Computational methods for chromosome-scale haplotype reconstruction.

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  • Author(s): Garg S;Garg S
  • Source:
    Genome biology [Genome Biol] 2021 Apr 12; Vol. 22 (1), pp. 101. Date of Electronic Publication: 2021 Apr 12.
  • Publication Type:
    Journal Article; Review
  • Language:
    English
  • Additional Information
    • Source:
      Publisher: BioMed Central Ltd Country of Publication: England NLM ID: 100960660 Publication Model: Electronic Cited Medium: Internet ISSN: 1474-760X (Electronic) Linking ISSN: 14747596 NLM ISO Abbreviation: Genome Biol Subsets: MEDLINE
    • Publication Information:
      Publication: London, UK : BioMed Central Ltd
      Original Publication: London : Genome Biology Ltd., c2000-
    • Subject Terms:
      Chromosomes* ; Haplotypes*; Computational Biology/*methods ; Genomics/*methods; Diploidy ; High-Throughput Nucleotide Sequencing/methods ; Humans ; Metagenome ; Metagenomics/methods ; Polyploidy ; Sequence Analysis, DNA/methods
    • Abstract:
      High-quality chromosome-scale haplotype sequences of diploid genomes, polyploid genomes, and metagenomes provide important insights into genetic variation associated with disease and biodiversity. However, whole-genome short read sequencing does not yield haplotype information spanning whole chromosomes directly. Computational assembly of shorter haplotype fragments is required for haplotype reconstruction, which can be challenging owing to limited fragment lengths and high haplotype and repeat variability across genomes. Recent advancements in long-read and chromosome-scale sequencing technologies, alongside computational innovations, are improving the reconstruction of haplotypes at the level of whole chromosomes. Here, we review recent and discuss methodological progress and perspectives in these areas.
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    • Publication Date:
      Date Created: 20210413 Date Completed: 20220111 Latest Revision: 20220111
    • Publication Date:
      20231215
    • Accession Number:
      PMC8040228
    • Accession Number:
      10.1186/s13059-021-02328-9
    • Accession Number:
      33845884