Mutation Assessor - Pancreatic Adenocarcinoma (Primary solid tumor)

Mutation Assessor

Pancreatic Adenocarcinoma (Primary solid tumor)

Due to issues with GAF 3.0, we strongly advise caution in the use of these results.

23 September 2013 | analyses__2013_09_23

Maintainer Information

Citation Information

Maintained by David Heiman (Broad Institute)

Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Mutation Assessor. Broad Institute of MIT and Harvard. doi:10.7908/C1PK0DHT

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: 752
Medium Functional Impact Missense Mutations: 4782
Low Functional Impact Missense Mutations: 4749
Neutral Functional Impact Mutations: 3444

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
NOS1AP	5	0	0	1	0.285	neutral	neutral
TCF20	16	0	0	2	0.520	neutral	neutral
LRP10	17	0	1	0	1.390	low	low
ADAMTSL4	26	1	0	0	2.775	medium	medium
HOXA1	28	0	1	0	1.770	low	low
FXR2	34	0	0	1	0.345	neutral	neutral
INTS10	39	0	1	0	1.155	low	low
PASD1	40	0	0	1	0.550	neutral	neutral
ADAD1	42	1	0	0	2.555	medium	medium
RBM25	43	0	0	1	0.550	neutral	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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