Sensitive and specific post-call filtering of genetic variants in xenograft and primary tumors
AffiliationUniv Arizona, Dept Epidemiol & Biostat, Mel & Enid Zuckerman Coll Publ Hlth
Univ Arizona, Ctr Canc
Univ Arizona, Dept Med
Univ Arizona, Dept Pathol
Univ Arizona, Dept Mol & Cellular Biol
MetadataShow full item record
PublisherOXFORD UNIV PRESS
CitationBrian K Mannakee, Uthra Balaji, Agnieszka K Witkiewicz, Ryan N Gutenkunst, Erik S Knudsen; Sensitive and specific post-call filtering of genetic variants in xenograft and primary tumors, Bioinformatics, Volume 34, Issue 10, 15 May 2018, Pages 1713–1718, https://doi.org/10.1093/bioinformatics/bty010
Rights© The Author(s) 2018. Published by Oxford University Press. All rights reserved.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at firstname.lastname@example.org.
AbstractMotivation: Tumor genome sequencing offers great promise for guiding research and therapy, but spurious variant calls can arise from multiple sources. Mouse contamination can generate many spurious calls when sequencing patient-derived xenografts. Paralogous genome sequences can also generate spurious calls when sequencing any tumor. We developed a BLAST-based algorithm, Mouse And Paralog EXterminator (MAPEX), to identify and filter out spurious calls from both these sources. Results: When calling variants from xenografts, MAPEX has similar sensitivity and specificity to more complex algorithms. When applied to any tumor, MAPEX also automatically flags calls that potentially arise from paralogous sequences. Our implementation, mapexr, runs quickly and easily on a desktop computer. MAPEX is thus a useful addition to almost any pipeline for calling genetic variants in tumors.
Note12 month embargo; published online: 08 January 2018
VersionFinal accepted manuscript
SponsorsNational Science Foundation [DGE-1143953]; National Institutes of Health [R01CA211878-01, P30CA023074-36S2]
- Consensus Genotyper for Exome Sequencing (CGES): improving the quality of exome variant genotypes.
- Authors: Trubetskoy V, Rodriguez A, Dave U, Campbell N, Crawford EL, Cook EH, Sutcliffe JS, Foster I, Madduri R, Cox NJ, Davis LK
- Issue date: 2015 Jan 15
- WaveCNV: allele-specific copy number alterations in primary tumors and xenograft models from next-generation sequencing.
- Authors: Holt C, Losic B, Pai D, Zhao Z, Trinh Q, Syam S, Arshadi N, Jang GH, Ali J, Beck T, McPherson J, Muthuswamy LB
- Issue date: 2014 Mar 15
- Using genotype array data to compare multi- and single-sample variant calls and improve variant call sets from deep coverage whole-genome sequencing data.
- Authors: Shringarpure SS, Mathias RA, Hernandez RD, O'Connor TD, Szpiech ZA, Torres R, De La Vega FM, Bustamante CD, Barnes KC, Taub MA, CAAPA Consortium.
- Issue date: 2017 Apr 15
- SV2: accurate structural variation genotyping and de novo mutation detection from whole genomes.
- Authors: Antaki D, Brandler WM, Sebat J
- Issue date: 2018 May 15
- ReliableGenome: annotation of genomic regions with high/low variant calling concordance.
- Authors: Popitsch N, WGS500 Consortium., Schuh A, Taylor JC
- Issue date: 2017 Jan 15