;hsa04931;hsa05016 PPARGC1A chartreuse2 16 -3.61930294906166 HDAC4-mRNA -0.951 0.279 -1.5 -0.405 0.00125 0.0437 ChromMod NS_CANCERPATH_C2535 HDAC4 mRNA 0 ChromMod hsa05034;hsa05169;hsa05203;hsa05206 HDAC4 chartreuse2 16 -3.40860215053763 NASP-mRNA -0.887 0.287 -1.45 -0.324 0.00322 0.1 ChromMod NS_CANCERPATH_C2535 NASP mRNA 0 ChromMod NASP chartreuse4 16 -3.09059233449477 HELLS-mRNA 0.773 0.262 0.258 1.29 0.00482 0.133 ChromMod NS_CANCERPATH_C2535 HELLS mRNA 0 ChromMod HELLS chartreuse4 16 2.95038167938931 SUV39H2-mRNA 0.719 0.253 0.224 1.21 0.00627 0.16 ChromMod NS_CANCERPATH_C2535 SUV39H2 mRNA 0 ChromMod hsa00310 SUV39H2 chartreuse4 16 2.84189723320158 RPS6KA5-mRNA -0.875 0.351 -1.56 -0.186 0.016 0.329 ChromMod, MAPK NS_CANCERPATH_C2535 RPS6KA5 mRNA 0 MAPK;ChromMod hsa04010;hsa04261;hsa04668;hsa04713;hsa04722;hsa05206;hsa05219 RPS6KA5 chartreuse4 16 -2.49287749287749 HDAC11-mRNA 0.773 0.342 0.104 1.44 0.0278 0.492 ChromMod NS_CANCERPATH_C2535 HDAC11 mRNA 0 ChromMod hsa05034;hsa05203 HDAC11 azure4 1 2.26023391812865 HMGA1-mRNA 0.687 0.311 0.0775 1.3 0.0316 0.531 ChromMod NS_CANCERPATH_C2535 HMGA1 mRNA 0 ChromMod HMGA1 azure4 1 2.20900321543408 HDAC5-mRNA -0.47 0.242 -0.944 0.00475 0.0578 0.861 ChromMod NS_CANCERPATH_C2535 HDAC5 mRNA 0 ChromMod hsa05034;hsa05169;hsa05203 HDAC5 azure4 1 -1.94214876033058 HDAC1-mRNA 0.353 0.186 -0.0109 0.717 0.0628 0.929 CC.PLS.Apop, ChromMod, Notch, TXmisReg NS_CANCERPATH_C2535 HDAC1 mRNA 0 CC.PLS.Apop;TXmisReg;ChromMod;Notch hsa04110;hsa04330;hsa04919;hsa05016;hsa05031;hsa05034;hsa05169;hsa05200;hsa05202;hsa05203;hsa05206;hsa05220 HDAC1 azure4 1 1.89784946236559 ARID1A-mRNA 0.332 0.181 -0.023 0.687 0.0725 1 ChromMod, Driver Gene NS_CANCERPATH_C2535 ARID1A mRNA 0 ChromMod;Driver Gene ARID1A azure4 1 1.83425414364641 HDAC2-mRNA 0.391 0.284 -0.166 0.947 0.175 1 CC.PLS.Apop, ChromMod, Notch, TXmisReg NS_CANCERPATH_C2535 HDAC2 mRNA 0 CC.PLS.Apop;TXmisReg;ChromMod;Notch hsa04110;hsa04330;hsa04919;hsa05016;hsa05034;hsa05169;hsa05200;hsa05202;hsa05203;hsa05220 HDAC2 azure4 1 1.37676056338028 WHSC1L1-mRNA 0.348 0.341 -0.321 1.02 0.313 1 ChromMod NS_CANCERPATH_C2535 WHSC1L1 mRNA 0 ChromMod hsa00310 WHSC1L1 azure4 1 1.02052785923754 MAP3K12-mRNA -0.259 0.285 -0.817 0.3 0.368 1 ChromMod, MAPK NS_CANCERPATH_C2535 MAP3K12 mRNA 0 MAPK;ChromMod hsa04010 MAP3K12 azure4 1 -0.908771929824562 CREBBP-mRNA -0.218 0.252 -0.711 0.275 0.391 1 CC.PLS.Apop, ChromMod, Driver Gene, JAK-STAT, Notch, TGF-B, Wnt NS_CANCERPATH_C2535 CREBBP mRNA 0 CC.PLS.Apop;JAK-STAT;TGF-B;ChromMod;Wnt;Notch;Driver Gene hsa04024;hsa04066;hsa04068;hsa04110;hsa04310;hsa04330;hsa04350;hsa04520;hsa04630;hsa04720;hsa04916;hsa04919;hsa04922;hsa05016;hsa05152;hsa05161;hsa05164;hsa05166;hsa05168;hsa05169;hsa05200;hsa05203;hsa05206;hsa05211;hsa05215 CREBBP azure4 1 -0.865079365079365 HDAC6-mRNA -0.22 0.286 -0.781 0.341 0.446 1 ChromMod NS_CANCERPATH_C2535 HDAC6 mRNA 0 ChromMod hsa05034;hsa05203 HDAC6 azure4 1 -0.769230769230769 HDAC10-mRNA 0.137 0.22 -0.295 0.568 0.538 1 ChromMod NS_CANCERPATH_C2535 HDAC10 mRNA 0 ChromMod hsa05034;hsa05203 HDAC10 azure4 1 0.622727272727273 BNIP3-mRNA 0.11 0.467 -0.806 1.02 0.815 1 ChromMod NS_CANCERPATH_C2535 BNIP3 mRNA 0 ChromMod hsa04068;hsa05134 BNIP3 azure4 1 0.235546038543897 NSD1-mRNA 0.0411 0.235 -0.42 0.503 0.862 1 ChromMod NS_CANCERPATH_C2535 NSD1 mRNA 0 ChromMod hsa00310 NSD1 azure4 1 0.174893617021277 DE Results - ChromMod genes - SubtypeB
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
Volcano Plot: SubtypeC
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Volcano Plot: SubtypeC
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - ChromMod genes - SubtypeC
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all SUV39H2-mRNA 2.06 0.272 1.52 2.59 6.14e-10 2.22e-07 ChromMod NS_CANCERPATH_C2535 SUV39H2 mRNA 0 ChromMod hsa00310 SUV39H2 chartreuse1 16 7.57352941176471 HELLS-mRNA 1.27 0.282 0.72 1.83 3.7e-05 0.00223 ChromMod NS_CANCERPATH_C2535 HELLS mRNA 0 ChromMod HELLS chartreuse1 16 4.50354609929078 HMGA1-mRNA 1.46 0.334 0.803 2.11 6.08e-05 0.00336 ChromMod NS_CANCERPATH_C2535 HMGA1 mRNA 0 ChromMod HMGA1 chartreuse1 16 4.37125748502994 MAP3K12-mRNA -1.23 0.306 -1.83 -0.631 0.000189 0.00847 ChromMod, MAPK NS_CANCERPATH_C2535 MAP3K12 mRNA 0 MAPK;ChromMod hsa04010 MAP3K12 chartreuse1 16 -4.01960784313725 RPS6KA5-mRNA -1.46 0.378 -2.2 -0.719 0.000313 0.0116 ChromMod, MAPK NS_CANCERPATH_C2535 RPS6KA5 mRNA 0 MAPK;ChromMod hsa04010;hsa04261;hsa04668;hsa04713;hsa04722;hsa05206;hsa05219 RPS6KA5 chartreuse2 16 -3.86243386243386 HDAC2-mRNA 0.834 0.305 0.235 1.43 0.00861 0.188 CC.PLS.Apop, ChromMod, Notch, TXmisReg NS_CANCERPATH_C2535 HDAC2 mRNA 0 CC.PLS.Apop;TXmisReg;ChromMod;Notch hsa04110;hsa04330;hsa04919;hsa05016;hsa05034;hsa05169;hsa05200;hsa05202;hsa05203;hsa05220 HDAC2 chartreuse4 16 2.7344262295082 HDAC4-mRNA -0.736 0.3 -1.32 -0.148 0.0175 0.34 ChromMod NS_CANCERPATH_C2535 HDAC4 mRNA 0 ChromMod hsa05034;hsa05169;hsa05203;hsa05206 HDAC4 chartreuse4 16 -2.45333333333333 HDAC1-mRNA 0.458 0.2 0.0665 0.85 0.0259 0.445 CC.PLS.Apop, ChromMod, Notch, TXmisReg NS_CANCERPATH_C2535 HDAC1 mRNA 0 CC.PLS.Apop;TXmisReg;ChromMod;Notch hsa04110;hsa04330;hsa04919;hsa05016;hsa05031;hsa05034;hsa05169;hsa05200;hsa05202;hsa05203;hsa05206;hsa05220 HDAC1 chartreuse4 16 2.29 PPARGC1A-mRNA -0.555 0.401 -1.34 0.231 0.172 1 ChromMod NS_CANCERPATH_C2535 PPARGC1A mRNA 0 ChromMod hsa04152;hsa04211;hsa04910;hsa04920;hsa04922;hsa04931;hsa05016 PPARGC1A azure4 1 -1.38403990024938 ARID1A-mRNA 0.24 0.195 -0.142 0.622 0.224 1 ChromMod, Driver Gene NS_CANCERPATH_C2535 ARID1A mRNA 0 ChromMod;Driver Gene ARID1A azure4 1 1.23076923076923 HDAC5-mRNA -0.3 0.26 -0.81 0.211 0.255 1 ChromMod NS_CANCERPATH_C2535 HDAC5 mRNA 0 ChromMod hsa05034;hsa05169;hsa05203 HDAC5 azure4 1 -1.15384615384615 CREBBP-mRNA -0.306 0.271 -0.836 0.225 0.264 1 CC.PLS.Apop, ChromMod, Driver Gene, JAK-STAT, Notch, TGF-B, Wnt NS_CANCERPATH_C2535 CREBBP mRNA 0 CC.PLS.Apop;JAK-STAT;TGF-B;ChromMod;Wnt;Notch;Driver Gene hsa04024;hsa04066;hsa04068;hsa04110;hsa04310;hsa04330;hsa04350;hsa04520;hsa04630;hsa04720;hsa04916;hsa04919;hsa04922;hsa05016;hsa05152;hsa05161;hsa05164;hsa05166;hsa05168;hsa05169;hsa05200;hsa05203;hsa05206;hsa05211;hsa05215 CREBBP azure4 1 -1.12915129151291 HDAC6-mRNA -0.307 0.308 -0.91 0.296 0.323 1 ChromMod NS_CANCERPATH_C2535 HDAC6 mRNA 0 ChromMod hsa05034;hsa05203 HDAC6 azure4 1 -0.996753246753247 HDAC10-mRNA 0.19 0.237 -0.274 0.655 0.426 1 ChromMod NS_CANCERPATH_C2535 HDAC10 mRNA 0 ChromMod hsa05034;hsa05203 HDAC10 azure4 1 0.80168776371308 NASP-mRNA -0.217 0.309 -0.822 0.388 0.485 1 ChromMod NS_CANCERPATH_C2535 NASP mRNA 0 ChromMod NASP azure4 1 -0.702265372168285 HDAC11-mRNA 0.201 0.367 -0.519 0.921 0.586 1 ChromMod NS_CANCERPATH_C2535 HDAC11 mRNA 0 ChromMod hsa05034;hsa05203 HDAC11 azure4 1 0.547683923705722 NSD1-mRNA 0.072 0.253 -0.424 0.568 0.777 1 ChromMod NS_CANCERPATH_C2535 NSD1 mRNA 0 ChromMod hsa00310 NSD1 azure4 1 0.284584980237154 BNIP3-mRNA 0.13 0.502 -0.854 1.11 0.797 1 ChromMod NS_CANCERPATH_C2535 BNIP3 mRNA 0 ChromMod hsa04068;hsa05134 BNIP3 azure4 1 0.258964143426295 WHSC1L1-mRNA 0.0871 0.367 -0.633 0.807 0.813 1 ChromMod NS_CANCERPATH_C2535 WHSC1L1 mRNA 0 ChromMod hsa00310 WHSC1L1 azure4 1 0.23732970027248 DE Results - ChromMod genes - SubtypeC
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
Volcano Plot: SubtypeD
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Volcano Plot: SubtypeD
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - ChromMod genes - SubtypeD
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all SUV39H2-mRNA 1.38 0.262 0.862 1.89 2.9e-06 0.000275 ChromMod NS_CANCERPATH_C2535 SUV39H2 mRNA 0 ChromMod hsa00310 SUV39H2 chartreuse1 16 5.26717557251908 HMGA1-mRNA 1.13 0.323 0.499 1.76 0.000953 0.0387 ChromMod NS_CANCERPATH_C2535 HMGA1 mRNA 0 ChromMod HMGA1 chartreuse2 16 3.4984520123839 HDAC2-mRNA 0.956 0.295 0.378 1.53 0.00209 0.0721 CC.PLS.Apop, ChromMod, Notch, TXmisReg NS_CANCERPATH_C2535 HDAC2 mRNA 0 CC.PLS.Apop;TXmisReg;ChromMod;Notch hsa04110;hsa04330;hsa04919;hsa05016;hsa05034;hsa05169;hsa05200;hsa05202;hsa05203;hsa05220 HDAC2 chartreuse3 16 3.24067796610169 HELLS-mRNA 0.753 0.273 0.219 1.29 0.00793 0.197 ChromMod NS_CANCERPATH_C2535 HELLS mRNA 0 ChromMod HELLS chartreuse4 16 2.75824175824176 HDAC4-mRNA -0.768 0.29 -1.34 -0.2 0.0106 0.243 ChromMod NS_CANCERPATH_C2535 HDAC4 mRNA 0 ChromMod hsa05034;hsa05169;hsa05203;hsa05206 HDAC4 chartreuse4 16 -2.64827586206897 HDAC5-mRNA -0.639 0.252 -1.13 -0.146 0.0141 0.304 ChromMod NS_CANCERPATH_C2535 HDAC5 mRNA 0 ChromMod hsa05034;hsa05169;hsa05203 HDAC5 chartreuse4 16 -2.53571428571429 MAP3K12-mRNA -0.7 0.296 -1.28 -0.119 0.0219 0.431 ChromMod, MAPK NS_CANCERPATH_C2535 MAP3K12 mRNA 0 MAPK;ChromMod hsa04010 MAP3K12 chartreuse4 16 -2.36486486486486 ARID1A-mRNA 0.386 0.188 0.0174 0.756 0.0452 0.762 ChromMod, Driver Gene NS_CANCERPATH_C2535 ARID1A mRNA 0 ChromMod;Driver Gene ARID1A azure4 1 2.0531914893617 RPS6KA5-mRNA -0.646 0.365 -1.36 0.0699 0.0828 1 ChromMod, MAPK NS_CANCERPATH_C2535 RPS6KA5 mRNA 0 MAPK;ChromMod hsa04010;hsa04261;hsa04668;hsa04713;hsa04722;hsa05206;hsa05219 RPS6KA5 azure4 1 -1.76986301369863 NASP-mRNA -0.463 0.298 -1.05 0.122 0.127 1 ChromMod NS_CANCERPATH_C2535 NASP mRNA 0 ChromMod NASP azure4 1 -1.55369127516779 HDAC1-mRNA 0.288 0.193 -0.0902 0.667 0.142 1 CC.PLS.Apop, ChromMod, Notch, TXmisReg NS_CANCERPATH_C2535 HDAC1 mRNA 0 CC.PLS.Apop;TXmisReg;ChromMod;Notch hsa04110;hsa04330;hsa04919;hsa05016;hsa05031;hsa05034;hsa05169;hsa05200;hsa05202;hsa05203;hsa05206;hsa05220 HDAC1 azure4 1 1.49222797927461 CREBBP-mRNA -0.278 0.261 -0.791 0.234 0.292 1 CC.PLS.Apop, ChromMod, Driver Gene, JAK-STAT, Notch, TGF-B, Wnt NS_CANCERPATH_C2535 CREBBP mRNA 0 CC.PLS.Apop;JAK-STAT;TGF-B;ChromMod;Wnt;Notch;Driver Gene hsa04024;hsa04066;hsa04068;hsa04110;hsa04310;hsa04330;hsa04350;hsa04520;hsa04630;hsa04720;hsa04916;hsa04919;hsa04922;hsa05016;hsa05152;hsa05161;hsa05164;hsa05166;hsa05168;hsa05169;hsa05200;hsa05203;hsa05206;hsa05211;hsa05215 CREBBP azure4 1 -1.06513409961686 NSD1-mRNA 0.232 0.245 -0.248 0.712 0.348 1 ChromMod NS_CANCERPATH_C2535 NSD1 mRNA 0 ChromMod hsa00310 NSD1 azure4 1 0.946938775510204 PPARGC1A-mRNA -0.355 0.388 -1.11 0.405 0.365 1 ChromMod NS_CANCERPATH_C2535 PPARGC1A mRNA 0 ChromMod hsa04152;hsa04211;hsa04910;hsa04920;hsa04922;hsa04931;hsa05016 PPARGC1A azure4 1 -0.914948453608247 HDAC6-mRNA -0.261 0.297 -0.843 0.322 0.384 1 ChromMod NS_CANCERPATH_C2535 HDAC6 mRNA 0 ChromMod hsa05034;hsa05203 HDAC6 azure4 1 -0.878787878787879 HDAC10-mRNA 0.183 0.229 -0.265 0.632 0.427 1 ChromMod NS_CANCERPATH_C2535 HDAC10 mRNA 0 ChromMod hsa05034;hsa05203 HDAC10 azure4 1 0.799126637554585 WHSC1L1-mRNA -0.277 0.355 -0.973 0.418 0.438 1 ChromMod NS_CANCERPATH_C2535 WHSC1L1 mRNA 0 ChromMod hsa00310 WHSC1L1 azure4 1 -0.780281690140845 BNIP3-mRNA 0.129 0.485 -0.822 1.08 0.791 1 ChromMod NS_CANCERPATH_C2535 BNIP3 mRNA 0 ChromMod hsa04068;hsa05134 BNIP3 azure4 1 0.265979381443299 HDAC11-mRNA 0.022 0.355 -0.674 0.718 0.951 1 ChromMod NS_CANCERPATH_C2535 HDAC11 mRNA 0 ChromMod hsa05034;hsa05203 HDAC11 azure4 1 0.0619718309859155 DE Results - ChromMod genes - SubtypeD
