(BRAF_Hotspot_Mutants cohort)
This is the analysis overview for Firehose run "02 May 2013".
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 99 tumor samples used in this analysis: 19 significant arm-level results, 14 significant focal amplifications, and 22 significant focal deletions were found. -
Mutation Analysis (MutSig v1.5)
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Mutation Analysis (MutSig v2.0)
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Mutation Analysis (MutSigCV v0.9)
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Clustering Analyses
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Clustering of copy number data by focal peak region with log2 ratio: consensus NMF
View Report | The most robust consensus NMF clustering of 99 samples using the 36 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 10300 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 99 samples and 10300 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 63 samples using the 175 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 175 most variable proteins were selected. Consensus average linkage hierarchical clustering of 63 samples and 175 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 mRNAseq gene expression: consensus NMF
View Report | The most robust consensus NMF clustering of 99 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 99 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 miRseq precursor expression: consensus NMF
View Report | We filtered the data to 150 most variable miRs. Consensus NMF clustering of 99 samples and 150 miRs 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. -
Correlation Analyses
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Preprocessing of clinical data
View Report | Clinical data for tier 1 clinical variables are generated. -
Correlation between copy number variations of arm-level result and selected clinical features
View Report | Testing the association between copy number variation 70 arm-level results and 8 clinical features across 67 patients, one significant finding detected with Q value < 0.25. -
Correlation between copy number variations of arm-level result and selected clinical features
View Report | Testing the association between copy number variation 70 arm-level results and 8 clinical features across 67 patients, one significant finding detected with Q value < 0.25. -
Correlation between copy number variation genes (focal) and selected clinical features
View Report | Testing the association between copy number variation 36 arm-level results and 8 clinical features across 67 patients, no significant finding detected with Q value < 0.25. -
Correlation between copy number variation genes (focal) and selected clinical features
View Report | Testing the association between copy number variation 36 arm-level results and 8 clinical features across 67 patients, one significant finding detected with Q value < 0.25. -
Correlation between gene methylation status and clinical features
View Report | Testing the association between 17172 genes and 7 clinical features across 64 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes. -
Correlation between gene methylation status and clinical features
View Report | Testing the association between 17172 genes and 7 clinical features across 64 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes. -
Correlation between gene mutation status and selected clinical features
View Report | Testing the association between mutation status of 98 genes and 8 clinical features across 65 patients, no significant finding detected with Q value < 0.25. -
Correlation between gene mutation status and selected clinical features
View Report | Testing the association between mutation status of 98 genes and 8 clinical features across 65 patients, no significant finding detected with Q value < 0.25. -
Correlation between RPPA expression and clinical features
View Report | Testing the association between 175 genes and 7 clinical features across 42 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one genes. -
Correlation between RPPA expression and clinical features
View Report | Testing the association between 175 genes and 7 clinical features across 42 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one genes. -
Correlation between mRNAseq expression and clinical features
View Report | Testing the association between 18144 genes and 7 clinical features across 67 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes. -
Correlation between mRNAseq expression and clinical features
View Report | Testing the association between 18144 genes and 7 clinical features across 67 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 608 genes and 7 clinical features across 67 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one genes. -
Correlation between miRseq expression and clinical features
View Report | Testing the association between 608 genes and 7 clinical features across 67 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one genes. -
Correlations between copy number and mRNAseq expression
View Report | The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are 1008, 1912, 2541, 3129, 3728.5, 4354, 4986.7, 5652, 6403, 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 = 99. Number of gene expression samples = 99. Number of methylation samples = 99. -
Pathway Analyses
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PARADIGM pathway analysis of mRNASeq expression data
View Report | There were 57 significant pathways identified in this analysis. -
PARADIGM pathway analysis of mRNASeq expression and copy number data
View Report | There were 57 significant pathways identified in this analysis.
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Run Prefix = awg_skcm__2013_05_02
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Summary Report Date = Mon May 13 16:21:44 2013
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Protection = FALSE