Mutation Assessor - Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (Primary solid tumor)

Mutation Assessor

Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (Primary solid tumor)

15 January 2014 | analyses__2014_01_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/C1D50KCG

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: 260
Medium Functional Impact Missense Mutations: 1750
Low Functional Impact Missense Mutations: 1925
Neutral Functional Impact Mutations: 1437

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
PIK3CA	1	0	1	10	0	1.620	low	low
PRSS48	2	2	2	0	8	0.030	neutral	neutral
UGT2B10	3	0	1	1	0	1.825	low	medium/low
TMCC1	4	0	0	0	1	0.000	neutral	neutral
UGT3A2	5	1	0	0	0	4.100	high	high
MAPK1	6	3	0	0	0	4.220	high	high
PRB2	7	0	0	1	0	1.100	low	low
OR10G8	9	0	0	3	11	-1.705	neutral	neutral
NFE2L2	11	0	5	0	0	2.865	medium	medium
ITGAX	12	0	4	0	1	2.320	medium	medium

Methods & Data

Input

CESC-TP.maf.annotated
CESC-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 CESC-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)

Made with Nozzle