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
- Subtype:
- SubtypeA
- SubtypeB
- SubtypeC
- SubtypeD
Volcano Plot: SubtypeA
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Volcano Plot: SubtypeA
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - DNARepair genes - SubtypeA
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all UBE2T-mRNA 1.83 0.393 1.06 2.6 2.2e-05 0.00461 DNARepair NS_CANCERPATH_C2535 UBE2T mRNA 0 DNARepair hsa03460 UBE2T chartreuse1 16 4.65648854961832 H2AFX-mRNA 1.23 0.337 0.567 1.89 0.000621 0.0563 DNARepair NS_CANCERPATH_C2535 H2AFX mRNA 0 DNARepair hsa05034;hsa05322 H2AFX chartreuse3 16 3.64985163204748 FANCE-mRNA -0.644 0.208 -1.05 -0.237 0.00308 0.186 DNARepair NS_CANCERPATH_C2535 FANCE mRNA 0 DNARepair hsa03460 FANCE chartreuse4 16 -3.09615384615385 RPS27A-mRNA -0.643 0.221 -1.08 -0.21 0.00529 0.251 DNARepair NS_CANCERPATH_C2535 RPS27A mRNA 0 DNARepair RPS27A chartreuse4 16 -2.90950226244344 XPA-mRNA -0.426 0.153 -0.726 -0.125 0.00767 0.325 DNARepair NS_CANCERPATH_C2535 XPA mRNA 0 DNARepair hsa03420 XPA chartreuse4 16 -2.7843137254902 FANCA-mRNA 0.87 0.319 0.245 1.5 0.00869 0.353 DNARepair NS_CANCERPATH_C2535 FANCA mRNA 0 DNARepair hsa03460 FANCA chartreuse4 16 2.72727272727273 RAD51-mRNA 0.813 0.302 0.221 1.41 0.00959 0.374 DNARepair NS_CANCERPATH_C2535 RAD51 mRNA 0 DNARepair hsa03440;hsa03460;hsa05200;hsa05212 RAD51 chartreuse4 16 2.69205298013245 ALKBH2-mRNA -0.593 0.241 -1.07 -0.121 0.0173 0.567 DNARepair NS_CANCERPATH_C2535 ALKBH2 mRNA 0 DNARepair ALKBH2 azure4 1 -2.46058091286307 FANCF-mRNA 0.504 0.207 0.0976 0.91 0.0186 0.605 DNARepair NS_CANCERPATH_C2535 FANCF mRNA 0 DNARepair hsa03460 FANCF azure4 1 2.43478260869565 PRKDC-mRNA 0.621 0.265 0.101 1.14 0.0231 0.719 CC.PLS.Apop, DNARepair NS_CANCERPATH_C2535 PRKDC mRNA 0 CC.PLS.Apop;DNARepair hsa03450;hsa04110 PRKDC azure4 1 2.34339622641509 DDB2-mRNA -0.626 0.269 -1.15 -0.0987 0.0239 0.726 DNARepair NS_CANCERPATH_C2535 DDB2 mRNA 0 DNARepair hsa03420;hsa04115;hsa04120;hsa05161 DDB2 azure4 1 -2.3271375464684 UBB-mRNA 0.426 0.187 0.0594 0.794 0.0269 0.759 DNARepair NS_CANCERPATH_C2535 UBB mRNA 0 DNARepair hsa05012 UBB azure4 1 2.27807486631016 POLD4-mRNA 0.768 0.368 0.0477 1.49 0.0415 1 DNARepair NS_CANCERPATH_C2535 POLD4 mRNA 0 DNARepair hsa00230;hsa00240;hsa01100;hsa03030;hsa03410;hsa03420;hsa03430;hsa03440;hsa05166 POLD4 azure4 1 2.08695652173913 MDC1-mRNA -0.343 0.177 -0.689 0.00299 0.0574 1 DNARepair NS_CANCERPATH_C2535 MDC1 mRNA 0 DNARepair MDC1 azure4 1 -1.93785310734463 C19orf40-mRNA 0.401 0.22 -0.0296 0.832 0.0737 1 DNARepair NS_CANCERPATH_C2535 C19orf40 mRNA 0 DNARepair hsa03460 FAAP24 azure4 1 1.82272727272727 RFC3-mRNA -0.562 0.313 -1.17 0.0513 0.0783 1 DNARepair NS_CANCERPATH_C2535 RFC3 mRNA 0 DNARepair hsa03030;hsa03420;hsa03430 RFC3 azure4 1 -1.79552715654952 ALKBH3-mRNA -0.519 0.294 -1.09 0.0558 0.0826 1 DNARepair NS_CANCERPATH_C2535 ALKBH3 mRNA 0 DNARepair ALKBH3 azure4 1 -1.76530612244898 FANCL-mRNA -0.441 0.256 -0.943 0.0609 0.091 1 DNARepair NS_CANCERPATH_C2535 FANCL mRNA 0 DNARepair hsa03460;hsa04120 FANCL azure4 1 -1.72265625 ERCC2-mRNA 0.36 0.211 -0.0527 0.773 0.0933 1 DNARepair NS_CANCERPATH_C2535 ERCC2 mRNA 0 DNARepair hsa03420 ERCC2 azure4 1 1.70616113744076 POLR2H-mRNA 0.35 0.227 -0.0953 0.796 0.129 1 DNARepair NS_CANCERPATH_C2535 POLR2H mRNA 0 DNARepair hsa00230;hsa00240;hsa01100;hsa04623;hsa05016;hsa05169 POLR2H azure4 1 1.54185022026432 DE Results - DNARepair genes - SubtypeA
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
Volcano Plot: SubtypeB
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Volcano Plot: SubtypeB
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - DNARepair genes - SubtypeB
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all UBE2T-mRNA 2.99 0.37 2.26 3.71 9.89e-11 7.25e-08 DNARepair NS_CANCERPATH_C2535 UBE2T mRNA 0 DNARepair hsa03460 UBE2T chartreuse1 16 8.08108108108108 RAD51-mRNA 1.57 0.285 1.01 2.13 1.16e-06 0.000109 DNARepair NS_CANCERPATH_C2535 RAD51 mRNA 0 DNARepair hsa03440;hsa03460;hsa05200;hsa05212 RAD51 chartreuse1 16 5.50877192982456 H2AFX-mRNA 1.66 0.317 1.04 2.28 2.92e-06 0.000237 DNARepair NS_CANCERPATH_C2535 H2AFX mRNA 0 DNARepair hsa05034;hsa05322 H2AFX chartreuse1 16 5.23659305993691 FANCA-mRNA 1.51 0.301 0.924 2.1 6.16e-06 0.00043 DNARepair NS_CANCERPATH_C2535 FANCA mRNA 0 DNARepair hsa03460 FANCA chartreuse1 16 5.01661129568106 FEN1-mRNA 1.16 0.252 0.666 1.66 2.76e-05 0.00162 DNARepair NS_CANCERPATH_C2535 FEN1 mRNA 0 DNARepair hsa03030;hsa03410;hsa03450 FEN1 chartreuse1 16 4.6031746031746 XPA-mRNA -0.659 0.145 -0.942 -0.375 3.18e-05 0.00178 DNARepair NS_CANCERPATH_C2535 XPA mRNA 0 DNARepair hsa03420 XPA chartreuse1 16 -4.5448275862069 RPS27A-mRNA -0.789 0.208 -1.2 -0.381 0.000393 0.0172 DNARepair NS_CANCERPATH_C2535 RPS27A mRNA 0 DNARepair RPS27A chartreuse2 16 -3.79326923076923 BRCA2-mRNA 0.925 0.252 0.431 1.42 0.000575 0.0231 DNARepair, Driver Gene NS_CANCERPATH_C2535 BRCA2 mRNA 0 DNARepair;Driver Gene hsa03440;hsa03460;hsa05200;hsa05212 BRCA2 chartreuse2 16 3.67063492063492 BRIP1-mRNA 1.14 0.37 0.415 1.87 0.0033 0.102 DNARepair NS_CANCERPATH_C2535 BRIP1 mRNA 0 DNARepair hsa03460 BRIP1 chartreuse4 16 3.08108108108108 POLD4-mRNA 1.06 0.346 0.381 1.74 0.0035 0.106 DNARepair NS_CANCERPATH_C2535 POLD4 mRNA 0 DNARepair hsa00230;hsa00240;hsa01100;hsa03030;hsa03410;hsa03420;hsa03430;hsa03440;hsa05166 POLD4 chartreuse4 16 3.0635838150289 PRKDC-mRNA 0.745 0.25 0.255 1.23 0.00437 0.124 CC.PLS.Apop, DNARepair NS_CANCERPATH_C2535 PRKDC mRNA 0 CC.PLS.Apop;DNARepair hsa03450;hsa04110 PRKDC chartreuse4 16 2.98 BRCA1-mRNA 0.995 0.334 0.341 1.65 0.00437 0.124 DNARepair, Driver Gene, PI3K NS_CANCERPATH_C2535 BRCA1 mRNA 0 PI3K;DNARepair;Driver Gene hsa03460;hsa04120;hsa04151;hsa05206 BRCA1 chartreuse4 16 2.97904191616766 ALKBH3-mRNA -0.815 0.277 -1.36 -0.273 0.00481 0.133 DNARepair NS_CANCERPATH_C2535 ALKBH3 mRNA 0 DNARepair ALKBH3 chartreuse4 16 -2.94223826714801 POLR2H-mRNA 0.612 0.214 0.192 1.03 0.00611 0.157 DNARepair NS_CANCERPATH_C2535 POLR2H mRNA 0 DNARepair hsa00230;hsa00240;hsa01100;hsa04623;hsa05016;hsa05169 POLR2H chartreuse4 16 2.85981308411215 POLE2-mRNA 0.713 0.255 0.214 1.21 0.00716 0.177 DNARepair NS_CANCERPATH_C2535 POLE2 mRNA 0 DNARepair hsa00230;hsa00240;hsa01100;hsa03030;hsa03410;hsa03420;hsa05166 POLE2 chartreuse4 16 2.79607843137255 RFC4-mRNA 0.952 0.351 0.264 1.64 0.00905 0.216 DNARepair NS_CANCERPATH_C2535 RFC4 mRNA 0 DNARepair hsa03030;hsa03420;hsa03430 RFC4 chartreuse4 16 2.71225071225071 FANCF-mRNA 0.523 0.195 0.14 0.906 0.00997 0.232 DNARepair NS_CANCERPATH_C2535 FANCF mRNA 0 DNARepair hsa03460 FANCF chartreuse4 16 2.68205128205128 NTHL1-mRNA 0.635 0.241 0.163 1.11 0.011 0.247 DNARepair NS_CANCERPATH_C2535 NTHL1 mRNA 0 DNARepair hsa03410 NTHL1 chartreuse4 16 2.63485477178423 C19orf40-mRNA 0.54 0.207 0.134 0.946 0.0119 0.256 DNARepair NS_CANCERPATH_C2535 C19orf40 mRNA 0 DNARepair hsa03460 FAAP24 chartreuse4 16 2.60869565217391 XRCC4-mRNA 0.462 0.193 0.0832 0.84 0.0205 0.401 DNARepair NS_CANCERPATH_C2535 XRCC4 mRNA 0 DNARepair hsa03450 XRCC4 chartreuse4 16 2.39378238341969 DE Results - DNARepair genes - SubtypeB
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
Volcano Plot: SubtypeC
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Volcano Plot: SubtypeC
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - DNARepair genes - SubtypeC
