Analysis Overview for PANCANCER
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 April 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

  • Clustering Analyses

    • 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.

  • 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 -0.00404, 0.04782, 0.104, 0.17178, 0.2493, 0.3319, 0.40534, 0.47608, 0.55744, 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 -0.0365, -0.0124, 0.0053, 0.0249, 0.0542, 0.0968, 0.1851, 0.2803, 0.4009, respectively.

  • Other Analyses

    • 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.

Methods & Data
Input

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

  • Run Prefix = analyses__2012_04_25

  • Summary Report Date = Thu May 24 07:44:55 2012

  • Protection = FALSE

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