Copy number analysis (GISTIC2)
View Report | There were 492 tumor samples used in this analysis: 30 significant arm-level results, 48 significant focal amplifications, and 49 significant focal deletions were found.

Mutation Analysis (MutSig v2.0)
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Mutation Analysis (MutSig vS2N)
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Clustering of copy number data: consensus NMF
View Report | The most robust consensus NMF clustering of 492 samples using the 98 copy number focal regions was identified for k = 5 clusters. We computed the clustering for k = 2 to k = 8 and used the cophenetic correlation coefficient to determine the best solution.

Clustering of Methylation: consensus NMF
View Report | The 9700 most variable methylated genes were selected based on variation. The variation cutoff are set for each tumor type empirically by fitting a bimodal distriution. For genes with multiple methylation probes, we chose the most variable one to represent the gene. Consensus NMF clustering of 383 samples and 9700 genes identified 3 subtypes with the stability of the clustering increasing for k = 2 to k = 8 and the average silhouette width calculation for selecting the robust clusters.

Clustering of RPPA data: consensus NMF
View Report | The most robust consensus NMF clustering of 200 samples using the 150 most variable proteins was identified for k = 6 clusters. We computed the clustering for k = 2 to k = 8 and used the cophenetic correlation coefficient to determine the best solution.

Clustering of RPPA data: consensus hierarchical
View Report | The 150 most variable proteins were selected. Consensus average linkage hierarchical clustering of 200 samples and 150 proteins identified 6 subtypes with the stability of the clustering increasing for k = 2 to k = 8 and the average silhouette width calculation for selecting the robust clusters.

Clustering of mRNA expression: consensus NMF
View Report | The most robust consensus NMF clustering of 54 samples using the 1500 most variable genes was identified for k = 4 clusters. We computed the clustering for k = 2 to k = 8 and used the cophenetic correlation coefficient to determine the best solution.

Clustering of mRNA expression: consensus hierarchical
View Report | The 1500 most variable genes were selected. Consensus average linkage hierarchical clustering of 54 samples and 1500 genes identified 3 subtypes with the stability of the clustering increasing for k = 2 to k = 8 and the average silhouette width calculation for selecting the robust clusters.

Clustering of mRNAseq gene expression: consensus NMF
View Report | The most robust consensus NMF clustering of 333 samples using the 1500 most variable genes was identified for k = 4 clusters. We computed the clustering for k = 2 to k = 8 and used the cophenetic correlation coefficient to determine the best solution.

Clustering of mRNAseq gene expression: consensus hierarchical
View Report | The 1500 most variable genes were selected. Consensus average linkage hierarchical clustering of 333 samples and 1500 genes identified 4 subtypes with the stability of the clustering increasing for k = 2 to k = 8 and the average silhouette width calculation for selecting the robust clusters.

Clustering of miRseq expression: consensus NMF
View Report | We filtered the data to 150 most variable miRs. Consensus NMF clustering of 485 samples and 150 miRs identified 3 subtypes with the stability of the clustering increasing for k = 2 to k = 8 and the average silhouette width calculation for selecting the robust clusters.

Clustering of miRseq expression: consensus hierarchical
View Report | We filtered the data to 150 most variable miRs. Consensus average linkage hierarchical clustering of 485 samples and 150 miRs identified 3 subtypes with the stability of the clustering increasing for k = 2 to k = 8 and the average silhouette width calculation for selecting the robust clusters.

Correlation between copy number variations of arm-level result and selected clinical features
View Report | Testing the association between copy number variation 79 arm-level results and 5 clinical features across 443 patients, 49 significant findings detected with Q value < 0.25.

Correlation between copy number variation genes and selected clinical features
View Report | Testing the association between copy number variation of 98 peak regions and 5 clinical features across 443 patients, 159 significant findings detected with Q value < 0.25.

Correlation between gene methylation status and clinical features
View Report | Testing the association between 17584 genes and 5 clinical features across 220 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.

Correlation between molecular cancer subtypes and selected clinical features
View Report | Testing the association between subtypes identified by 10 different clustering approaches and 5 clinical features across 451 patients, 32 significant findings detected with P value < 0.05.

Correlation between gene mutation status and selected clinical features
View Report | Testing the association between mutation status of 123 genes and 5 clinical features across 248 patients, 9 significant findings detected with Q value < 0.25.

Correlation between RPPA expression and clinical features
View Report | Testing the association between 166 genes and 5 clinical features across 200 samples, statistically thresholded by Q value < 0.05, 2 clinical features related to at least one genes.

Correlation between mRNA expression and clinical features
View Report | Testing the association between 17814 genes and 5 clinical features across 54 samples, statistically thresholded by Q value < 0.05, 1 clinical feature related to at least one genes.

Correlation between mRNAseq expression and clinical features
View Report | Testing the association between 18585 genes and 5 clinical features across 333 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.

Correlation between miRseq expression and clinical features
View Report | Testing the association between 564 genes and 5 clinical features across 436 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes.

Correlations between copy number and mRNA expression
View Report | The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are -0.10414, -0.0138, 0.0519, 0.11058, 0.1705, 0.23282, 0.2964, 0.3696, 0.46436, respectively.

Correlations between copy number and mRNAseq expression
View Report | The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are 978.1, 1595.2, 2049, 2500.4, 3008.5, 3531, 4085, 4692, 5429.9, respectively.

Correlation between mRNA expression and DNA methylation
View Report | The top 25 correlated methylation probes per gene are displayed. Total number of matched samples = 221. Number of gene expression samples = 333. Number of methylation samples = 221.

Association of mutation, copy number alteration, and subtype markers with pathways
View Report | There are 62 genes with significant mutation (Q value <= 0.1) and 330 genes with significant copy number alteration (Q value <= 0.25). The identified marker genes (Q value <= 0.01 or within top 2000) are 921 for subtype 1, 921 for subtype 2, 921 for subtype 3. Pathways significantly enriched with these genes (Q value <= 0.01) are identified :

PARADIGM pathway analysis of mRNA expression data
View Report | There were 59 significant pathways identified in this analysis.

PARADIGM pathway analysis of mRNA expression and copy number data
View Report | There were 36 significant pathways identified in this analysis.