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all FANCA-mRNA 2.85 0.323 2.22 3.49 6.54e-12 6.71e-09 DNARepair NS_CANCERPATH_C2535 FANCA mRNA 0 DNARepair hsa03460 FANCA chartreuse1 16 8.82352941176471 UBE2T-mRNA 3.4 0.398 2.62 4.18 1.73e-11 1.38e-08 DNARepair NS_CANCERPATH_C2535 UBE2T mRNA 0 DNARepair hsa03460 UBE2T chartreuse1 16 8.5427135678392 H2AFX-mRNA 2.25 0.341 1.58 2.92 2.22e-08 3.53e-06 DNARepair NS_CANCERPATH_C2535 H2AFX mRNA 0 DNARepair hsa05034;hsa05322 H2AFX chartreuse1 16 6.59824046920821 BRCA2-mRNA 1.7 0.271 1.17 2.24 6.83e-08 9.06e-06 DNARepair, Driver Gene NS_CANCERPATH_C2535 BRCA2 mRNA 0 DNARepair;Driver Gene hsa03440;hsa03460;hsa05200;hsa05212 BRCA2 chartreuse1 16 6.27306273062731 FEN1-mRNA 1.55 0.271 1.02 2.08 5.57e-07 5.68e-05 DNARepair NS_CANCERPATH_C2535 FEN1 mRNA 0 DNARepair hsa03030;hsa03410;hsa03450 FEN1 chartreuse1 16 5.71955719557196 XPA-mRNA -0.883 0.155 -1.19 -0.579 6.11e-07 6.08e-05 DNARepair NS_CANCERPATH_C2535 XPA mRNA 0 DNARepair hsa03420 XPA chartreuse1 16 -5.69677419354839 RAD51-mRNA 1.72 0.306 1.12 2.32 7.44e-07 7.05e-05 DNARepair NS_CANCERPATH_C2535 RAD51 mRNA 0 DNARepair hsa03440;hsa03460;hsa05200;hsa05212 RAD51 chartreuse1 16 5.62091503267974 PRKDC-mRNA 1.43 0.269 0.906 1.96 2.15e-06 0.000168 CC.PLS.Apop, DNARepair NS_CANCERPATH_C2535 PRKDC mRNA 0 CC.PLS.Apop;DNARepair hsa03450;hsa04110 PRKDC chartreuse1 16 5.31598513011152 RAD50-mRNA -1.07 0.232 -1.53 -0.618 2.56e-05 0.00167 DNARepair NS_CANCERPATH_C2535 RAD50 mRNA 0 DNARepair hsa03440;hsa03450 RAD50 chartreuse1 16 -4.61206896551724 BRIP1-mRNA 1.75 0.398 0.974 2.53 5.27e-05 0.00295 DNARepair NS_CANCERPATH_C2535 BRIP1 mRNA 0 DNARepair hsa03460 BRIP1 chartreuse1 16 4.39698492462312 RFC4-mRNA 1.36 0.378 0.624 2.1 0.000683 0.0234 DNARepair NS_CANCERPATH_C2535 RFC4 mRNA 0 DNARepair hsa03030;hsa03420;hsa03430 RFC4 chartreuse2 16 3.5978835978836 C19orf40-mRNA 0.765 0.223 0.328 1.2 0.00118 0.0352 DNARepair NS_CANCERPATH_C2535 C19orf40 mRNA 0 DNARepair hsa03460 FAAP24 chartreuse2 16 3.4304932735426 POLR2D-mRNA 0.503 0.147 0.215 0.791 0.00121 0.0358 DNARepair NS_CANCERPATH_C2535 POLR2D mRNA 0 DNARepair hsa00230;hsa00240;hsa01100;hsa05016;hsa05169 POLR2D chartreuse2 16 3.42176870748299 FANCB-mRNA 0.823 0.245 0.343 1.3 0.00147 0.042 DNARepair NS_CANCERPATH_C2535 FANCB mRNA 0 DNARepair hsa03460 FANCB chartreuse2 16 3.35918367346939 DDB2-mRNA -0.883 0.273 -1.42 -0.349 0.00209 0.0561 DNARepair NS_CANCERPATH_C2535 DDB2 mRNA 0 DNARepair hsa03420;hsa04115;hsa04120;hsa05161 DDB2 chartreuse3 16 -3.23443223443223 POLR2H-mRNA 0.736 0.23 0.285 1.19 0.00237 0.0613 DNARepair NS_CANCERPATH_C2535 POLR2H mRNA 0 DNARepair hsa00230;hsa00240;hsa01100;hsa04623;hsa05016;hsa05169 POLR2H chartreuse3 16 3.2 POLE2-mRNA 0.841 0.274 0.304 1.38 0.00341 0.0809 DNARepair NS_CANCERPATH_C2535 POLE2 mRNA 0 DNARepair hsa00230;hsa00240;hsa01100;hsa03030;hsa03410;hsa03420;hsa05166 POLE2 chartreuse3 16 3.06934306569343 POLD1-mRNA 0.62 0.217 0.195 1.05 0.00615 0.138 DNARepair NS_CANCERPATH_C2535 POLD1 mRNA 0 DNARepair hsa00230;hsa00240;hsa01100;hsa03030;hsa03410;hsa03420;hsa03430;hsa03440;hsa05166 POLD1 chartreuse4 16 2.85714285714286 FANCC-mRNA 0.713 0.258 0.208 1.22 0.00785 0.173 DNARepair NS_CANCERPATH_C2535 FANCC mRNA 0 DNARepair hsa03460 FANCC chartreuse4 16 2.76356589147287 UBB-mRNA 0.508 0.19 0.136 0.88 0.00992 0.211 DNARepair NS_CANCERPATH_C2535 UBB mRNA 0 DNARepair hsa05012 UBB chartreuse4 16 2.67368421052632 DE Results - DNARepair genes - SubtypeC
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
Volcano Plot: SubtypeD
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Volcano Plot: SubtypeD
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - DNARepair genes - SubtypeD
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all UBE2T-mRNA 2.87 0.385 2.11 3.62 9.29e-10 6.58e-07 DNARepair NS_CANCERPATH_C2535 UBE2T mRNA 0 DNARepair hsa03460 UBE2T chartreuse1 16 7.45454545454546 H2AFX-mRNA 2.15 0.33 1.5 2.79 2.95e-08 7.32e-06 DNARepair NS_CANCERPATH_C2535 H2AFX mRNA 0 DNARepair hsa05034;hsa05322 H2AFX chartreuse1 16 6.51515151515151 BRCA2-mRNA 1.58 0.262 1.07 2.1 1.69e-07 2.58e-05 DNARepair, Driver Gene NS_CANCERPATH_C2535 BRCA2 mRNA 0 DNARepair;Driver Gene hsa03440;hsa03460;hsa05200;hsa05212 BRCA2 chartreuse1 16 6.03053435114504 RAD51-mRNA 1.76 0.296 1.18 2.34 2.29e-07 3.21e-05 DNARepair NS_CANCERPATH_C2535 RAD51 mRNA 0 DNARepair hsa03440;hsa03460;hsa05200;hsa05212 RAD51 chartreuse1 16 5.94594594594595 XPA-mRNA -0.793 0.15 -1.09 -0.498 2.6e-06 0.000253 DNARepair NS_CANCERPATH_C2535 XPA mRNA 0 DNARepair hsa03420 XPA chartreuse1 16 -5.28666666666667 FANCA-mRNA 1.64 0.313 1.02 2.25 2.99e-06 0.000276 DNARepair NS_CANCERPATH_C2535 FANCA mRNA 0 DNARepair hsa03460 FANCA chartreuse1 16 5.23961661341853 FEN1-mRNA 1.31 0.262 0.796 1.82 7.02e-06 0.000582 DNARepair NS_CANCERPATH_C2535 FEN1 mRNA 0 DNARepair hsa03030;hsa03410;hsa03450 FEN1 chartreuse1 16 5 MAD2L2-mRNA 0.857 0.258 0.351 1.36 0.00164 0.0589 CC.PLS.Apop, DNARepair NS_CANCERPATH_C2535 MAD2L2 mRNA 0 CC.PLS.Apop;DNARepair hsa04110;hsa04114;hsa04914;hsa05100;hsa05131 MAD2L2 chartreuse3 16 3.32170542635659 UBB-mRNA 0.59 0.183 0.231 0.95 0.00222 0.0755 DNARepair NS_CANCERPATH_C2535 UBB mRNA 0 DNARepair hsa05012 UBB chartreuse3 16 3.22404371584699 PRKDC-mRNA 0.829 0.26 0.32 1.34 0.00239 0.0793 CC.PLS.Apop, DNARepair NS_CANCERPATH_C2535 PRKDC mRNA 0 CC.PLS.Apop;DNARepair hsa03450;hsa04110 PRKDC chartreuse3 16 3.18846153846154 POLR2D-mRNA 0.446 0.142 0.167 0.724 0.0028 0.0899 DNARepair NS_CANCERPATH_C2535 POLR2D mRNA 0 DNARepair hsa00230;hsa00240;hsa01100;hsa05016;hsa05169 POLR2D chartreuse3 16 3.14084507042254 C19orf40-mRNA 0.639 0.215 0.217 1.06 0.00455 0.133 DNARepair NS_CANCERPATH_C2535 C19orf40 mRNA 0 DNARepair hsa03460 FAAP24 chartreuse4 16 2.97209302325581 BRIP1-mRNA 1.13 0.385 0.375 1.88 0.00495 0.14 DNARepair NS_CANCERPATH_C2535 BRIP1 mRNA 0 DNARepair hsa03460 BRIP1 chartreuse4 16 2.93506493506493 DDB2-mRNA -0.761 0.264 -1.28 -0.244 0.00567 0.154 DNARepair NS_CANCERPATH_C2535 DDB2 mRNA 0 DNARepair hsa03420;hsa04115;hsa04120;hsa05161 DDB2 chartreuse4 16 -2.88257575757576 FANCF-mRNA 0.543 0.203 0.145 0.941 0.00997 0.232 DNARepair NS_CANCERPATH_C2535 FANCF mRNA 0 DNARepair hsa03460 FANCF chartreuse4 16 2.67487684729064 POLE2-mRNA 0.705 0.265 0.186 1.22 0.0103 0.237 DNARepair NS_CANCERPATH_C2535 POLE2 mRNA 0 DNARepair hsa00230;hsa00240;hsa01100;hsa03030;hsa03410;hsa03420;hsa05166 POLE2 chartreuse4 16 2.66037735849057 POLR2H-mRNA 0.589 0.223 0.153 1.03 0.0107 0.244 DNARepair NS_CANCERPATH_C2535 POLR2H mRNA 0 DNARepair hsa00230;hsa00240;hsa01100;hsa04623;hsa05016;hsa05169 POLR2H chartreuse4 16 2.64125560538117 XRCC4-mRNA 0.467 0.201 0.0736 0.861 0.0239 0.462 DNARepair NS_CANCERPATH_C2535 XRCC4 mRNA 0 DNARepair hsa03450 XRCC4 chartreuse4 16 2.32338308457711 RFC4-mRNA 0.764 0.365 0.0484 1.48 0.0413 0.723 DNARepair NS_CANCERPATH_C2535 RFC4 mRNA 0 DNARepair hsa03030;hsa03420;hsa03430 RFC4 azure4 1 2.09315068493151 RAD50-mRNA -0.467 0.224 -0.906 -0.0268 0.0425 0.733 DNARepair NS_CANCERPATH_C2535 RAD50 mRNA 0 DNARepair hsa03440;hsa03450 RAD50 azure4 1 -2.08482142857143 DE Results - DNARepair genes - SubtypeD
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
- Subtype:
- SubtypeA
- SubtypeB
- SubtypeC
- SubtypeD
Volcano Plot: SubtypeA
More Plot Information
Volcano Plot: SubtypeA
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - Driver Gene genes - SubtypeA
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all KIT-mRNA -3.12 0.436 -3.98 -2.27 2.68e-09 5.33e-06 Driver Gene, PI3K, RAS NS_CANCERPATH_C2535 KIT mRNA 0 RAS;PI3K;Driver Gene hsa04014;hsa04015;hsa04060;hsa04072;hsa04144;hsa04151;hsa04640;hsa04916;hsa05200;hsa05221;hsa05230 KIT chartreuse1 16 -7.15596330275229 KLF4-mRNA -1.88 0.383 -2.63 -1.13 9.02e-06 0.00256 Driver Gene NS_CANCERPATH_C2535 KLF4 mRNA 0 Driver Gene hsa04550 KLF4 chartreuse1 16 -4.90861618798956 PDGFRA-mRNA -1.78 0.369 -2.5 -1.05 1.31e-05 0.00345 Driver Gene, MAPK, PI3K, RAS NS_CANCERPATH_C2535 PDGFRA mRNA 0 RAS;PI3K;MAPK;Driver Gene hsa04010;hsa04014;hsa04015;hsa04020;hsa04060;hsa04072;hsa04144;hsa04151;hsa04510;hsa04540;hsa04810;hsa05166;hsa05200;hsa05206;hsa05214;hsa05215;hsa05218;hsa05230;hsa05231 PDGFRA chartreuse1 16 -4.82384823848238 PIK3R1-mRNA -1.47 0.322 -2.1 -0.838 3.11e-05 0.00562 CC.PLS.Apop, Driver Gene, JAK-STAT, PI3K, RAS NS_CANCERPATH_C2535 PIK3R1 mRNA 0 CC.PLS.Apop;RAS;PI3K;JAK-STAT;Driver Gene hsa04012;hsa04014;hsa04015;hsa04022;hsa04024;hsa04062;hsa04066;hsa04068;hsa04070;hsa04071;hsa04072;hsa04150;hsa04151;hsa04152;hsa04210;hsa04211;hsa04261;hsa04370;hsa04380;hsa04510;hsa04550;hsa04611;hsa04620;hsa04630;hsa04650;hsa04660;hsa04662;hsa04664;hsa04666;hsa04668;hsa04670;hsa04722;hsa04725;hsa04750;hsa04810;hsa04910;hsa04914;hsa04915;hsa04917;hsa04919;hsa04921;hsa04923;hsa04930;hsa04931;hsa04932;hsa04933;hsa04960;hsa04973;hsa05100;hsa05142;hsa05145;hsa05146;hsa05160;hsa05161;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05220;hsa05221;hsa05222;hsa05223;hsa05230;hsa05231 PIK3R1 chartreuse1 16 -4.56521739130435 GATA3-mRNA 2.09 0.479 1.15 3.03 6.17e-05 0.0092 Driver Gene NS_CANCERPATH_C2535 GATA3 mRNA 0 Driver Gene hsa05321 GATA3 chartreuse1 16 4.36325678496868 EGFR-mRNA -2.34 0.537 -3.39 -1.29 6.27e-05 0.0092 Driver Gene, MAPK, PI3K, RAS NS_CANCERPATH_C2535 EGFR mRNA 0 RAS;PI3K;MAPK;Driver Gene hsa04010;hsa04012;hsa04014;hsa04015;hsa04020;hsa04060;hsa04066;hsa04068;hsa04072;hsa04144;hsa04151;hsa04320;hsa04510;hsa04520;hsa04540;hsa04810;hsa04912;hsa04915;hsa04921;hsa05120;hsa05160;hsa05200;hsa05205;hsa05206;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05219;hsa05223;hsa05230;hsa05231 EGFR chartreuse1 16 -4.35754189944134 KRAS-mRNA 1.2 0.292 0.625 1.77 0.000144 0.0168 Driver Gene, MAPK, PI3K, RAS NS_CANCERPATH_C2535 KRAS mRNA 0 RAS;PI3K;MAPK;Driver Gene hsa04010;hsa04012;hsa04014;hsa04015;hsa04062;hsa04068;hsa04071;hsa04072;hsa04151;hsa04211;hsa04320;hsa04360;hsa04370;hsa04530;hsa04540;hsa04550;hsa04650;hsa04660;hsa04662;hsa04664;hsa04720;hsa04722;hsa04725;hsa04726;hsa04730;hsa04810;hsa04910;hsa04912;hsa04914;hsa04915;hsa04916;hsa04917;hsa04919;hsa04921;hsa04933;hsa04960;hsa05034;hsa05160;hsa05161;hsa05166;hsa05200;hsa05203;hsa05205;hsa05206;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05216;hsa05218;hsa05219;hsa05220;hsa05221;hsa05223;hsa05230;hsa05231 KRAS chartreuse2 16 4.10958904109589 ASXL1-mRNA -0.968 0.246 -1.45 -0.487 0.000242 0.0275 Driver Gene NS_CANCERPATH_C2535 ASXL1 mRNA 0 Driver Gene ASXL1 chartreuse2 16 -3.9349593495935 EZH2-mRNA 1.17 0.31 0.558 1.77 0.000431 0.0451 Driver Gene NS_CANCERPATH_C2535 EZH2 mRNA 0 Driver Gene hsa05206 EZH2 chartreuse2 16 3.7741935483871 ABL1-mRNA -0.846 0.249 -1.33 -0.359 0.00129 0.103 CC.PLS.Apop, Driver Gene, RAS NS_CANCERPATH_C2535 ABL1 mRNA 0 CC.PLS.Apop;RAS;Driver Gene hsa04012;hsa04014;hsa04110;hsa04360;hsa04722;hsa05130;hsa05131;hsa05200;hsa05206;hsa05220;hsa05416 ABL1 chartreuse4 16 -3.39759036144578 MYD88-mRNA 0.729 0.224 0.29 1.17 0.00198 0.138 CC.PLS.Apop, Driver Gene NS_CANCERPATH_C2535 MYD88 mRNA 0 CC.PLS.Apop;Driver Gene hsa04064;hsa04210;hsa04620;hsa05132;hsa05133;hsa05134;hsa05140;hsa05142;hsa05143;hsa05144;hsa05145;hsa05152;hsa05161;hsa05162;hsa05164;hsa05168 