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Cited 10 time in webofscience Cited 12 time in scopus
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Comparative analysis of whole-genome sequencing pipelines to minimize false negative findings

Authors
Hwang, K.-B.Lee, I.-H.Li, H.Won, D.-G.Hernandez-Ferrer, C.Negron, J.A.Kong, S.W.
Issue Date
Mar-2019
Publisher
Nature Publishing Group
Citation
Scientific Reports, v.9, no.1, pp.3219
Journal Title
Scientific Reports
Volume
9
Number
1
Start Page
3219
URI
http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/30680
DOI
10.1038/s41598-019-39108-2
ISSN
2045-2322
Abstract
Comprehensive and accurate detection of variants from whole-genome sequencing (WGS) is a strong prerequisite for translational genomic medicine; however, low concordance between analytic pipelines is an outstanding challenge. We processed a European and an African WGS samples with 70 analytic pipelines comprising the combination of 7 short-read aligners and 10 variant calling algorithms (VCAs), and observed remarkable differences in the number of variants called by different pipelines (max/min ratio: 1.3~3.4). The similarity between variant call sets was more closely determined by VCAs rather than by short-read aligners. Remarkably, reported minor allele frequency had a substantial effect on concordance between pipelines (concordance rate ratio: 0.11~0.92; Wald tests, P < 0.001), entailing more discordant results for rare and novel variants. We compared the performance of analytic pipelines and pipeline ensembles using gold-standard variant call sets and the catalog of variants from the 1000 Genomes Project. Notably, a single pipeline using BWA-MEM and GATK-HaplotypeCaller performed comparable to the pipeline ensembles for ‘callable’ regions (~97%) of the human reference genome. While a single pipeline is capable of analyzing common variants in most genomic regions, our findings demonstrated the limitations and challenges in analyzing rare or novel variants, especially for non-European genomes. © 2019, The Author(s).
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