4.7 Article

gpart: human genome partitioning and visualization of high-density SNP data by identifying haplotype blocks

Journal

BIOINFORMATICS
Volume 35, Issue 21, Pages 4419-4421

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btz308

Keywords

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Funding

  1. National Research Foundation of Korea (NRF) [NRF-2018R1A2B6008016]
  2. Canadian Institutes of Health Research (CIHR) [MOP-84287, PJT 159463]
  3. Canadian Statistical Sciences Institute
  4. Canadian Institutes of Health Research Strategic Training for Advanced Genetic Epidemiology (CIHR STAGE) [GET-101831]

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aSummary: For the analysis of high-throughput genomic data produced by next-generation sequencing (NGS) technologies, researchers need to identify linkage disequilibrium (LD) structure in the genome. In this work, we developed an R package gpart which provides clustering algorithms to define LD blocks or analysis units consisting of SNPs. The visualization tool in gpart can display the LD structure and gene positions for up to 20 000 SNPs in one image. The gpart functions facilitate construction of LD blocks and SNP partitions for vast amounts of genome sequencing data within reasonable time and memory limits in personal computing environments.

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