MYD88 chartreuse4 16 3.25446428571429 PTCH1-mRNA -1.12 0.365 -1.84 -0.408 0.00334 0.187 Driver Gene, HH NS_CANCERPATH_C2535 PTCH1 mRNA 0 HH;Driver Gene hsa04024;hsa04340;hsa05200;hsa05205;hsa05217 PTCH1 chartreuse4 16 -3.06849315068493 PTPN11-mRNA -0.572 0.189 -0.942 -0.203 0.00375 0.202 Driver Gene, JAK-STAT, RAS NS_CANCERPATH_C2535 PTPN11 mRNA 0 RAS;JAK-STAT;Driver Gene hsa04014;hsa04072;hsa04630;hsa04650;hsa04670;hsa04722;hsa04920;hsa04931;hsa05120;hsa05168;hsa05205;hsa05211;hsa05220 PTPN11 chartreuse4 16 -3.02645502645503 CEBPA-mRNA -1.29 0.448 -2.17 -0.409 0.00586 0.271 Driver Gene, TXmisReg NS_CANCERPATH_C2535 CEBPA mRNA 0 TXmisReg;Driver Gene hsa04932;hsa05200;hsa05202;hsa05221 CEBPA chartreuse4 16 -2.87946428571429 IDH2-mRNA 1.02 0.363 0.305 1.73 0.00716 0.313 Driver Gene NS_CANCERPATH_C2535 IDH2 mRNA 0 Driver Gene hsa01100 IDH2 chartreuse4 16 2.8099173553719 RET-mRNA 1.97 0.739 0.527 3.42 0.01 0.387 Driver Gene NS_CANCERPATH_C2535 RET mRNA 0 Driver Gene hsa04144;hsa05200;hsa05216;hsa05230 RET chartreuse4 16 2.66576454668471 RUNX1-mRNA 0.936 0.351 0.248 1.62 0.0102 0.391 Driver Gene, TXmisReg NS_CANCERPATH_C2535 RUNX1 mRNA 0 TXmisReg;Driver Gene hsa05200;hsa05202;hsa05220;hsa05221 RUNX1 chartreuse4 16 2.66666666666667 BCOR-mRNA 0.47 0.177 0.122 0.817 0.0106 0.402 Driver Gene NS_CANCERPATH_C2535 BCOR mRNA 0 Driver Gene BCOR chartreuse4 16 2.65536723163842 AKT1-mRNA 0.777 0.314 0.161 1.39 0.0167 0.559 CC.PLS.Apop, Driver Gene, JAK-STAT, MAPK, PI3K, RAS NS_CANCERPATH_C2535 AKT1 mRNA 0 CC.PLS.Apop;RAS;PI3K;JAK-STAT;MAPK;Driver Gene hsa04010;hsa04012;hsa04014;hsa04015;hsa04022;hsa04024;hsa04062;hsa04066;hsa04068;hsa04071;hsa04072;hsa04150;hsa04151;hsa04152;hsa04210;hsa04211;hsa04261;hsa04370;hsa04380;hsa04510;hsa04530;hsa04550;hsa04611;hsa04620;hsa04630;hsa04660;hsa04662;hsa04664;hsa04666;hsa04668;hsa04722;hsa04725;hsa04728;hsa04910;hsa04914;hsa04915;hsa04917;hsa04919;hsa04920;hsa04922;hsa04923;hsa04931;hsa04932;hsa04933;hsa04973;hsa05142;hsa05145;hsa05152;hsa05160;hsa05161;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05205;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05220;hsa05221;hsa05222;hsa05223;hsa05230;hsa05231 AKT1 azure4 1 2.47452229299363 MET-mRNA -1.18 0.498 -2.16 -0.205 0.0214 0.671 Driver Gene, PI3K, RAS, TXmisReg NS_CANCERPATH_C2535 MET mRNA 0 RAS;PI3K;TXmisReg;Driver Gene hsa04014;hsa04015;hsa04060;hsa04144;hsa04151;hsa04360;hsa04510;hsa04520;hsa05100;hsa05120;hsa05144;hsa05200;hsa05202;hsa05205;hsa05206;hsa05211;hsa05218;hsa05230 MET azure4 1 -2.36947791164659 DE Results - Driver Gene genes - SubtypeA
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
Volcano Plot: SubtypeB
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Volcano Plot: SubtypeB
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - Driver Gene genes - SubtypeB
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all KIT-mRNA -3.78 0.41 -4.58 -2.97 1.68e-12 2.22e-09 Driver Gene, PI3K, RAS NS_CANCERPATH_C2535 KIT mRNA 0 RAS;PI3K;Driver Gene hsa04014;hsa04015;hsa04060;hsa04072;hsa04144;hsa04151;hsa04640;hsa04916;hsa05200;hsa05221;hsa05230 KIT chartreuse1 16 -9.21951219512195 EGFR-mRNA -3.46 0.506 -4.46 -2.47 8.82e-09 1.75e-06 Driver Gene, MAPK, PI3K, RAS NS_CANCERPATH_C2535 EGFR mRNA 0 RAS;PI3K;MAPK;Driver Gene hsa04010;hsa04012;hsa04014;hsa04015;hsa04020;hsa04060;hsa04066;hsa04068;hsa04072;hsa04144;hsa04151;hsa04320;hsa04510;hsa04520;hsa04540;hsa04810;hsa04912;hsa04915;hsa04921;hsa05120;hsa05160;hsa05200;hsa05205;hsa05206;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05219;hsa05223;hsa05230;hsa05231 EGFR chartreuse1 16 -6.83794466403162 PIK3R1-mRNA -1.92 0.303 -2.52 -1.33 5.54e-08 8.16e-06 CC.PLS.Apop, Driver Gene, JAK-STAT, PI3K, RAS NS_CANCERPATH_C2535 PIK3R1 mRNA 0 CC.PLS.Apop;RAS;PI3K;JAK-STAT;Driver Gene hsa04012;hsa04014;hsa04015;hsa04022;hsa04024;hsa04062;hsa04066;hsa04068;hsa04070;hsa04071;hsa04072;hsa04150;hsa04151;hsa04152;hsa04210;hsa04211;hsa04261;hsa04370;hsa04380;hsa04510;hsa04550;hsa04611;hsa04620;hsa04630;hsa04650;hsa04660;hsa04662;hsa04664;hsa04666;hsa04668;hsa04670;hsa04722;hsa04725;hsa04750;hsa04810;hsa04910;hsa04914;hsa04915;hsa04917;hsa04919;hsa04921;hsa04923;hsa04930;hsa04931;hsa04932;hsa04933;hsa04960;hsa04973;hsa05100;hsa05142;hsa05145;hsa05146;hsa05160;hsa05161;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05220;hsa05221;hsa05222;hsa05223;hsa05230;hsa05231 PIK3R1 chartreuse1 16 -6.33663366336634 EZH2-mRNA 1.82 0.292 1.25 2.39 8.24e-08 1.06e-05 Driver Gene NS_CANCERPATH_C2535 EZH2 mRNA 0 Driver Gene hsa05206 EZH2 chartreuse1 16 6.23287671232877 KLF4-mRNA -2.23 0.36 -2.94 -1.53 9.26e-08 1.15e-05 Driver Gene NS_CANCERPATH_C2535 KLF4 mRNA 0 Driver Gene hsa04550 KLF4 chartreuse1 16 -6.19444444444444 PDGFRA-mRNA -2.11 0.348 -2.79 -1.43 1.53e-07 1.69e-05 Driver Gene, MAPK, PI3K, RAS NS_CANCERPATH_C2535 PDGFRA mRNA 0 RAS;PI3K;MAPK;Driver Gene hsa04010;hsa04014;hsa04015;hsa04020;hsa04060;hsa04072;hsa04144;hsa04151;hsa04510;hsa04540;hsa04810;hsa05166;hsa05200;hsa05206;hsa05214;hsa05215;hsa05218;hsa05230;hsa05231 PDGFRA chartreuse1 16 -6.0632183908046 PTCH1-mRNA -1.91 0.344 -2.59 -1.24 9.52e-07 9.24e-05 Driver Gene, HH NS_CANCERPATH_C2535 PTCH1 mRNA 0 HH;Driver Gene hsa04024;hsa04340;hsa05200;hsa05205;hsa05217 PTCH1 chartreuse1 16 -5.55232558139535 MET-mRNA -2.42 0.469 -3.34 -1.5 3.85e-06 0.000295 Driver Gene, PI3K, RAS, TXmisReg NS_CANCERPATH_C2535 MET mRNA 0 RAS;PI3K;TXmisReg;Driver Gene hsa04014;hsa04015;hsa04060;hsa04144;hsa04151;hsa04360;hsa04510;hsa04520;hsa05100;hsa05120;hsa05144;hsa05200;hsa05202;hsa05205;hsa05206;hsa05211;hsa05218;hsa05230 MET chartreuse1 16 -5.15991471215352 HIST1H3B-mRNA 2.52 0.507 1.52 3.51 7.75e-06 0.000522 Driver Gene, TXmisReg NS_CANCERPATH_C2535 HIST1H3B mRNA 0 TXmisReg;Driver Gene hsa05034;hsa05202;hsa05322 HIST1H3B chartreuse1 16 4.97041420118343 KRAS-mRNA 1.3 0.275 0.757 1.83 1.84e-05 0.00111 Driver Gene, MAPK, PI3K, RAS NS_CANCERPATH_C2535 KRAS mRNA 0 RAS;PI3K;MAPK;Driver Gene hsa04010;hsa04012;hsa04014;hsa04015;hsa04062;hsa04068;hsa04071;hsa04072;hsa04151;hsa04211;hsa04320;hsa04360;hsa04370;hsa04530;hsa04540;hsa04550;hsa04650;hsa04660;hsa04662;hsa04664;hsa04720;hsa04722;hsa04725;hsa04726;hsa04730;hsa04810;hsa04910;hsa04912;hsa04914;hsa04915;hsa04916;hsa04917;hsa04919;hsa04921;hsa04933;hsa04960;hsa05034;hsa05160;hsa05161;hsa05166;hsa05200;hsa05203;hsa05205;hsa05206;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05216;hsa05218;hsa05219;hsa05220;hsa05221;hsa05223;hsa05230;hsa05231 KRAS chartreuse1 16 4.72727272727273 MYD88-mRNA 0.879 0.211 0.465 1.29 0.000117 0.00559 CC.PLS.Apop, Driver Gene NS_CANCERPATH_C2535 MYD88 mRNA 0 CC.PLS.Apop;Driver Gene hsa04064;hsa04210;hsa04620;hsa05132;hsa05133;hsa05134;hsa05140;hsa05142;hsa05143;hsa05144;hsa05145;hsa05152;hsa05161;hsa05162;hsa05164;hsa05168 MYD88 chartreuse1 16 4.16587677725119 GATA3-mRNA 1.71 0.451 0.823 2.59 0.000403 0.0174 Driver Gene NS_CANCERPATH_C2535 GATA3 mRNA 0 Driver Gene hsa05321 GATA3 chartreuse2 16 3.79157427937916 BRCA2-mRNA 0.925 0.252 0.431 1.42 0.000575 0.0231 DNARepair, Driver Gene NS_CANCERPATH_C2535 BRCA2 mRNA 0 DNARepair;Driver Gene hsa03440;hsa03460;hsa05200;hsa05212 BRCA2 chartreuse2 16 3.67063492063492 ABL1-mRNA -0.851 0.234 -1.31 -0.392 0.000641 0.0247 CC.PLS.Apop, Driver Gene, RAS NS_CANCERPATH_C2535 ABL1 mRNA 0 CC.PLS.Apop;RAS;Driver Gene hsa04012;hsa04014;hsa04110;hsa04360;hsa04722;hsa05130;hsa05131;hsa05200;hsa05206;hsa05220;hsa05416 ABL1 chartreuse2 16 -3.63675213675214 ASXL1-mRNA -0.775 0.231 -1.23 -0.321 0.00152 0.0515 Driver Gene NS_CANCERPATH_C2535 ASXL1 mRNA 0 Driver Gene ASXL1 chartreuse3 16 -3.35497835497835 BRCA1-mRNA 0.995 0.334 0.341 1.65 0.00437 0.124 DNARepair, Driver Gene, PI3K NS_CANCERPATH_C2535 BRCA1 mRNA 0 PI3K;DNARepair;Driver Gene hsa03460;hsa04120;hsa04151;hsa05206 BRCA1 chartreuse4 16 2.97904191616766 SETBP1-mRNA -1.41 0.477 -2.34 -0.475 0.00468 0.132 Driver Gene NS_CANCERPATH_C2535 SETBP1 mRNA 0 Driver Gene SETBP1 chartreuse4 16 -2.9559748427673 IDH2-mRNA 0.967 0.342 0.297 1.64 0.00665 0.166 Driver Gene NS_CANCERPATH_C2535 IDH2 mRNA 0 Driver Gene hsa01100 IDH2 chartreuse4 16 2.82748538011696 TRAF7-mRNA 0.656 0.24 0.187 1.13 0.00838 0.203 Driver Gene NS_CANCERPATH_C2535 TRAF7 mRNA 0 Driver Gene TRAF7 chartreuse4 16 2.73333333333333 SMAD4-mRNA -0.524 0.195 -0.906 -0.143 0.00946 0.224 CC.PLS.Apop, Driver Gene, TGF-B, Wnt NS_CANCERPATH_C2535 SMAD4 mRNA 0 CC.PLS.Apop;TGF-B;Wnt;Driver Gene hsa04068;hsa04110;hsa04310;hsa04350;hsa04390;hsa04520;hsa04550;hsa04933;hsa05161;hsa05166;hsa05200;hsa05210;hsa05212;hsa05220 SMAD4 chartreuse4 16 -2.68717948717949 DE Results - Driver Gene genes - SubtypeB
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
Volcano Plot: SubtypeC
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Volcano Plot: SubtypeC
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - Driver Gene genes - SubtypeC
