A dynamic Bayesian Markov model for phasing and characterizing haplotypes in next-generation sequencing.

doi:10.1093/bioinformatics/btt065

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Article

A dynamic Bayesian Markov model for phasing and characterizing haplotypes in next-generation sequencing.

Bioinformatics (Oxford, England) - 1 Apr 2013

Zhang Yu

Abstract excerpt

MOTIVATION: Next-generation sequencing (NGS) technologies have enabled whole-genome discovery and analysis of genetic variants in many species of interest. Individuals are often sequenced at low coverage for detecting novel variants, phasing haplotypes and inferring population structures. Although several tools have been developed for SNP and genotype calling in NGS data, haplotype phasing is often done...

Topics

Algorithms
Bayes Theorem
Genotype
Genotyping Techniques
Haplotypes
High-Throughput Nucleotide Sequencing
Humans
Markov Chains
Polymorphism, Single Nucleotide
Sequence Analysis, DNA

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Identifiers

PMID: 23407359
DOI: 10.1093/bioinformatics/btt065
PMCID: PMC3656686

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