This is an overview of Prostate Adenocarcinoma analysis pipelines from Firehose run "15 July 2014".
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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LowPass Copy number analysis (GISTIC2)
View Report | There were 115 tumor samples used in this analysis: 16 significant arm-level results, 4 significant focal amplifications, and 16 significant focal deletions were found. -
Mutation Analysis (MutSig 2CV v3.1)
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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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Mutation Assessor
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SNP6 Copy number analysis (GISTIC2)
View Report | There were 419 tumor samples used in this analysis: 22 significant arm-level results, 29 significant focal amplifications, and 33 significant focal deletions were found. -
Correlations to Clinical Parameters
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Correlation between aggregated molecular cancer subtypes and selected clinical features
View Report | Testing the association between subtypes identified by 10 different clustering approaches and 13 clinical features across 274 patients, 28 significant findings detected with P value < 0.05 and Q value < 0.25. -
Correlation between copy number variation genes (focal events) and selected clinical features
View Report | Testing the association between copy number variation 62 focal events and 13 clinical features across 271 patients, 31 significant findings 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 64 arm-level events and 13 clinical features across 271 patients, 34 significant findings detected with Q value < 0.25. -
Correlation between gene methylation status and clinical features
View Report | Testing the association between 20041 genes and 13 clinical features across 265 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 9 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 34 genes and 13 clinical features across 247 patients, 2 significant findings detected with Q value < 0.25. -
Correlation between miRseq expression and clinical features
View Report | Testing the association between 471 miRs and 13 clinical features across 272 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 10 clinical features related to at least one miRs. -
Correlation between mRNAseq expression and clinical features
View Report | Testing the association between 18250 genes and 13 clinical features across 268 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 10 clinical features related to at least one genes. -
Correlation between mutation rate and clinical features
View Report | Testing the association between 2 variables and 14 clinical features across 247 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 7 clinical features related to at least one variables. -
Correlation between RPPA expression and clinical features
View Report | Testing the association between 189 genes and 12 clinical features across 158 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 9 clinical features related to at least one genes. -
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 419 samples using the 62 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 copy number data by peak region with threshold value: consensus NMF
View Report | The most robust consensus NMF clustering of 419 samples using the 62 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 3635 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 336 samples and 3635 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 mature expression: consensus hierarchical
View Report | Median absolute deviation (MAD) was used to select 246 most variable miRs. Consensus ward linkage hierarchical clustering of 421 samples and 246 miRs identified 5 subtypes with the stability of the clustering increasing for k = 2 to k = 10. -
Clustering of miRseq mature expression: consensus NMF
View Report | We filtered the data to 246 most variable miRs. Consensus NMF clustering of 421 samples and 246 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 precursor expression: consensus hierarchical
View Report | Median absolute deviation (MAD) was used to select 117 most variable miRs. Consensus ward linkage hierarchical clustering of 421 samples and 117 miRs identified 3 subtypes with the stability of the clustering increasing for k = 2 to k = 10. -
Clustering of miRseq precursor expression: consensus NMF
View Report | We filtered the data to 150 most variable miRs. Consensus NMF clustering of 421 samples and 150 miRs identified 5 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 hierarchical
View Report | Median absolute deviation (MAD) was used to select 1500 most variable genes. Consensus ward linkage hierarchical clustering of 374 samples and 1500 genes identified 3 subtypes with the stability of the clustering increasing for k = 2 to k = 10. -
Clustering of mRNAseq gene expression: consensus NMF
View Report | The most robust consensus NMF clustering of 374 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 RPPA data: consensus hierarchical
View Report | Median absolute deviation (MAD) was used to select 189 most variable proteins. Consensus ward linkage hierarchical clustering of 164 samples and 189 proteins identified 3 subtypes with the stability of the clustering increasing for k = 2 to k = 10. -
Clustering of RPPA data: consensus NMF
View Report | The most robust consensus NMF clustering of 164 samples using 189 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. -
Pathway Analyses
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PARADIGM pathway analysis of mRNASeq expression and copy number data
View Report | There were 52 significant pathways identified in this analysis. -
PARADIGM pathway analysis of mRNASeq expression data
View Report | There were 51 significant pathways identified in this analysis. -
Other Correlation Analyses
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Correlation between copy number variation genes (focal events) and molecular subtypes
View Report | Testing the association between copy number variation 62 focal events and 10 molecular subtypes across 419 patients, 146 significant findings detected with P value < 0.05 and Q value < 0.25. -
Correlation between copy number variations of arm-level result and molecular subtypes
View Report | Testing the association between copy number variation 77 arm-level events and 10 molecular subtypes across 419 patients, 66 significant findings detected with P value < 0.05 and Q value < 0.25. -
Correlation between gene mutation status and molecular subtypes
View Report | Testing the association between mutation status of 38 genes and 10 molecular subtypes across 261 patients, 7 significant findings detected with P value < 0.05 and Q value < 0.25. -
Correlation between mRNA expression and DNA methylation
View Report | The top 25 correlated methylation probes per gene are displayed. Total number of matched samples = 333. Number of gene expression samples = 374. Number of methylation samples = 336. -
Correlations between copy number and mRNAseq expression
View Report | The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are 668, 1422, 1807, 2175, 2572, 2991, 3492, 4093, 4934, respectively.
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Summary Report Date = Tue Sep 16 18:41:12 2014
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Protection = FALSE