Analysis Overview for Ovarian Serous Cystadenocarcinoma
Maintained by TCGA GDAC Team (Broad Institute/Dana-Farber Cancer Institute/Harvard Medical School)
Overview
Introduction

This is the analysis overview for Firehose run "25 May 2012".

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

    • Mutation Analysis (MutSig)
      View Report | Significantly mutated genes (q ≤ 0.1): 24

    • Copy number analysis (GISTIC2)
      View Report | There were 558 tumor samples used in this analysis: 29 significant arm-level results, 34 significant focal amplifications, and 47 significant focal deletions were found.

  • Clustering Analyses

    • Clustering of mRNA expression: consensus NMF
      View Report | The most robust consensus NMF clustering of 565 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 mRNA expression: consensus hierarchical
      View Report | The 1500 most variable genes were selected. Consensus average linkage hierarchical clustering of 565 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 Methylation: consensus NMF
      View Report | The 1229 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 551 samples and 1229 genes identified 6 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 miR expression: consensus NMF
      View Report | We filtered the data to 150 most variable miRs. Consensus NMF clustering of 564 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 miR expression: consensus hierarchical
      View Report | We filtered the data to 150 most variable miRs. Consensus average linkage hierarchical clustering of 564 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 NMF
      View Report | We filtered the data to 150 most variable miRs. Consensus NMF clustering of 46 samples and 150 miRs identified 2 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 46 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.

  • Correlation Analyses

    • Correlations between copy number and mRNA expression
      View Report | The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are 0.00656, 0.0587, 0.11676, 0.19694, 0.2852, 0.373, 0.44306, 0.5089, 0.5796, respectively.

    • Correlations between copy number and miR expression
      View Report | The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are -0.03896, -0.01806, 0.00264, 0.02156, 0.0455, 0.09396, 0.18182, 0.27824, 0.3735, respectively.

    • Correlation between mRNA expression and DNA methylation
      View Report | The top 25 correlated methylation probe(s) per gene are displayed. Total number of matched samples = 549 Number of gene expression samples = 553 Number of methylation samples = 565

  • Other Analyses

    • Clustering of RPPA data: consensus hierarchical
      View Report | The 150 most variable proteins were selected. Consensus average linkage hierarchical clustering of 412 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 RPPA data: consensus NMF
      View Report | The most robust consensus NMF clustering of 412 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.

    • Correlation between mRNA expression and clinical features
      View Report | Testing the association between 18632 genes and 6 clinical features across 564 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes.

    • Correlation between miR expression and clinical features
      View Report | Testing the association between 817 miRs and 6 clinical features across 562 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one miRs.

    • Correlation between molecular cancer subtypes and selected clinical features
      View Report | Testing the association between subtypes identified by 7 different clustering approaches and 6 clinical features across 566 patients, 7 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 57 genes and 4 clinical features across 316 patients, no significant finding detected with Q value < 0.25.

    • Identification of putative miR direct targets
      View Report | This pipeline use a relevance network approach to infer putative miR:mRNA regulatory connections. All miR:mRNA pairs that have correlations < -0.3 and have predicted interactions in three sequence prediction databases (Miranda, Pictar, Targetscan) define the final network.

    • Association of mutation, copy number alteration, and subtype markers with pathways
      View Report | There are 20 genes with significant mutation (Q value <= 0.1) and 258 genes with significant copy number alteration (Q value <= 0.25). The identified marker genes (Q value <= 0.01 or within top 2000) are 2000 for subtype 1, 2000 for subtype 2, 2000 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 70 significant pathways identified in this analysis.

    • PARADIGM pathway analysis of mRNA expression and copy number data
      View Report | There were 108 significant pathways identified in this analysis.

Methods & Data
Input

  • Firehose Directory = /local/cga-fh/tcga-gdac

  • Run Prefix = analyses__2012_05_25

  • Summary Report Date = Sat Jun 16 13:19:11 2012

  • Protection = FALSE

Copyright © 2011 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle