Goo Jun1, Fritz Sedlazeck2, Qihui Zhu3, Adam English2, Ginger Metcalf2, Hyun Min Kang4, Charles Lee3, Richard Gibbs2, Eric Boerwinkle1. 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.
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.
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