Mutation Assessor - Colon Adenocarcinoma (Primary solid tumor)

Mutation Assessor

Colon Adenocarcinoma (Primary solid tumor)

28 January 2016 | analyses__2016_01_28

Maintainer Information

Citation Information

Maintained by David Heiman (Broad Institute)

Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Mutation Assessor. Broad Institute of MIT and Harvard. doi:10.7908/C1154GDS

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: 6558
Medium Functional Impact Missense Mutations: 37473
Low Functional Impact Missense Mutations: 35967
Neutral Functional Impact Mutations: 25796

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.

MutSig Rank	Gene	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
1	APC	0	45	145	77	1.0600	low	low
2	TP53	0	217	26	15	2.9325	medium	medium
3	ARID1A	0	19	16	8	1.5900	low	medium
4	RNF43	0	1	7	7	0.8950	low	low/neutral
5	SOX9	4	2	0	1	3.5850	high	high
7	TXNDC2	0	0	2	3	0.7500	neutral	neutral
8	ACVR1B	6	3	8	4	1.7650	low	low
9	B2M	1	3	2	0	2.3900	medium	medium
11	CDH1	12	21	18	12	1.9600	medium	medium
12	MLH1	9	22	1	4	2.8900	medium	medium

Methods & Data

Input

COAD-TP.maf.annotated
sig_genes.txt
Mutation Assessor Scores Release 2:

hg18
hg19

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 COAD-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)

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