Mutation Assessor - Pancreatic Adenocarcinoma (Primary solid tumor)

Mutation Assessor

Pancreatic Adenocarcinoma (Primary solid tumor)

16 April 2014 | analyses__2014_04_16

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/C1P26WS9

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: 970
Medium Functional Impact Missense Mutations: 6042
Low Functional Impact Missense Mutations: 5995
Neutral Functional Impact Mutations: 4389

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	Medium Functional Impact Count	Low Functional Impact Count	Neutral Functional Impact Count	Median Functional Impact Score	Median Functional Impact Level	Mode Functional Impact Level
DHX9	3	1	0	0	2.5100	medium	medium
AFTPH	5	0	0	2	0.5500	neutral	neutral
APP	6	1	0	1	1.2600	low	medium/neutral
TMC4	7	0	0	1	0.2550	neutral	neutral
BRDT	9	0	1	0	1.6100	low	low
IRS1	12	0	0	1	0.6900	neutral	neutral
PDILT	15	0	1	0	1.8450	low	low
CUX2	16	1	3	0	1.1725	low	low
TAOK2	18	0	2	1	1.0400	low	low
SORBS2	19	0	1	1	0.6150	neutral	low/neutral

Methods & Data

Input

PAAD-TP.maf.annotated
PAAD-TP.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 PAAD-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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