This is the analysis overview for Firehose run "25 August 2012".
Note: These results are offered to the community as an additional reference point, enabling a wide range of cancer biologists, clinical investigators, and genome and computational scientists to easily incorporate TCGA into the backdrop of ongoing research. While every effort is made to ensure that Firehose input data and algorithms are of the highest possible quality, these analyses have not been reviewed by domain experts.
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Sequence and Copy Number Analyses
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Copy number analysis (GISTIC2)
View Report | There were 575 tumor samples used in this analysis: 24 significant arm-level results, 28 significant focal amplifications, and 47 significant focal deletions were found. -
Mutation Analysis (MutSig)
View Report | MAF used for this analysis: COADREAD.final_analysis_set.maf -
Clustering Analyses
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Clustering of copy number data: consensus NMF
View Report | The most robust consensus NMF clustering of 575 samples using the 75 copy number focal regions 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 Methylation: consensus NMF
View Report | The 6945 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 349 samples and 6945 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 399 samples using the 150 most variable proteins 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 RPPA data: consensus hierarchical
View Report | The 150 most variable proteins were selected. Consensus average linkage hierarchical clustering of 399 samples and 150 proteins 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 mRNA expression: consensus NMF
View Report | The most robust consensus NMF clustering of 224 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 224 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 83 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 83 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 255 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 255 samples and 150 miRs identified 2 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 Analyses
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Correlation between copy number variations of arm-level result and selected clinical features
View Report | Testing the association between copy number variation 78 arm-level results and 11 clinical features across 575 patients, 22 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 75 peak regions and 11 clinical features across 575 patients, 53 significant findings detected with Q value < 0.25. -
Correlation between gene methylation status and clinical features
View Report | Testing the association between 20228 genes and 11 clinical features across 349 samples, statistically thresholded by Q value < 0.05, 9 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 7 different clustering approaches and 11 clinical features across 585 patients, 15 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 538 genes and 10 clinical features across 224 patients, 2 significant findings detected with Q value < 0.25. -
Correlation between RPPA expression and clinical features
View Report | Testing the association between 171 genes and 11 clinical features across 399 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes. -
Correlation between mRNA expression and clinical features
View Report | Testing the association between 17814 genes and 10 clinical features across 224 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one genes. -
Correlation between miRseq expression and clinical features
View Report | Testing the association between 404 genes and 10 clinical features across 255 samples, statistically thresholded by Q value < 0.05, 4 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 -0.0307, 0.0222, 0.0714, 0.1338, 0.204, 0.28, 0.34934, 0.4228, 0.51106, 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 888, 1953, 2596, 3174, 3732, 4279, 4859, 5512, 6310, 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 = 6. Number of gene expression samples = 83. Number of methylation samples = 349. -
Other Analyses
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Association of mutation, copy number alteration, and subtype markers with pathways
View Report | There are 308 genes with significant mutation (Q value <= 0.1) and 490 genes with significant copy number alteration (Q value <= 0.25). The identified marker genes (Q value <= 0.01 or within top 2000) are 2000 for subtype 1, 2000 for subtype 2, 2000 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 54 significant pathways identified in this analysis. -
PARADIGM pathway analysis of mRNA expression and copy number data
View Report | There were 48 significant pathways identified in this analysis.
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Run Prefix = analyses__2012_08_25
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Summary Report Date = Thu Sep 27 11:57:04 2012
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Protection = FALSE