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all EZH2-mRNA 2.92 0.314 2.31 3.54 1.15e-12 4.59e-09 Driver Gene NS_CANCERPATH_C2535 EZH2 mRNA 0 Driver Gene hsa05206 EZH2 chartreuse1 16 9.29936305732484 KIT-mRNA -2.95 0.441 -3.81 -2.08 1.6e-08 2.76e-06 Driver Gene, PI3K, RAS NS_CANCERPATH_C2535 KIT mRNA 0 RAS;PI3K;Driver Gene hsa04014;hsa04015;hsa04060;hsa04072;hsa04144;hsa04151;hsa04640;hsa04916;hsa05200;hsa05221;hsa05230 KIT chartreuse1 16 -6.68934240362812 BRCA2-mRNA 1.7 0.271 1.17 2.24 6.83e-08 9.06e-06 DNARepair, Driver Gene NS_CANCERPATH_C2535 BRCA2 mRNA 0 DNARepair;Driver Gene hsa03440;hsa03460;hsa05200;hsa05212 BRCA2 chartreuse1 16 6.27306273062731 PIK3R1-mRNA -2.01 0.326 -2.65 -1.37 1.06e-07 1.31e-05 CC.PLS.Apop, Driver Gene, JAK-STAT, PI3K, RAS NS_CANCERPATH_C2535 PIK3R1 mRNA 0 CC.PLS.Apop;RAS;PI3K;JAK-STAT;Driver Gene hsa04012;hsa04014;hsa04015;hsa04022;hsa04024;hsa04062;hsa04066;hsa04068;hsa04070;hsa04071;hsa04072;hsa04150;hsa04151;hsa04152;hsa04210;hsa04211;hsa04261;hsa04370;hsa04380;hsa04510;hsa04550;hsa04611;hsa04620;hsa04630;hsa04650;hsa04660;hsa04662;hsa04664;hsa04666;hsa04668;hsa04670;hsa04722;hsa04725;hsa04750;hsa04810;hsa04910;hsa04914;hsa04915;hsa04917;hsa04919;hsa04921;hsa04923;hsa04930;hsa04931;hsa04932;hsa04933;hsa04960;hsa04973;hsa05100;hsa05142;hsa05145;hsa05146;hsa05160;hsa05161;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05220;hsa05221;hsa05222;hsa05223;hsa05230;hsa05231 PIK3R1 chartreuse1 16 -6.16564417177914 KLF4-mRNA -2.32 0.388 -3.08 -1.56 2.11e-07 2.33e-05 Driver Gene NS_CANCERPATH_C2535 KLF4 mRNA 0 Driver Gene hsa04550 KLF4 chartreuse1 16 -5.97938144329897 MYD88-mRNA 1.28 0.227 0.84 1.73 6.52e-07 6.32e-05 CC.PLS.Apop, Driver Gene NS_CANCERPATH_C2535 MYD88 mRNA 0 CC.PLS.Apop;Driver Gene hsa04064;hsa04210;hsa04620;hsa05132;hsa05133;hsa05134;hsa05140;hsa05142;hsa05143;hsa05144;hsa05145;hsa05152;hsa05161;hsa05162;hsa05164;hsa05168 MYD88 chartreuse1 16 5.63876651982379 PDGFRA-mRNA -2.09 0.374 -2.82 -1.35 8.8e-07 7.95e-05 Driver Gene, MAPK, PI3K, RAS NS_CANCERPATH_C2535 PDGFRA mRNA 0 RAS;PI3K;MAPK;Driver Gene hsa04010;hsa04014;hsa04015;hsa04020;hsa04060;hsa04072;hsa04144;hsa04151;hsa04510;hsa04540;hsa04810;hsa05166;hsa05200;hsa05206;hsa05214;hsa05215;hsa05218;hsa05230;hsa05231 PDGFRA chartreuse1 16 -5.58823529411765 HIST1H3B-mRNA 2.95 0.545 1.88 4.02 1.59e-06 0.000135 Driver Gene, TXmisReg NS_CANCERPATH_C2535 HIST1H3B mRNA 0 TXmisReg;Driver Gene hsa05034;hsa05202;hsa05322 HIST1H3B chartreuse1 16 5.41284403669725 BCL2-mRNA -2.12 0.467 -3.04 -1.2 3.41e-05 0.00208 CC.PLS.Apop, Driver Gene, PI3K NS_CANCERPATH_C2535 BCL2 mRNA 0 CC.PLS.Apop;PI3K;Driver Gene hsa04064;hsa04066;hsa04071;hsa04141;hsa04151;hsa04210;hsa04261;hsa04510;hsa04630;hsa04722;hsa04725;hsa04933;hsa05014;hsa05145;hsa05152;hsa05161;hsa05169;hsa05200;hsa05206;hsa05210;hsa05215;hsa05222 BCL2 chartreuse1 16 -4.53961456102784 MSH2-mRNA 0.832 0.188 0.464 1.2 4.94e-05 0.00289 Driver Gene NS_CANCERPATH_C2535 MSH2 mRNA 0 Driver Gene hsa03430;hsa05200;hsa05210 MSH2 chartreuse1 16 4.42553191489362 AR-mRNA -2.55 0.597 -3.72 -1.38 8.23e-05 0.00442 Driver Gene NS_CANCERPATH_C2535 AR mRNA 0 Driver Gene hsa04114;hsa05200;hsa05215 AR chartreuse1 16 -4.2713567839196 KRAS-mRNA 1.25 0.296 0.675 1.83 9.06e-05 0.00468 Driver Gene, MAPK, PI3K, RAS NS_CANCERPATH_C2535 KRAS mRNA 0 RAS;PI3K;MAPK;Driver Gene hsa04010;hsa04012;hsa04014;hsa04015;hsa04062;hsa04068;hsa04071;hsa04072;hsa04151;hsa04211;hsa04320;hsa04360;hsa04370;hsa04530;hsa04540;hsa04550;hsa04650;hsa04660;hsa04662;hsa04664;hsa04720;hsa04722;hsa04725;hsa04726;hsa04730;hsa04810;hsa04910;hsa04912;hsa04914;hsa04915;hsa04916;hsa04917;hsa04919;hsa04921;hsa04933;hsa04960;hsa05034;hsa05160;hsa05161;hsa05166;hsa05200;hsa05203;hsa05205;hsa05206;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05216;hsa05218;hsa05219;hsa05220;hsa05221;hsa05223;hsa05230;hsa05231 KRAS chartreuse1 16 4.22297297297297 SETBP1-mRNA -2.12 0.513 -3.13 -1.12 0.000127 0.00615 Driver Gene NS_CANCERPATH_C2535 SETBP1 mRNA 0 Driver Gene SETBP1 chartreuse1 16 -4.13255360623782 PHF6-mRNA 1.16 0.285 0.606 1.72 0.000153 0.00723 Driver Gene NS_CANCERPATH_C2535 PHF6 mRNA 0 Driver Gene PHF6 chartreuse1 16 4.07017543859649 ABL1-mRNA -1 0.252 -1.5 -0.508 0.000217 0.0093 CC.PLS.Apop, Driver Gene, RAS NS_CANCERPATH_C2535 ABL1 mRNA 0 CC.PLS.Apop;RAS;Driver Gene hsa04012;hsa04014;hsa04110;hsa04360;hsa04722;hsa05130;hsa05131;hsa05200;hsa05206;hsa05220;hsa05416 ABL1 chartreuse1 16 -3.96825396825397 MSH6-mRNA 0.754 0.19 0.382 1.13 0.000217 0.0093 Driver Gene NS_CANCERPATH_C2535 MSH6 mRNA 0 Driver Gene hsa03430;hsa05200;hsa05210 MSH6 chartreuse1 16 3.96842105263158 GNA11-mRNA -0.945 0.239 -1.41 -0.477 0.000233 0.00975 Driver Gene NS_CANCERPATH_C2535 GNA11 mRNA 0 Driver Gene hsa04020;hsa04022;hsa04270;hsa04540;hsa04725;hsa04730;hsa04911;hsa04912;hsa04925;hsa05142;hsa05146;hsa05200 GNA11 chartreuse1 16 -3.95397489539749 DNMT1-mRNA 1.03 0.262 0.521 1.55 0.000238 0.00986 Driver Gene NS_CANCERPATH_C2535 DNMT1 mRNA 0 Driver Gene hsa01100;hsa05206 DNMT1 chartreuse1 16 3.93129770992366 SMARCA4-mRNA 0.886 0.228 0.44 1.33 0.000284 0.0109 Driver Gene NS_CANCERPATH_C2535 SMARCA4 mRNA 0 Driver Gene SMARCA4 chartreuse2 16 3.8859649122807 NRAS-mRNA 0.94 0.251 0.449 1.43 0.000443 0.0157 Driver Gene, MAPK, PI3K, RAS NS_CANCERPATH_C2535 NRAS mRNA 0 RAS;PI3K;MAPK;Driver Gene hsa04010;hsa04012;hsa04014;hsa04015;hsa04062;hsa04068;hsa04071;hsa04072;hsa04151;hsa04211;hsa04360;hsa04370;hsa04530;hsa04540;hsa04550;hsa04650;hsa04660;hsa04662;hsa04664;hsa04720;hsa04722;hsa04725;hsa04726;hsa04730;hsa04810;hsa04910;hsa04912;hsa04915;hsa04916;hsa04917;hsa04919;hsa04921;hsa04933;hsa05034;hsa05160;hsa05161;hsa05166;hsa05200;hsa05203;hsa05205;hsa05206;hsa05211;hsa05213;hsa05214;hsa05215;hsa05216;hsa05218;hsa05219;hsa05220;hsa05221;hsa05223;hsa05230;hsa05231 NRAS chartreuse2 16 3.74501992031872 DE Results - Driver Gene genes - SubtypeC
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
Volcano Plot: SubtypeD
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Volcano Plot: SubtypeD
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - Driver Gene genes - SubtypeD
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all ERBB2-mRNA 4.62 0.51 3.62 5.62 2.79e-12 5.56e-09 Driver Gene NS_CANCERPATH_C2535 ERBB2 mRNA 0 Driver Gene hsa04012;hsa04020;hsa04066;hsa04510;hsa04520;hsa05200;hsa05205;hsa05206;hsa05212;hsa05213;hsa05215;hsa05219;hsa05223;hsa05230 ERBB2 chartreuse1 16 9.05882352941176 KIT-mRNA -3.33 0.426 -4.17 -2.5 2.48e-10 3.29e-07 Driver Gene, PI3K, RAS NS_CANCERPATH_C2535 KIT mRNA 0 RAS;PI3K;Driver Gene hsa04014;hsa04015;hsa04060;hsa04072;hsa04144;hsa04151;hsa04640;hsa04916;hsa05200;hsa05221;hsa05230 KIT chartreuse1 16 -7.8169014084507 EZH2-mRNA 2.26 0.303 1.66 2.85 1e-09 6.58e-07 Driver Gene NS_CANCERPATH_C2535 EZH2 mRNA 0 Driver Gene hsa05206 EZH2 chartreuse1 16 7.45874587458746 BRCA2-mRNA 1.58 0.262 1.07 2.1 1.69e-07 2.58e-05 DNARepair, Driver Gene NS_CANCERPATH_C2535 BRCA2 mRNA 0 DNARepair;Driver Gene hsa03440;hsa03460;hsa05200;hsa05212 BRCA2 chartreuse1 16 6.03053435114504 HIST1H3B-mRNA 2.87 0.526 1.84 3.9 1.4e-06 0.000155 Driver Gene, TXmisReg NS_CANCERPATH_C2535 HIST1H3B mRNA 0 TXmisReg;Driver Gene hsa05034;hsa05202;hsa05322 HIST1H3B chartreuse1 16 5.45627376425856 KLF4-mRNA -2.02 0.375 -2.75 -1.28 1.79e-06 0.000187 Driver Gene NS_CANCERPATH_C2535 KLF4 mRNA 0 Driver Gene hsa04550 KLF4 chartreuse1 16 -5.38666666666667 KRAS-mRNA 1.53 0.286 0.975 2.09 1.84e-06 0.000188 Driver Gene, MAPK, PI3K, RAS NS_CANCERPATH_C2535 KRAS mRNA 0 RAS;PI3K;MAPK;Driver Gene hsa04010;hsa04012;hsa04014;hsa04015;hsa04062;hsa04068;hsa04071;hsa04072;hsa04151;hsa04211;hsa04320;hsa04360;hsa04370;hsa04530;hsa04540;hsa04550;hsa04650;hsa04660;hsa04662;hsa04664;hsa04720;hsa04722;hsa04725;hsa04726;hsa04730;hsa04810;hsa04910;hsa04912;hsa04914;hsa04915;hsa04916;hsa04917;hsa04919;hsa04921;hsa04933;hsa04960;hsa05034;hsa05160;hsa05161;hsa05166;hsa05200;hsa05203;hsa05205;hsa05206;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05216;hsa05218;hsa05219;hsa05220;hsa05221;hsa05223;hsa05230;hsa05231 KRAS chartreuse1 16 5.34965034965035 PDGFRA-mRNA -1.87 0.361 -2.58 -1.16 3.73e-06 0.000337 Driver Gene, MAPK, PI3K, RAS NS_CANCERPATH_C2535 PDGFRA mRNA 0 RAS;PI3K;MAPK;Driver Gene hsa04010;hsa04014;hsa04015;hsa04020;hsa04060;hsa04072;hsa04144;hsa04151;hsa04510;hsa04540;hsa04810;hsa05166;hsa05200;hsa05206;hsa05214;hsa05215;hsa05218;hsa05230;hsa05231 PDGFRA chartreuse1 16 -5.18005540166205 IDH2-mRNA 1.84 0.355 1.14 2.53 3.84e-06 0.00034 Driver Gene NS_CANCERPATH_C2535 IDH2 mRNA 0 Driver Gene hsa01100 IDH2 chartreuse1 16 5.1830985915493 MYD88-mRNA 1.04 0.219 0.612 1.47 1.62e-05 0.00113 CC.PLS.Apop, Driver Gene NS_CANCERPATH_C2535 MYD88 mRNA 0 CC.PLS.Apop;Driver Gene hsa04064;hsa04210;hsa04620;hsa05132;hsa05133;hsa05134;hsa05140;hsa05142;hsa05143;hsa05144;hsa05145;hsa05152;hsa05161;hsa05162;hsa05164;hsa05168 MYD88 chartreuse1 16 4.74885844748858 SMARCA4-mRNA 1.03 0.22 0.603 1.47 1.93e-05 0.0013 Driver Gene NS_CANCERPATH_C2535 SMARCA4 mRNA 0 Driver Gene SMARCA4 chartreuse1 16 4.68181818181818 PIK3R1-mRNA -1.3 0.315 -1.92 -0.683 0.000133 0.00749 CC.PLS.Apop, Driver Gene, JAK-STAT, PI3K, RAS NS_CANCERPATH_C2535 PIK3R1 mRNA 0 CC.PLS.Apop;RAS;PI3K;JAK-STAT;Driver Gene hsa04012;hsa04014;hsa04015;hsa04022;hsa04024;hsa04062;hsa04066;hsa04068;hsa04070;hsa04071;hsa04072;hsa04150;hsa04151;hsa04152;hsa04210;hsa04211;hsa04261;hsa04370;hsa04380;hsa04510;hsa04550;hsa04611;hsa04620;hsa04630;hsa04650;hsa04660;hsa04662;hsa04664;hsa04666;hsa04668;hsa04670;hsa04722;hsa04725;hsa04750;hsa04810;hsa04910;hsa04914;hsa04915;hsa04917;hsa04919;hsa04921;hsa04923;hsa04930;hsa04931;hsa04932;hsa04933;hsa04960;hsa04973;hsa05100;hsa05142;hsa05145;hsa05146;hsa05160;hsa05161;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05220;hsa05221;hsa05222;hsa05223;hsa05230;hsa05231 PIK3R1 chartreuse1 16 -4.12698412698413 ASXL1-mRNA -0.971 0.241 -1.44 -0.499 0.000179 0.00939 Driver Gene NS_CANCERPATH_C2535 ASXL1 mRNA 0 Driver Gene ASXL1 chartreuse2 16 -4.02904564315353 PTCH1-mRNA -1.39 0.358 -2.09 -0.692 0.000282 0.0142 Driver Gene, HH NS_CANCERPATH_C2535 PTCH1 mRNA 0 HH;Driver Gene hsa04024;hsa04340;hsa05200;hsa05205;hsa05217 PTCH1 chartreuse2 16 -3.88268156424581 SETBP1-mRNA -1.88 0.496 -2.85 -0.911 0.000384 0.0179 Driver Gene NS_CANCERPATH_C2535 SETBP1 mRNA 0 Driver Gene SETBP1 chartreuse2 16 -3.79032258064516 AKT1-mRNA 1.14 0.308 0.537 1.74 0.000514 0.023 CC.PLS.Apop, Driver Gene, JAK-STAT, MAPK, PI3K, RAS NS_CANCERPATH_C2535 AKT1 mRNA 0 CC.PLS.Apop;RAS;PI3K;JAK-STAT;MAPK;Driver Gene hsa04010;hsa04012;hsa04014;hsa04015;hsa04022;hsa04024;hsa04062;hsa04066;hsa04068;hsa04071;hsa04072;hsa04150;hsa04151;hsa04152;hsa04210;hsa04211;hsa04261;hsa04370;hsa04380;hsa04510;hsa04530;hsa04550;hsa04611;hsa04620;hsa04630;hsa04660;hsa04662;hsa04664;hsa04666;hsa04668;hsa04722;hsa04725;hsa04728;hsa04910;hsa04914;hsa04915;hsa04917;hsa04919;hsa04920;hsa04922;hsa04923;hsa04931;hsa04932;hsa04933;hsa04973;hsa05142;hsa05145;hsa05152;hsa05160;hsa05161;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05205;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05220;hsa05221;hsa05222;hsa05223;hsa05230;hsa05231 