Mutation Assessor - Pancreatic Adenocarcinoma (Primary solid tumor)

Mutation Assessor

Pancreatic Adenocarcinoma (Primary solid tumor)

02 April 2015 | analyses__2015_04_02

Maintainer Information

Citation Information

Maintained by David Heiman (Broad Institute)

Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Mutation Assessor. Broad Institute of MIT and Harvard. doi:10.7908/C1K35SRN

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: 1159
Medium Functional Impact Missense Mutations: 7113
Low Functional Impact Missense Mutations: 6851
Neutral Functional Impact Mutations: 4998

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
KRAS	1	0	125	1	0	3.1575	medium	medium
TP53	2	0	65	1	1	3.0750	medium	medium
RIOK1	4	0	1	0	0	3.2100	medium	medium
CDKN2A	7	1	2	5	0	0.8050	low	low
AEBP1	8	0	0	0	2	0.6225	neutral	neutral
RBM47	9	0	2	0	0	1.9750	medium	medium
RFX1	11	0	1	0	0	2.7800	medium	medium
SMAD4	13	2	12	0	0	3.3675	medium	medium
GPR6	14	0	1	0	0	2.7550	medium	medium
LZTS1	15	0	0	1	1	0.9975	low	low/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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