Analysis Overview
Mesothelioma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1668CN3
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Analysis Overview for Mesothelioma (Primary solid tumor cohort) - 28 January 2016. Broad Institute of MIT and Harvard. doi:10.7908/C1668CN3
Overview
Introduction

This is an overview of Mesothelioma analysis pipelines from Firehose run "28 January 2016".

Summary

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.

Results

  • Sequence and Copy Number Analyses

    • SNP6 Copy number analysis (GISTIC2)
      View Report | There were 87 tumor samples used in this analysis: 21 significant arm-level results, 0 significant focal amplifications, and 21 significant focal deletions were found.

  • Correlations to Clinical Parameters

    • Correlation between aggregated 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 87 patients, 18 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 21 focal events and 11 clinical features across 87 patients, 15 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 72 arm-level events and 11 clinical features across 87 patients, 3 significant findings detected with Q value < 0.25.

    • Correlation between gene methylation status and clinical features
      View Report | Testing the association between 16998 genes and 11 clinical features across 87 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 5 clinical features related to at least one genes.

    • Correlation between miRseq expression and clinical features
      View Report | Testing the association between 519 miRs and 11 clinical features across 87 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 4 clinical features related to at least one miRs.

    • Correlation between mRNAseq expression and clinical features
      View Report | Testing the association between 18209 genes and 11 clinical features across 87 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 5 clinical features related to at least one genes.

    • Correlation between RPPA expression and clinical features
      View Report | Testing the association between 193 genes and 10 clinical features across 63 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 3 clinical features related to at least one genes.

  • Clustering Analyses

    • Clustering of copy number data by focal peak region with absolute value: consensus NMF
      View Report | The most robust consensus NMF clustering of 87 samples using the 21 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 copy number data by peak region with threshold value: consensus NMF
      View Report | The most robust consensus NMF clustering of 87 samples using the 21 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 most robust consensus NMF clustering of 87 samples using the 5165 most variable genes was identified for k = 5 clusters. We computed the clustering for k = 2 to k = 10 and uused the cophenetic correlation coefficient and the average silhouette width calculation to determine the robust clusters.

    • Clustering of miRseq mature expression: consensus hierarchical
      View Report | Median absolute deviation (MAD) was used to select 647 most variable miRs. Consensus ward linkage hierarchical clustering of 85 samples and 647 miRs identified 4 subtypes with the stability of the clustering increasing for k = 2 to k = 10.

    • Clustering of miRseq mature expression: consensus NMF
      View Report | The most robust consensus NMF clustering of 85 samples using the 647 most variable miRs was identified for k = 3 clusters. We computed the clustering for k = 2 to k = 10 and uused the cophenetic correlation coefficient and the average silhouette width calculation to determine the robust clusters.

    • Clustering of miRseq precursor expression: consensus hierarchical
      View Report | Median absolute deviation (MAD) was used to select 129 most variable miRs. Consensus ward linkage hierarchical clustering of 87 samples and 129 miRs identified 5 subtypes with the stability of the clustering increasing for k = 2 to k = 10.

    • Clustering of miRseq precursor expression: consensus NMF
      View Report | The most robust consensus NMF clustering of 87 samples using the 150 most variable miRs was identified for k = 4 clusters. We computed the clustering for k = 2 to k = 10 and uused the cophenetic correlation coefficient and the average silhouette width calculation to determine 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 87 samples and 1500 genes identified 5 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 87 samples using the 1500 most variable genes was identified for k = 4 clusters. We computed the clustering for k = 2 to k = 10 and uused the cophenetic correlation coefficient and the average silhouette width calculation to determine the robust clusters.

    • Clustering of RPPA data: consensus hierarchical
      View Report | Median absolute deviation (MAD) was used to select 193 most variable proteins. Consensus ward linkage hierarchical clustering of 63 samples and 193 proteins identified 6 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 63 samples using the 193 most variable proteins was identified for k = 4 clusters. We computed the clustering for k = 2 to k = 10 and uused the cophenetic correlation coefficient and the average silhouette width calculation to determine the robust clusters.

  • Other Analyses

    • Aggregate Analysis Features
      View Report

    • Identification of putative miR direct targets by sequencing data
      View Report | The CLR algorithm was applied on 756 miRs and 18209 mRNAs across 87 samples. After 2 filtering steps, the number of 98 miR:genes pairs were detected.

  • Pathway Analyses

    • GSEA Class2: Canonical Pathways enriched in each subtypes of mRNAseq_cNMF in MESO-TP
      View Report | basic data info

    • PARADIGM pathway analysis of mRNASeq expression and copy number data
      View Report | There were 46 significant pathways identified in this analysis.

    • PARADIGM pathway analysis of mRNASeq expression data
      View Report | There were 50 significant pathways identified in this analysis.

  • Other Correlation Analyses

    • Correlation between copy number variation genes (focal events) and molecular subtypes
      View Report | Testing the association between copy number variation 21 focal events and 10 molecular subtypes across 87 patients, 61 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 72 arm-level events and 10 molecular subtypes across 87 patients, 43 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 = 87. Number of gene expression samples = 87. Number of methylation samples = 87.

    • Correlations between copy number and mRNAseq expression
      View Report | The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are 931, 1820.2, 2457, 3063, 3668, 4271, 4892.2, 5546.8, 6270.4, respectively.

Methods & Data
Input

  • Summary Report Date = Thu Apr 7 17:58:21 2016

  • Protection = FALSE

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