Genotype calling from next-generation sequencing data using haplotype information of reads | Zendy

Degui Zhi | Zendy; Jihua Wu | Zendy; Nianjun Liu | Zendy; Kui Zhang | Zendy

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Genotype calling from next-generation sequencing data using haplotype information of reads

Author(s) -

Degui Zhi,

Jihua Wu,

Nianjun Liu,

Kui Zhang

Publication year - 2012

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bts047

Subject(s) - genotyping , haplotype , hidden markov model , computer science , dna sequencing , genome , linkage disequilibrium , biology , computational biology , data mining , genetics , genotype , artificial intelligence , gene

Low coverage sequencing provides an economic strategy for whole genome sequencing. When sequencing a set of individuals, genotype calling can be challenging due to low sequencing coverage. Linkage disequilibrium (LD) based refinement of genotyping calling is essential to improve the accuracy. Current LD-based methods use read counts or genotype likelihoods at individual potential polymorphic sites (PPSs). Reads that span multiple PPSs (jumping reads) can provide additional haplotype information overlooked by current methods.

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