Mutation Assessor
Uterine Carcinosarcoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Assessor. Broad Institute of MIT and Harvard. doi:10.7908/C1ZK5FHM
Overview
Introduction

This report serves to summarize the functional impact of missense mutations in each gene as determined by Mutation Assessor[1].

Summary
  • High Functional Impact Missense Mutations: 341

  • Medium Functional Impact Missense Mutations: 1976

  • Low Functional Impact Missense Mutations: 1849

  • Neutral Functional Impact Mutations: 1392

Results
Functional Impact by Gene

Table 1.  Get Full Table A gene-level breakdown of missense mutation functional impact, ordered by MutSig rank. Includes missense mutation counts broken down by level of functional impact (high, medium, low, neutral), median functional impact score and level, and most common level(s) of functional impact (mode) per gene.

Gene MutSig
Rank
High
Functional Impact
Count
Medium
Functional Impact
Count
Low
Functional Impact
Count
Neutral
Functional Impact
Count
Median
Functional Impact
Score
Median
Functional Impact
Level
Mode
Functional Impact
Level
TP53 1 0 42 0 0 3.1125 medium medium
FBXW7 2 4 10 3 5 2.1650 medium medium
PPP2R1A 3 11 5 1 0 3.5500 high high
PTEN 4 6 3 0 0 3.5750 high high
KRAS 5 0 7 0 0 3.1350 medium medium
ZBTB7B 6 0 2 2 0 1.7400 low medium/low
CHD4 7 5 3 1 0 3.5450 high high
PIK3R1 8 0 1 0 0 2.4750 medium medium
ARHGAP35 9 0 1 0 0 2.1200 medium medium
PIK3CA 10 0 9 7 6 1.6200 low medium
Methods & Data
Input
  1. UCS-TP.maf.annotated

  2. sig_genes.txt

  3. Mutation Assessor Scores Release 2:

A lookup is done against the relevant Mutation Assessor Scores table for each missense mutation in a given MAF file, and available functional impact score and level are appended as two new columns to generate UCS-TP.maf.annotated. These are summarized in Table 1, sorted by MutSig rank.

Download Results

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

References
[1] Boris Reva, Yevgeniy Antipin, and Chris Sander, Predicting the functional impact of protein mutations: application to cancer genomics, Nucl. Acids Res. 39(17):e118 (2011)