muCNV: Genotyping Structural Variants for Population-level Sequencing

Goo Jun; Fritz Sedlazeck; Qihui Zhu; Adam English; Ginger Metcalf; Hyun Min Kang; Human Genome Structural Variation Consortium (HGSVC); Charles Lee; Richard Gibbs; Eric Boerwinkle

doi:10.1093/bioinformatics/btab199

muCNV: Genotyping Structural Variants for Population-level Sequencing

Bioinformatics. 2021 Aug 4;37(14):2055–2057. doi: 10.1093/bioinformatics/btab199. Epub 2021 Mar 24.

Authors

Goo Jun¹, Fritz Sedlazeck², Qihui Zhu³, Adam English², Ginger Metcalf², Hyun Min Kang⁴; Human Genome Structural Variation Consortium (HGSVC); Charles Lee³, Richard Gibbs², Eric Boerwinkle¹

Affiliations

¹ Human Genetics Center, University of Texas Health Science Center at Houston, 1200 Pressler St., Houston, TX 77030, USA.
² Human Genome Sequencing Center, Baylor College of Medicine, 1 Baylor Olaza, Houston, TX 77030, USA.
³ Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA.
⁴ Department of Biostatistics, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109, USA.

Abstract

Motivation: There are high demands for joint genotyping of structural variations with short-read sequencing, but efficient and accurate genotyping in population scale is a challenging task.

Results: We developed muCNV that aggregates per-sample summary pileups for joint genotyping of > 100,000 samples. Pilot results show very low Mendelian inconsistencies. Applications to large-scale projects in cloud show the computational efficiencies of muCNV genotyping pipeline.

Availability: muCNV is publicly available for download at: https://github.com/gjun/muCNV.

Supplementary information: Supplementary data are available at Bioinformatics online.

MeSH terms

Computational Biology / methods
Genotype
Genotyping Techniques / methods
High-Throughput Nucleotide Sequencing / methods
Humans
Sequence Analysis, DNA / methods
Software*

Abstract

MeSH terms

Grants and funding