This is the analysis overview for Firehose run "13 September 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 303 tumor samples used in this analysis: 26 significant arm-level results, 28 significant focal amplifications, and 42 significant focal deletions were found. -
Mutation Analysis (MutSig)
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Mutation Analysis (MutSig)
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Clustering Analyses
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Clustering of copy number data: consensus NMF
View Report | The most robust consensus NMF clustering of 303 samples using the 70 copy number focal regions was identified for k = 3 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 4403 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 220 samples and 4403 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 RPPA data: consensus NMF
View Report | The most robust consensus NMF clustering of 237 samples using the 150 most variable proteins was identified for k = 3 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 237 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 32 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 32 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 263 samples using the 1500 most variable genes was identified for k = 3 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 263 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 345 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 345 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 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 79 arm-level results and 11 clinical features across 287 patients, 3 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 70 peak regions and 11 clinical features across 287 patients, 5 significant findings detected with Q value < 0.25. -
Correlation between gene methylation status and clinical features
View Report | Testing the association between 17374 genes and 11 clinical features across 194 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 10 different clustering approaches and 11 clinical features across 292 patients, 16 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 279 genes and 11 clinical features across 172 patients, 8 significant findings detected with Q value < 0.25. -
Correlation between RPPA expression and clinical features
View Report | Testing the association between 174 genes and 11 clinical features across 229 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes. -
Correlation between mRNA expression and clinical features
View Report | Testing the association between 17814 genes and 8 clinical features across 32 samples, statistically thresholded by Q value < 0.05, 2 clinical features related to at least one genes. -
Correlation between mRNAseq expression and clinical features
View Report | Testing the association between 18286 genes and 11 clinical features across 263 samples, statistically thresholded by Q value < 0.05, 7 clinical features related to at least one genes. -
Correlation between miRseq expression and clinical features
View Report | Testing the association between 539 genes and 11 clinical features across 284 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 -0.12546, -0.0186, 0.0605, 0.1312, 0.1987, 0.26944, 0.34298, 0.42, 0.5197, 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 1002.5, 1728, 2311, 2887, 3491, 4127, 4785, 5453, 6225, 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 = 194. Number of gene expression samples = 263. Number of methylation samples = 194. -
Other Analyses
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Association of mutation, copy number alteration, and subtype markers with pathways
View Report | There are 161 genes with significant mutation (Q value <= 0.1) and 448 genes with significant copy number alteration (Q value <= 0.25). The identified marker genes (Q value <= 0.01 or within top 2000) are 19 for subtype 1, 19 for subtype 2, 19 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 41 significant pathways identified in this analysis. -
PARADIGM pathway analysis of mRNA expression and copy number data
View Report | There were 39 significant pathways identified in this analysis.
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Run Prefix = analyses__2012_09_13
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Summary Report Date = Mon Oct 29 23:05:11 2012
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Protection = FALSE