Whole-genome haplotyping using long reads and statistical methods
| Autor: | Zhihai Ma, Dan Xie, Rui Chen, Tim Blauwkamp, Michael Snyder, Michael Kertesz, Dmitry Pushkarev, Volodymyr Kuleshov |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Genetics
Genome Human Haplotype Biomedical Engineering Bioengineering Genomics Hybrid genome assembly Computational biology Sequence Analysis DNA Biology DNA Methylation Applied Microbiology and Biotechnology Genome Polymerase Chain Reaction Polymorphism Single Nucleotide Article Haplotypes Statistical analyses Molecular Medicine Humans Human genome Algorithms Biotechnology |
| Zdroj: | Nature biotechnology |
| ISSN: | 1546-1696 1087-0156 |
| Popis: | The rapid growth of sequencing technologies has greatly contributed to our understanding of human genetics. Yet, despite this growth, mainstream technologies have not been fully able to resolve the diploid nature of the human genome. Here we describe statistically aided, long-read haplotyping (SLRH), a rapid, accurate method that uses a statistical algorithm to take advantage of the partially phased information contained in long genomic fragments analyzed by short-read sequencing. For a human sample, as little as 30 Gbp of additional sequencing data are needed to phase genotypes identified by 50× coverage whole-genome sequencing. Using SLRH, we phase 99% of single-nucleotide variants in three human genomes into long haplotype blocks 0.2-1 Mbp in length. We apply our method to determine allele-specific methylation patterns in a human genome and identify hundreds of differentially methylated regions that were previously unknown. SLRH should facilitate population-scale haplotyping of human genomes. |
| Databáze: | OpenAIRE |
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