Analysis Overview
Mesothelioma (Primary solid tumor)
02 April 2015 | analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1CV4GT5
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Analysis Overview for Mesothelioma (Primary solid tumor cohort) - 02 April 2015. Broad Institute of MIT and Harvard. doi:10.7908/C1CV4GT5
Overview
Introduction

This is an overview of Mesothelioma analysis pipelines from Firehose run "02 April 2015".

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 8 different clustering approaches and 8 clinical features across 77 patients, 9 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 8 clinical features across 77 patients, 3 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 73 arm-level events and 8 clinical features across 77 patients, no significant finding detected with Q value < 0.25.

- Correlation between gene methylation status and clinical features
  View Report | Testing the association between 20103 genes and 8 clinical features across 77 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 2 clinical features related to at least one genes.

- Correlation between miRseq expression and clinical features
  View Report | Testing the association between 519 miRs and 8 clinical features across 77 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 3 clinical features related to at least one miRs.

- Correlation between mRNAseq expression and clinical features
  View Report | Testing the association between 18203 genes and 8 clinical features across 77 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 4 clinical features related to at least one genes.

- Clustering Analyses

- Clustering of copy number data by focal peak region with log2 ratio: 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 5586 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 87 samples and 5586 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 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 | We filtered the data to 647 most variable miRs. Consensus NMF clustering of 85 samples and 647 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 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 | We filtered the data to 150 most variable miRs. Consensus NMF clustering of 87 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 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 86 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 86 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.

- Other Analyses

- Identification of putative miR direct targets by sequencing data
  View Report | The CLR algorithm was applied on 756 miRs and 18203 mRNAs across 86 samples. After 2 filtering steps, the number of 64 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 49 significant pathways identified in this analysis.

- PARADIGM pathway analysis of mRNASeq expression data
  View Report | There were 54 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 8 molecular subtypes across 87 patients, 52 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 74 arm-level events and 8 molecular subtypes across 87 patients, 50 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 = 86. Number of gene expression samples = 86. 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 924.1, 1804, 2444, 3036.4, 3653.5, 4250, 4870.7, 5539, 6281.9, respectively.

Methods & Data
Input

- Summary Report Date = Sat Aug 15 14:25:23 2015

- Protection = FALSE

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