AKT1 chartreuse2 16 3.7012987012987 EGFR-mRNA -1.8 0.526 -2.83 -0.769 0.00122 0.0465 Driver Gene, MAPK, PI3K, RAS NS_CANCERPATH_C2535 EGFR mRNA 0 RAS;PI3K;MAPK;Driver Gene hsa04010;hsa04012;hsa04014;hsa04015;hsa04020;hsa04060;hsa04066;hsa04068;hsa04072;hsa04144;hsa04151;hsa04320;hsa04510;hsa04520;hsa04540;hsa04810;hsa04912;hsa04915;hsa04921;hsa05120;hsa05160;hsa05200;hsa05205;hsa05206;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05219;hsa05223;hsa05230;hsa05231 EGFR chartreuse2 16 -3.42205323193916 BCL2-mRNA -1.54 0.452 -2.43 -0.659 0.00123 0.0465 CC.PLS.Apop, Driver Gene, PI3K NS_CANCERPATH_C2535 BCL2 mRNA 0 CC.PLS.Apop;PI3K;Driver Gene hsa04064;hsa04066;hsa04071;hsa04141;hsa04151;hsa04210;hsa04261;hsa04510;hsa04630;hsa04722;hsa04725;hsa04933;hsa05014;hsa05145;hsa05152;hsa05161;hsa05169;hsa05200;hsa05206;hsa05210;hsa05215;hsa05222 BCL2 chartreuse2 16 -3.4070796460177 DNMT1-mRNA 0.848 0.253 0.351 1.34 0.00153 0.0562 Driver Gene NS_CANCERPATH_C2535 DNMT1 mRNA 0 Driver Gene hsa01100;hsa05206 DNMT1 chartreuse3 16 3.35177865612648 MEN1-mRNA 0.744 0.238 0.278 1.21 0.0029 0.0922 Driver Gene, TXmisReg NS_CANCERPATH_C2535 MEN1 mRNA 0 TXmisReg;Driver Gene hsa05202 MEN1 chartreuse3 16 3.12605042016807 DE Results - Driver Gene genes - SubtypeD
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
- Subtype:
- SubtypeA
- SubtypeB
- SubtypeC
- SubtypeD
Volcano Plot: SubtypeA
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Volcano Plot: SubtypeA
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - HH genes - SubtypeA
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all PTCH1-mRNA -1.12 0.365 -1.84 -0.408 0.00334 0.187 Driver Gene, HH NS_CANCERPATH_C2535 PTCH1 mRNA 0 HH;Driver Gene hsa04024;hsa04340;hsa05200;hsa05205;hsa05217 PTCH1 chartreuse4 16 -3.06849315068493 GAS1-mRNA -1.44 0.494 -2.41 -0.473 0.00521 0.25 HH NS_CANCERPATH_C2535 GAS1 mRNA 0 HH hsa04340 GAS1 chartreuse4 16 -2.91497975708502 WNT7B-mRNA 1.65 0.712 0.253 3.04 0.0246 0.74 HH, Wnt NS_CANCERPATH_C2535 WNT7B mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT7B azure4 1 2.31741573033708 SMO-mRNA -0.829 0.394 -1.6 -0.0572 0.0401 1 Driver Gene, HH NS_CANCERPATH_C2535 SMO mRNA 0 HH;Driver Gene hsa04340;hsa05200;hsa05205;hsa05217 SMO azure4 1 -2.10406091370558 WNT10A-mRNA 0.687 0.354 -0.00666 1.38 0.0577 1 HH, Wnt NS_CANCERPATH_C2535 WNT10A mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT10A azure4 1 1.9406779661017 PRKACA-mRNA -0.61 0.344 -1.28 0.0642 0.082 1 CC.PLS.Apop, HH, MAPK, RAS, Wnt NS_CANCERPATH_C2535 PRKACA mRNA 0 CC.PLS.Apop;RAS;MAPK;HH;Wnt hsa04010;hsa04014;hsa04020;hsa04024;hsa04062;hsa04114;hsa04210;hsa04211;hsa04261;hsa04270;hsa04310;hsa04340;hsa04540;hsa04611;hsa04713;hsa04720;hsa04723;hsa04724;hsa04725;hsa04726;hsa04727;hsa04728;hsa04740;hsa04750;hsa04910;hsa04911;hsa04912;hsa04913;hsa04914;hsa04915;hsa04916;hsa04918;hsa04919;hsa04921;hsa04922;hsa04923;hsa04924;hsa04925;hsa04961;hsa04962;hsa04970;hsa04971;hsa05012;hsa05020;hsa05030;hsa05031;hsa05032;hsa05034;hsa05110;hsa05146;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05414 PRKACA azure4 1 -1.77325581395349 GSK3B-mRNA 0.263 0.18 -0.0895 0.616 0.15 1 CC.PLS.Apop, HH, PI3K, Wnt NS_CANCERPATH_C2535 GSK3B mRNA 0 CC.PLS.Apop;PI3K;HH;Wnt hsa04012;hsa04062;hsa04110;hsa04151;hsa04310;hsa04340;hsa04360;hsa04390;hsa04510;hsa04550;hsa04660;hsa04662;hsa04722;hsa04728;hsa04910;hsa04916;hsa04917;hsa04919;hsa04931;hsa04932;hsa05010;hsa05160;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05210;hsa05213;hsa05215;hsa05217 GSK3B azure4 1 1.46111111111111 WNT5B-mRNA -0.729 0.534 -1.78 0.318 0.178 1 HH, Wnt NS_CANCERPATH_C2535 WNT5B mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT5B azure4 1 -1.36516853932584 WNT2B-mRNA -0.402 0.306 -1 0.198 0.195 1 HH, Wnt NS_CANCERPATH_C2535 WNT2B mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT2B azure4 1 -1.31372549019608 BMP4-mRNA -0.654 0.518 -1.67 0.362 0.213 1 HH, TGF-B NS_CANCERPATH_C2535 BMP4 mRNA 0 TGF-B;HH hsa04340;hsa04350;hsa04390;hsa04550;hsa04919;hsa05200;hsa05217 BMP4 azure4 1 -1.26254826254826 WNT5A-mRNA 0.858 0.698 -0.51 2.23 0.224 1 HH, Wnt NS_CANCERPATH_C2535 WNT5A mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT5A azure4 1 1.22922636103152 WNT3-mRNA 0.657 0.558 -0.436 1.75 0.244 1 HH, Wnt NS_CANCERPATH_C2535 WNT3 mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05206;hsa05217 WNT3 azure4 1 1.17741935483871 WNT4-mRNA 0.439 0.588 -0.713 1.59 0.458 1 HH, Wnt NS_CANCERPATH_C2535 WNT4 mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa04919;hsa05166;hsa05200;hsa05205;hsa05217 WNT4 azure4 1 0.746598639455782 WNT2-mRNA 0.305 0.424 -0.527 1.14 0.475 1 HH, Wnt NS_CANCERPATH_C2535 WNT2 mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT2 azure4 1 0.719339622641509 PRKACB-mRNA -0.158 0.55 -1.24 0.92 0.775 1 CC.PLS.Apop, HH, MAPK, RAS, Wnt NS_CANCERPATH_C2535 PRKACB mRNA 0 CC.PLS.Apop;RAS;MAPK;HH;Wnt hsa04010;hsa04014;hsa04020;hsa04024;hsa04062;hsa04114;hsa04210;hsa04211;hsa04261;hsa04270;hsa04310;hsa04340;hsa04540;hsa04611;hsa04713;hsa04720;hsa04723;hsa04724;hsa04725;hsa04726;hsa04727;hsa04728;hsa04740;hsa04750;hsa04910;hsa04911;hsa04912;hsa04913;hsa04914;hsa04915;hsa04916;hsa04918;hsa04919;hsa04921;hsa04922;hsa04923;hsa04924;hsa04925;hsa04961;hsa04962;hsa04970;hsa04971;hsa05012;hsa05020;hsa05030;hsa05031;hsa05032;hsa05110;hsa05146;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05414 PRKACB azure4 1 -0.287272727272727 PRKX-mRNA -0.0751 0.334 -0.729 0.579 0.823 1 CC.PLS.Apop, HH, MAPK, RAS, Wnt NS_CANCERPATH_C2535 PRKX mRNA 0 CC.PLS.Apop;RAS;MAPK;HH;Wnt PRKX azure4 1 -0.224850299401198 GLI3-mRNA 0.0358 0.443 -0.832 0.904 0.936 1 HH NS_CANCERPATH_C2535 GLI3 mRNA 0 HH hsa04024;hsa04340;hsa05200;hsa05217 GLI3 azure4 1 0.0808126410835214 WNT6-mRNA -0.0245 0.373 -0.755 0.706 0.948 1 HH, Wnt NS_CANCERPATH_C2535 WNT6 mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT6 azure4 1 -0.0656836461126005 LRP2-mRNA 0.00423 1.08 -2.11 2.12 0.997 1 HH NS_CANCERPATH_C2535 LRP2 mRNA 0 HH hsa04340;hsa04918 LRP2 azure4 1 0.00391666666666667 DE Results - HH genes - SubtypeA
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
Volcano Plot: SubtypeB
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Volcano Plot: SubtypeB
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - HH genes - SubtypeB
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all PTCH1-mRNA -1.91 0.344 -2.59 -1.24 9.52e-07 9.24e-05 Driver Gene, HH NS_CANCERPATH_C2535 PTCH1 mRNA 0 HH;Driver Gene hsa04024;hsa04340;hsa05200;hsa05205;hsa05217 PTCH1 chartreuse1 16 -5.55232558139535 GAS1-mRNA -1.73 0.466 -2.65 -0.82 0.000488 0.0198 HH NS_CANCERPATH_C2535 GAS1 mRNA 0 HH hsa04340 GAS1 chartreuse2 16 -3.71244635193133 BMP4-mRNA -1.43 0.488 -2.39 -0.474 0.00503 0.137 HH, TGF-B NS_CANCERPATH_C2535 BMP4 mRNA 0 TGF-B;HH hsa04340;hsa04350;hsa04390;hsa04550;hsa04919;hsa05200;hsa05217 BMP4 chartreuse4 16 -2.93032786885246 WNT2B-mRNA -0.781 0.288 -1.35 -0.216 0.00907 0.216 HH, Wnt NS_CANCERPATH_C2535 WNT2B mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT2B chartreuse4 16 -2.71180555555556 SMO-mRNA -0.978 0.371 -1.71 -0.251 0.011 0.247 Driver Gene, HH NS_CANCERPATH_C2535 SMO mRNA 0 HH;Driver Gene hsa04340;hsa05200;hsa05205;hsa05217 SMO chartreuse4 16 -2.63611859838275 WNT7B-mRNA 1.75 0.671 0.433 3.06 0.0119 0.256 HH, Wnt NS_CANCERPATH_C2535 WNT7B mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT7B chartreuse4 16 2.6080476900149 GSK3B-mRNA 0.351 0.17 0.0186 0.684 0.0435 0.681 CC.PLS.Apop, HH, PI3K, Wnt NS_CANCERPATH_C2535 GSK3B mRNA 0 CC.PLS.Apop;PI3K;HH;Wnt hsa04012;hsa04062;hsa04110;hsa04151;hsa04310;hsa04340;hsa04360;hsa04390;hsa04510;hsa04550;hsa04660;hsa04662;hsa04722;hsa04728;hsa04910;hsa04916;hsa04917;hsa04919;hsa04931;hsa04932;hsa05010;hsa05160;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05210;hsa05213;hsa05215;hsa05217 GSK3B azure4 1 2.06470588235294 LRP2-mRNA -1.62 1.02 -3.61 0.381 0.119 1 HH NS_CANCERPATH_C2535 LRP2 mRNA 0 HH hsa04340;hsa04918 LRP2 azure4 1 -1.58823529411765 WNT3-mRNA 0.829 0.526 -0.201 1.86 0.121 1 HH, Wnt NS_CANCERPATH_C2535 WNT3 mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05206;hsa05217 WNT3 azure4 1 1.57604562737643 PRKACA-mRNA -0.476 0.324 -1.11 0.159 0.148 1 CC.PLS.Apop, HH, MAPK, RAS, Wnt NS_CANCERPATH_C2535 PRKACA mRNA 0 CC.PLS.Apop;RAS;MAPK;HH;Wnt hsa04010;hsa04014;hsa04020;hsa04024;hsa04062;hsa04114;hsa04210;hsa04211;hsa04261;hsa04270;hsa04310;hsa04340;hsa04540;hsa04611;hsa04713;hsa04720;hsa04723;hsa04724;hsa04725;hsa04726;hsa04727;hsa04728;hsa04740;hsa04750;hsa04910;hsa04911;hsa04912;hsa04913;hsa04914;hsa04915;hsa04916;hsa04918;hsa04919;hsa04921;hsa04922;hsa04923;hsa04924;hsa04925;hsa04961;hsa04962;hsa04970;hsa04971;hsa05012;hsa05020;hsa05030;hsa05031;hsa05032;hsa05034;hsa05110;hsa05146;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05414 PRKACA azure4 1 -1.46913580246914 WNT6-mRNA -0.465 0.351 -1.15 0.223 0.191 1 HH, Wnt NS_CANCERPATH_C2535 WNT6 mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT6 azure4 1 -1.32478632478632 WNT2-mRNA 0.503 0.4 -0.28 1.29 0.214 1 HH, Wnt NS_CANCERPATH_C2535 WNT2 mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT2 azure4 1 1.2575 WNT5B-mRNA -0.488 0.503 -1.47 0.498 0.336 1 HH, Wnt NS_CANCERPATH_C2535 WNT5B mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT5B azure4 1 -0.970178926441352 PRKACB-mRNA -0.39 0.518 -1.41 0.625 0.455 1 CC.PLS.Apop, HH, MAPK, RAS, Wnt NS_CANCERPATH_C2535 PRKACB mRNA 0 CC.PLS.Apop;RAS;MAPK;HH;Wnt hsa04010;hsa04014;hsa04020;hsa04024;hsa04062;hsa04114;hsa04210;hsa04211;hsa04261;hsa04270;hsa04310;hsa04340;hsa04540;hsa04611;hsa04713;hsa04720;hsa04723;hsa04724;hsa04725;hsa04726;hsa04727;hsa04728;hsa04740;hsa04750;hsa04910;hsa04911;hsa04912;hsa04913;hsa04914;hsa04915;hsa04916;hsa04918;hsa04919;hsa04921;hsa04922;hsa04923;hsa04924;hsa04925;hsa04961;hsa04962;hsa04970;hsa04971;hsa05012;hsa05020;hsa05030;hsa05031;hsa05032;hsa05110;hsa05146;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05414 PRKACB azure4 1 -0.752895752895753 PRKX-mRNA -0.214 0.315 -0.83 0.403 0.5 1 CC.PLS.Apop, HH, MAPK, RAS, Wnt NS_CANCERPATH_C2535 PRKX mRNA 0 CC.PLS.Apop;RAS;MAPK;HH;Wnt PRKX azure4 1 -0.679365079365079 WNT4-mRNA 0.256 0.554 -0.83 1.34 0.646 1 HH, Wnt NS_CANCERPATH_C2535 WNT4 mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa04919;hsa05166;hsa05200;hsa05205;hsa05217 WNT4 azure4 1 0.462093862815884 WNT5A-mRNA 0.281 0.658 -1.01 1.57 0.671 1 HH, Wnt NS_CANCERPATH_C2535 WNT5A mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT5A azure4 1 0.427051671732523 WNT10A-mRNA 0.103 0.333 -0.551 0.756 0.759 1 HH, Wnt NS_CANCERPATH_C2535 WNT10A mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT10A azure4 1 0.309309309309309 GLI3-mRNA -0.0685 0.417 -0.886 0.75 0.87 1 HH NS_CANCERPATH_C2535 GLI3 mRNA 0 HH hsa04024;hsa04340;hsa05200;hsa05217 GLI3 azure4 1 -0.164268585131895 DE Results - HH genes - SubtypeB
