ArticleBioinformatics (Oxford, England)2018
Sensitive and specific post-call filtering of genetic variants in xenograft and primary tumors.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Comprehensive characterization of patient-derived xenograft models of pediatric leukemia.iScience · 2023Article
- Translesion DNA synthesis mediates acquired resistance to olaparib plus temozolomide in small cell lung cancer.Science advances · 2022Article
- Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Motivation: 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. Availability and implementation: The mapexr package for R is available at https://github.com/bmannakee/mapexr under the MIT license. Contact: mannakee@email.arizona.edu or rgutenk@email.arizona.edu or eknudsen@email.arizona.edu. Supplementary information: Supplementary data are available at Bioinformatics online.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.