期刊
BIOINFORMATICS
卷 35, 期 22, 页码 4806-4808出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btz479
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资金
- grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) - Ministry of Health & Welfare, Republic of Korea [HI14C1324]
- Bio & Medical Technology Development Program through the National Research Foundation of Korea (NRF) - Ministry of Science and ICT [NRF-2016M3A9B6903439]
- National Research Foundation of Korea [2016M3A9B6903439] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
A Summary: Mislabeling in the process of next generation sequencing is a frequent problem that can cause an entire genomic analysis to fail, and a regular cohort-level checkup is needed to ensure that it has not occurred. We developed a new, automated tool (BAMixChecker) that accurately detects sample mismatches from a given BAM file cohort with minimal user intervention. BAMixChecker uses a flexible, data-specific set of single-nucleotide polymorphisms and detects orphan (unpaired) and swapped (mispaired) samples based on genotype-concordance score and entropy-based file name analysis. BAMixChecker shows similar to 100% accuracy in real WES, RNA-Seq and targeted sequencing data cohorts, even for small panels (<50 genes). BAMixChecker provides an HTML-style report that graphically outlines the sample matching status in tables and heatmaps, with which users can quickly inspect any mismatch events.
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