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
Volcano Plot: SubtypeC
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Volcano Plot: SubtypeC
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - HH genes - SubtypeC
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all BMP4-mRNA -2.65 0.525 -3.68 -1.62 5.79e-06 0.000397 HH, TGF-B NS_CANCERPATH_C2535 BMP4 mRNA 0 TGF-B;HH hsa04340;hsa04350;hsa04390;hsa04550;hsa04919;hsa05200;hsa05217 BMP4 chartreuse1 16 -5.04761904761905 PRKX-mRNA 1.3 0.338 0.632 1.96 0.000348 0.0127 CC.PLS.Apop, HH, MAPK, RAS, Wnt NS_CANCERPATH_C2535 PRKX mRNA 0 CC.PLS.Apop;RAS;MAPK;HH;Wnt PRKX chartreuse2 16 3.84615384615385 GAS1-mRNA -1.66 0.501 -2.65 -0.683 0.00163 0.0457 HH NS_CANCERPATH_C2535 GAS1 mRNA 0 HH hsa04340 GAS1 chartreuse2 16 -3.31337325349301 GLI3-mRNA -1.46 0.449 -2.33 -0.576 0.00207 0.0561 HH NS_CANCERPATH_C2535 GLI3 mRNA 0 HH hsa04024;hsa04340;hsa05200;hsa05217 GLI3 chartreuse3 16 -3.25167037861915 LRP2-mRNA -2.55 1.1 -4.69 -0.4 0.024 0.424 HH NS_CANCERPATH_C2535 LRP2 mRNA 0 HH hsa04340;hsa04918 LRP2 chartreuse4 16 -2.31818181818182 GSK3B-mRNA 0.422 0.182 0.0639 0.779 0.0249 0.43 CC.PLS.Apop, HH, PI3K, Wnt NS_CANCERPATH_C2535 GSK3B mRNA 0 CC.PLS.Apop;PI3K;HH;Wnt hsa04012;hsa04062;hsa04110;hsa04151;hsa04310;hsa04340;hsa04360;hsa04390;hsa04510;hsa04550;hsa04660;hsa04662;hsa04722;hsa04728;hsa04910;hsa04916;hsa04917;hsa04919;hsa04931;hsa04932;hsa05010;hsa05160;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05210;hsa05213;hsa05215;hsa05217 GSK3B chartreuse4 16 2.31868131868132 PRKACA-mRNA -0.654 0.349 -1.34 0.0294 0.0663 0.959 CC.PLS.Apop, HH, MAPK, RAS, Wnt NS_CANCERPATH_C2535 PRKACA mRNA 0 CC.PLS.Apop;RAS;MAPK;HH;Wnt hsa04010;hsa04014;hsa04020;hsa04024;hsa04062;hsa04114;hsa04210;hsa04211;hsa04261;hsa04270;hsa04310;hsa04340;hsa04540;hsa04611;hsa04713;hsa04720;hsa04723;hsa04724;hsa04725;hsa04726;hsa04727;hsa04728;hsa04740;hsa04750;hsa04910;hsa04911;hsa04912;hsa04913;hsa04914;hsa04915;hsa04916;hsa04918;hsa04919;hsa04921;hsa04922;hsa04923;hsa04924;hsa04925;hsa04961;hsa04962;hsa04970;hsa04971;hsa05012;hsa05020;hsa05030;hsa05031;hsa05032;hsa05034;hsa05110;hsa05146;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05414 PRKACA azure4 1 -1.87392550143267 WNT10A-mRNA 0.626 0.359 -0.0762 1.33 0.0865 1 HH, Wnt NS_CANCERPATH_C2535 WNT10A mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT10A azure4 1 1.74373259052925 WNT4-mRNA -0.85 0.596 -2.02 0.318 0.16 1 HH, Wnt NS_CANCERPATH_C2535 WNT4 mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa04919;hsa05166;hsa05200;hsa05205;hsa05217 WNT4 azure4 1 -1.4261744966443 PRKACB-mRNA -0.761 0.557 -1.85 0.331 0.178 1 CC.PLS.Apop, HH, MAPK, RAS, Wnt NS_CANCERPATH_C2535 PRKACB mRNA 0 CC.PLS.Apop;RAS;MAPK;HH;Wnt hsa04010;hsa04014;hsa04020;hsa04024;hsa04062;hsa04114;hsa04210;hsa04211;hsa04261;hsa04270;hsa04310;hsa04340;hsa04540;hsa04611;hsa04713;hsa04720;hsa04723;hsa04724;hsa04725;hsa04726;hsa04727;hsa04728;hsa04740;hsa04750;hsa04910;hsa04911;hsa04912;hsa04913;hsa04914;hsa04915;hsa04916;hsa04918;hsa04919;hsa04921;hsa04922;hsa04923;hsa04924;hsa04925;hsa04961;hsa04962;hsa04970;hsa04971;hsa05012;hsa05020;hsa05030;hsa05031;hsa05032;hsa05110;hsa05146;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05414 PRKACB azure4 1 -1.36624775583483 WNT2B-mRNA -0.391 0.31 -0.999 0.216 0.212 1 HH, Wnt NS_CANCERPATH_C2535 WNT2B mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT2B azure4 1 -1.26129032258065 WNT2-mRNA 0.457 0.43 -0.386 1.3 0.293 1 HH, Wnt NS_CANCERPATH_C2535 WNT2 mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT2 azure4 1 1.06279069767442 WNT6-mRNA 0.29 0.378 -0.45 1.03 0.445 1 HH, Wnt NS_CANCERPATH_C2535 WNT6 mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT6 azure4 1 0.767195767195767 WNT7B-mRNA 0.486 0.721 -0.927 1.9 0.503 1 HH, Wnt NS_CANCERPATH_C2535 WNT7B mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT7B azure4 1 0.674063800277393 WNT3-mRNA 0.321 0.565 -0.787 1.43 0.573 1 HH, Wnt NS_CANCERPATH_C2535 WNT3 mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05206;hsa05217 WNT3 azure4 1 0.568141592920354 PTCH1-mRNA -0.194 0.37 -0.92 0.531 0.602 1 Driver Gene, HH NS_CANCERPATH_C2535 PTCH1 mRNA 0 HH;Driver Gene hsa04024;hsa04340;hsa05200;hsa05205;hsa05217 PTCH1 azure4 1 -0.524324324324324 SMO-mRNA 0.0479 0.399 -0.734 0.83 0.905 1 Driver Gene, HH NS_CANCERPATH_C2535 SMO mRNA 0 HH;Driver Gene hsa04340;hsa05200;hsa05205;hsa05217 SMO azure4 1 0.120050125313283 WNT5A-mRNA 0.0489 0.707 -1.34 1.44 0.945 1 HH, Wnt NS_CANCERPATH_C2535 WNT5A mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT5A azure4 1 0.0691654879773692 WNT5B-mRNA 0.0266 0.541 -1.03 1.09 0.961 1 HH, Wnt NS_CANCERPATH_C2535 WNT5B mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT5B azure4 1 0.0491682070240296 DE Results - HH genes - SubtypeC
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
Volcano Plot: SubtypeD
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Volcano Plot: SubtypeD
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - HH genes - SubtypeD
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all PTCH1-mRNA -1.39 0.358 -2.09 -0.692 0.000282 0.0142 Driver Gene, HH NS_CANCERPATH_C2535 PTCH1 mRNA 0 HH;Driver Gene hsa04024;hsa04340;hsa05200;hsa05205;hsa05217 PTCH1 chartreuse2 16 -3.88268156424581 GSK3B-mRNA 0.639 0.176 0.294 0.985 0.000654 0.0283 CC.PLS.Apop, HH, PI3K, Wnt NS_CANCERPATH_C2535 GSK3B mRNA 0 CC.PLS.Apop;PI3K;HH;Wnt hsa04012;hsa04062;hsa04110;hsa04151;hsa04310;hsa04340;hsa04360;hsa04390;hsa04510;hsa04550;hsa04660;hsa04662;hsa04722;hsa04728;hsa04910;hsa04916;hsa04917;hsa04919;hsa04931;hsa04932;hsa05010;hsa05160;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05210;hsa05213;hsa05215;hsa05217 GSK3B chartreuse2 16 3.63068181818182 GAS1-mRNA -1.66 0.484 -2.61 -0.712 0.00119 0.0464 HH NS_CANCERPATH_C2535 GAS1 mRNA 0 HH hsa04340 GAS1 chartreuse2 16 -3.4297520661157 LRP2-mRNA -3.03 1.06 -5.11 -0.959 0.00599 0.16 HH NS_CANCERPATH_C2535 LRP2 mRNA 0 HH hsa04340;hsa04918 LRP2 chartreuse4 16 -2.85849056603774 WNT7B-mRNA 1.89 0.697 0.52 3.25 0.00919 0.218 HH, Wnt NS_CANCERPATH_C2535 WNT7B mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT7B chartreuse4 16 2.7116212338594 WNT10A-mRNA 0.671 0.346 -0.00815 1.35 0.0583 0.92 HH, Wnt NS_CANCERPATH_C2535 WNT10A mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT10A azure4 1 1.9393063583815 BMP4-mRNA -0.91 0.508 -1.91 0.0851 0.0789 1 HH, TGF-B NS_CANCERPATH_C2535 BMP4 mRNA 0 TGF-B;HH hsa04340;hsa04350;hsa04390;hsa04550;hsa04919;hsa05200;hsa05217 BMP4 azure4 1 -1.79133858267717 WNT2-mRNA 0.571 0.416 -0.244 1.39 0.175 1 HH, Wnt NS_CANCERPATH_C2535 WNT2 mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT2 azure4 1 1.37259615384615 PRKACA-mRNA -0.455 0.337 -1.12 0.205 0.182 1 CC.PLS.Apop, HH, MAPK, RAS, Wnt NS_CANCERPATH_C2535 PRKACA mRNA 0 CC.PLS.Apop;RAS;MAPK;HH;Wnt hsa04010;hsa04014;hsa04020;hsa04024;hsa04062;hsa04114;hsa04210;hsa04211;hsa04261;hsa04270;hsa04310;hsa04340;hsa04540;hsa04611;hsa04713;hsa04720;hsa04723;hsa04724;hsa04725;hsa04726;hsa04727;hsa04728;hsa04740;hsa04750;hsa04910;hsa04911;hsa04912;hsa04913;hsa04914;hsa04915;hsa04916;hsa04918;hsa04919;hsa04921;hsa04922;hsa04923;hsa04924;hsa04925;hsa04961;hsa04962;hsa04970;hsa04971;hsa05012;hsa05020;hsa05030;hsa05031;hsa05032;hsa05034;hsa05110;hsa05146;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05414 PRKACA azure4 1 -1.35014836795252 PRKX-mRNA 0.407 0.327 -0.233 1.05 0.218 1 CC.PLS.Apop, HH, MAPK, RAS, Wnt NS_CANCERPATH_C2535 PRKX mRNA 0 CC.PLS.Apop;RAS;MAPK;HH;Wnt PRKX azure4 1 1.24464831804281 SMO-mRNA -0.434 0.386 -1.19 0.321 0.265 1 Driver Gene, HH NS_CANCERPATH_C2535 SMO mRNA 0 HH;Driver Gene hsa04340;hsa05200;hsa05205;hsa05217 SMO azure4 1 -1.12435233160622 GLI3-mRNA -0.47 0.434 -1.32 0.38 0.284 1 HH NS_CANCERPATH_C2535 GLI3 mRNA 0 HH hsa04024;hsa04340;hsa05200;hsa05217 GLI3 azure4 1 -1.08294930875576 WNT2B-mRNA -0.314 0.299 -0.901 0.273 0.3 1 HH, Wnt NS_CANCERPATH_C2535 WNT2B mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT2B azure4 1 -1.05016722408027 WNT5B-mRNA -0.44 0.523 -1.46 0.585 0.404 1 HH, Wnt NS_CANCERPATH_C2535 WNT5B mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT5B azure4 1 -0.841300191204589 WNT3-mRNA -0.396 0.546 -1.47 0.675 0.471 1 HH, Wnt NS_CANCERPATH_C2535 WNT3 mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05206;hsa05217 WNT3 azure4 1 -0.725274725274725 PRKACB-mRNA -0.384 0.539 -1.44 0.672 0.48 1 CC.PLS.Apop, HH, MAPK, RAS, Wnt NS_CANCERPATH_C2535 PRKACB mRNA 0 CC.PLS.Apop;RAS;MAPK;HH;Wnt hsa04010;hsa04014;hsa04020;hsa04024;hsa04062;hsa04114;hsa04210;hsa04211;hsa04261;hsa04270;hsa04310;hsa04340;hsa04540;hsa04611;hsa04713;hsa04720;hsa04723;hsa04724;hsa04725;hsa04726;hsa04727;hsa04728;hsa04740;hsa04750;hsa04910;hsa04911;hsa04912;hsa04913;hsa04914;hsa04915;hsa04916;hsa04918;hsa04919;hsa04921;hsa04922;hsa04923;hsa04924;hsa04925;hsa04961;hsa04962;hsa04970;hsa04971;hsa05012;hsa05020;hsa05030;hsa05031;hsa05032;hsa05110;hsa05146;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05414 PRKACB azure4 1 -0.712430426716141 WNT4-mRNA -0.338 0.576 -1.47 0.791 0.56 1 HH, Wnt NS_CANCERPATH_C2535 WNT4 mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa04919;hsa05166;hsa05200;hsa05205;hsa05217 WNT4 azure4 1 -0.586805555555556 WNT5A-mRNA 0.127 0.684 -1.21 1.47 0.854 1 HH, Wnt NS_CANCERPATH_C2535 WNT5A mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT5A azure4 1 0.185672514619883 WNT6-mRNA 0.0556 0.365 -0.659 0.771 0.879 1 HH, Wnt NS_CANCERPATH_C2535 WNT6 mRNA 0 HH;Wnt hsa04310;hsa04340;hsa04390;hsa04550;hsa04916;hsa05166;hsa05200;hsa05205;hsa05217 WNT6 azure4 1 0.152328767123288 DE Results - HH genes - SubtypeD
