Mutation Assessor - Pancreatic Adenocarcinoma (Primary solid tumor)

Mutation Assessor

Pancreatic Adenocarcinoma (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/C1WD3ZBG

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: 848
Medium Functional Impact Missense Mutations: 5316
Low Functional Impact Missense Mutations: 5296
Neutral Functional Impact Mutations: 3804

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
KRAS	1	31	0	0	3.2450	medium	medium
TP53	2	15	0	0	3.1700	medium	medium
C19orf55	3	1	0	1	0.9975	low	medium/neutral
CDKN2A	6	0	2	0	0.8050	low	low
NFIL3	7	0	1	0	1.5000	low	low
OTOF	8	2	1	0	2.2050	medium	medium
IRS1	9	0	0	1	0.6900	neutral	neutral
GAS2L2	10	0	3	0	1.6100	low	low
APP	12	1	0	1	1.2600	low	medium/neutral
THBS4	17	0	0	1	0.1700	neutral	neutral

Methods & Data

Input

PAAD-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 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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