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

Degui Zhi1, Jihua Wu, Nianjun Liu

  • 1Section on Statistical Genetics, Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA. dzhi@ms.soph.uab.edu

Summary

A new Hidden Markov Model (HMM) method improves whole genome sequencing accuracy by utilizing jumping reads. The HapSeq program reduces genotyping error rates by up to 30% in simulations and real-world data.

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