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
- Subtype:
- SubtypeA
- SubtypeB
- SubtypeC
- SubtypeD
Volcano Plot: SubtypeA
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Volcano Plot: SubtypeA
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - JAK-STAT genes - SubtypeA
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all IL11RA-mRNA -1.51 0.246 -1.99 -1.03 1.19e-07 0.000118 JAK-STAT NS_CANCERPATH_C2535 IL11RA mRNA 0 JAK-STAT hsa04060;hsa04630;hsa04640 IL11RA chartreuse1 16 -6.13821138211382 SPRY2-mRNA -1.82 0.342 -2.49 -1.15 2.22e-06 0.000804 JAK-STAT NS_CANCERPATH_C2535 SPRY2 mRNA 0 JAK-STAT hsa05206 SPRY2 chartreuse1 16 -5.32163742690058 LIFR-mRNA -1.99 0.434 -2.84 -1.14 3e-05 0.00562 JAK-STAT NS_CANCERPATH_C2535 LIFR mRNA 0 JAK-STAT hsa04060;hsa04550;hsa04630 LIFR chartreuse1 16 -4.5852534562212 PIK3R1-mRNA -1.47 0.322 -2.1 -0.838 3.11e-05 0.00562 CC.PLS.Apop, Driver Gene, JAK-STAT, PI3K, RAS NS_CANCERPATH_C2535 PIK3R1 mRNA 0 CC.PLS.Apop;RAS;PI3K;JAK-STAT;Driver Gene hsa04012;hsa04014;hsa04015;hsa04022;hsa04024;hsa04062;hsa04066;hsa04068;hsa04070;hsa04071;hsa04072;hsa04150;hsa04151;hsa04152;hsa04210;hsa04211;hsa04261;hsa04370;hsa04380;hsa04510;hsa04550;hsa04611;hsa04620;hsa04630;hsa04650;hsa04660;hsa04662;hsa04664;hsa04666;hsa04668;hsa04670;hsa04722;hsa04725;hsa04750;hsa04810;hsa04910;hsa04914;hsa04915;hsa04917;hsa04919;hsa04921;hsa04923;hsa04930;hsa04931;hsa04932;hsa04933;hsa04960;hsa04973;hsa05100;hsa05142;hsa05145;hsa05146;hsa05160;hsa05161;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05220;hsa05221;hsa05222;hsa05223;hsa05230;hsa05231 PIK3R1 chartreuse1 16 -4.56521739130435 GHR-mRNA -2.18 0.507 -3.18 -1.19 7.34e-05 0.0101 JAK-STAT, PI3K NS_CANCERPATH_C2535 GHR mRNA 0 PI3K;JAK-STAT hsa04060;hsa04080;hsa04151;hsa04630 GHR chartreuse2 16 -4.29980276134122 LEPR-mRNA -1.43 0.386 -2.18 -0.67 0.000525 0.0497 JAK-STAT NS_CANCERPATH_C2535 LEPR mRNA 0 JAK-STAT hsa04060;hsa04080;hsa04152;hsa04630;hsa04920;hsa04932 LEPR chartreuse3 16 -3.70466321243523 CBLC-mRNA 1.77 0.491 0.805 2.73 0.00071 0.0628 JAK-STAT NS_CANCERPATH_C2535 CBLC mRNA 0 JAK-STAT hsa04012;hsa04120;hsa04144;hsa04660;hsa04910;hsa05100;hsa05200;hsa05205;hsa05220 CBLC chartreuse3 16 3.60488798370672 SOS1-mRNA -0.53 0.148 -0.819 -0.241 0.000733 0.0634 JAK-STAT, MAPK, PI3K, RAS NS_CANCERPATH_C2535 SOS1 mRNA 0 RAS;PI3K;JAK-STAT;MAPK hsa04010;hsa04012;hsa04014;hsa04062;hsa04068;hsa04072;hsa04151;hsa04320;hsa04510;hsa04540;hsa04630;hsa04650;hsa04660;hsa04662;hsa04664;hsa04722;hsa04810;hsa04910;hsa04912;hsa04915;hsa04917;hsa05034;hsa05160;hsa05200;hsa05205;hsa05206;hsa05211;hsa05213;hsa05214;hsa05215;hsa05220;hsa05221;hsa05223;hsa05231 SOS1 chartreuse3 16 -3.58108108108108 MYC-mRNA -1.91 0.567 -3.02 -0.794 0.00146 0.112 CC.PLS.Apop, JAK-STAT, MAPK, PI3K, TGF-B, TXmisReg, Wnt NS_CANCERPATH_C2535 MYC mRNA 0 CC.PLS.Apop;PI3K;JAK-STAT;MAPK;TGF-B;TXmisReg;Wnt hsa04010;hsa04012;hsa04110;hsa04151;hsa04310;hsa04350;hsa04390;hsa04550;hsa04630;hsa04919;hsa05161;hsa05166;hsa05169;hsa05200;hsa05202;hsa05205;hsa05206;hsa05210;hsa05213;hsa05216;hsa05219;hsa05220;hsa05221;hsa05222;hsa05230 MYC chartreuse4 16 -3.36860670194004 CSF3R-mRNA 1.51 0.453 0.627 2.4 0.00155 0.114 JAK-STAT, PI3K NS_CANCERPATH_C2535 CSF3R mRNA 0 PI3K;JAK-STAT hsa04060;hsa04151;hsa04630;hsa04640;hsa05200 Neutrophils CSF3R chartreuse4 16 3.33333333333333 PIK3R5-mRNA 0.867 0.277 0.324 1.41 0.00288 0.181 CC.PLS.Apop, JAK-STAT, PI3K, RAS NS_CANCERPATH_C2535 PIK3R5 mRNA 0 CC.PLS.Apop;RAS;PI3K;JAK-STAT hsa04012;hsa04014;hsa04015;hsa04022;hsa04024;hsa04062;hsa04066;hsa04068;hsa04070;hsa04071;hsa04072;hsa04150;hsa04151;hsa04152;hsa04210;hsa04211;hsa04261;hsa04370;hsa04380;hsa04510;hsa04550;hsa04611;hsa04620;hsa04630;hsa04650;hsa04660;hsa04662;hsa04664;hsa04666;hsa04668;hsa04670;hsa04722;hsa04725;hsa04750;hsa04810;hsa04910;hsa04914;hsa04915;hsa04917;hsa04919;hsa04921;hsa04923;hsa04930;hsa04931;hsa04932;hsa04933;hsa04960;hsa04973;hsa05100;hsa05142;hsa05145;hsa05146;hsa05160;hsa05161;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05220;hsa05221;hsa05222;hsa05223;hsa05230;hsa05231 PIK3R5 chartreuse4 16 3.12996389891697 PTPN11-mRNA -0.572 0.189 -0.942 -0.203 0.00375 0.202 Driver Gene, JAK-STAT, RAS NS_CANCERPATH_C2535 PTPN11 mRNA 0 RAS;JAK-STAT;Driver Gene hsa04014;hsa04072;hsa04630;hsa04650;hsa04670;hsa04722;hsa04920;hsa04931;hsa05120;hsa05168;hsa05205;hsa05211;hsa05220 PTPN11 chartreuse4 16 -3.02645502645503 SPRY1-mRNA -1.09 0.361 -1.8 -0.383 0.00391 0.207 JAK-STAT NS_CANCERPATH_C2535 SPRY1 mRNA 0 JAK-STAT SPRY1 chartreuse4 16 -3.01939058171745 CCND2-mRNA -0.805 0.325 -1.44 -0.168 0.0165 0.557 CC.PLS.Apop, JAK-STAT, PI3K, TXmisReg, Wnt NS_CANCERPATH_C2535 CCND2 mRNA 0 CC.PLS.Apop;PI3K;JAK-STAT;TXmisReg;Wnt hsa04068;hsa04110;hsa04115;hsa04151;hsa04310;hsa04390;hsa04510;hsa04630;hsa04917;hsa05162;hsa05166;hsa05202;hsa05203;hsa05206 CCND2 azure4 1 -2.47692307692308 AKT1-mRNA 0.777 0.314 0.161 1.39 0.0167 0.559 CC.PLS.Apop, Driver Gene, JAK-STAT, MAPK, PI3K, RAS NS_CANCERPATH_C2535 AKT1 mRNA 0 CC.PLS.Apop;RAS;PI3K;JAK-STAT;MAPK;Driver Gene hsa04010;hsa04012;hsa04014;hsa04015;hsa04022;hsa04024;hsa04062;hsa04066;hsa04068;hsa04071;hsa04072;hsa04150;hsa04151;hsa04152;hsa04210;hsa04211;hsa04261;hsa04370;hsa04380;hsa04510;hsa04530;hsa04550;hsa04611;hsa04620;hsa04630;hsa04660;hsa04662;hsa04664;hsa04666;hsa04668;hsa04722;hsa04725;hsa04728;hsa04910;hsa04914;hsa04915;hsa04917;hsa04919;hsa04920;hsa04922;hsa04923;hsa04931;hsa04932;hsa04933;hsa04973;hsa05142;hsa05145;hsa05152;hsa05160;hsa05161;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05205;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05220;hsa05221;hsa05222;hsa05223;hsa05230;hsa05231 AKT1 azure4 1 2.47452229299363 IL7R-mRNA 1.27 0.553 0.187 2.35 0.0256 0.744 JAK-STAT, PI3K NS_CANCERPATH_C2535 IL7R mRNA 0 PI3K;JAK-STAT hsa04060;hsa04068;hsa04151;hsa04630;hsa04640;hsa05340 IL7R azure4 1 2.29656419529837 PIK3CA-mRNA -0.542 0.242 -1.02 -0.0671 0.0296 0.807 CC.PLS.Apop, Driver Gene, JAK-STAT, PI3K, RAS NS_CANCERPATH_C2535 PIK3CA mRNA 0 CC.PLS.Apop;RAS;PI3K;JAK-STAT;Driver Gene hsa00562;hsa04012;hsa04014;hsa04015;hsa04022;hsa04024;hsa04062;hsa04066;hsa04068;hsa04070;hsa04071;hsa04072;hsa04150;hsa04151;hsa04152;hsa04210;hsa04211;hsa04261;hsa04370;hsa04380;hsa04510;hsa04550;hsa04611;hsa04620;hsa04630;hsa04650;hsa04660;hsa04662;hsa04664;hsa04666;hsa04668;hsa04670;hsa04722;hsa04725;hsa04750;hsa04810;hsa04910;hsa04914;hsa04915;hsa04917;hsa04919;hsa04921;hsa04923;hsa04930;hsa04931;hsa04932;hsa04933;hsa04960;hsa04973;hsa05100;hsa05142;hsa05145;hsa05146;hsa05160;hsa05161;hsa05162;hsa05164;hsa05166;hsa05169;hsa05200;hsa05203;hsa05205;hsa05206;hsa05210;hsa05211;hsa05212;hsa05213;hsa05214;hsa05215;hsa05218;hsa05220;hsa05221;hsa05222;hsa05223;hsa05230;hsa05231 PIK3CA azure4 1 -2.2396694214876 PRLR-mRNA 1.03 0.47 0.114 1.96 0.032 0.855 JAK-STAT, PI3K NS_CANCERPATH_C2535 PRLR mRNA 0 PI3K;JAK-STAT hsa04060;hsa04080;hsa04151;hsa04630;hsa04917 PRLR azure4 1 2.19148936170213 STAT3-mRNA 0.448 0.224 0.00905 0.886 0.0507 1 JAK-STAT NS_CANCERPATH_C2535 STAT3 mRNA 0 JAK-STAT hsa04062;hsa04066;hsa04068;hsa04550;hsa04630;hsa04917;hsa04920;hsa04931;hsa04933;hsa05145;hsa05160;hsa05161;hsa05162;hsa05169;hsa05200;hsa05203;hsa05205;hsa05206;hsa05212;hsa05221;hsa05321 STAT3 azure4 1 2 STAT1-mRNA 0.939 0.513 -0.0673 1.94 0.0732 1 JAK-STAT NS_CANCERPATH_C2535 STAT1 mRNA 0 JAK-STAT hsa04062;hsa04380;hsa04620;hsa04630;hsa04917;hsa04919;hsa04933;hsa05140;hsa05145;hsa05152;hsa05160;hsa05161;hsa05162;hsa05164;hsa05168;hsa05200;hsa05212;hsa05321 STAT1 azure4 1 1.83040935672515 DE Results - JAK-STAT genes - SubtypeA
Table displaying each sample's global significance scores and directed global significance scores as defined in the heatmaps above. The global significance score is calculated as the square root of the mean squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis. The directed global significance score is calculated as the square root of the mean signed squared t-statistic for the genes in a gene set, with t-statistics coming from the linear regression underlying our differential expression analysis.
Volcano Plot: SubtypeB
More Plot Information
Volcano Plot: SubtypeB
Volcano plot displaying each gene's -log10(p-value) and log2 fold change for the selected covariate. Highly statistically significant genes fall at the top of the plot, and highly differentially expressed genes fall to either side. Genes within the selected gene set are highlighted in blue. Green point colors and horizontal lines indicate various False Discovery Rate (FDR) thresholds.
DE Results - JAK-STAT genes - SubtypeB
More Plot Information Download CSV DataProbe Label Log2 fold change std error Lower confidence limit Upper confidence limit P-value BY.p.value Gene.sets Codeset.Name Probe.Label Analyte.Type Is.Control Control.Type Probe.Annotation KEGG.Pathways Cell.Type Official.Gene.Name volcanocol volcanopch tstats.all