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HAplotype inference using Reference and Sequencing tecHnology HARSH

An efficient method that combines multi-SNP read information with reference panels of haplotypes for improved genotype and haplotype inference in sequencing data. Unlike previous phasing methods that use read counts at each SNP as input, our method takes into account the information from reads spanning multiple SNPs. HARSH is able to efficiently find the likely haplotypes in terms of the marginal probability over the genotype data. Using simulations from HapMap and 1000 Genomes data, we show that our method achieves superior accuracy than existing approaches with decreased computational requirements.

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HARSH classification

HARSH specifications

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HARSH distribution


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HARSH support


  • Wen-Yun Yang <>


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Department of Computer Science, University of California, Los Angeles, CA, USA; Inter-Departmental Program in Bioinformatics, University of California, Los Angeles, CA, USA; IBM T.J. Watson Research, Yorktown Heights, NY, USA; Department of Pathology and Laboratory Medicine, University of California, Los Angeles, CA, USA; Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA, USA; Department of Human Genetics, University of California, Los Angeles, CA, USA

Funding source(s)

National Science Foundation (0513612, 0731455, 0729049, 0916676, 1065276 and 1320589); National Institutes of Health (K25-HL080079, U01-DA024417, P01-HL30568, PO1-HL28481 R03-CA162200 and R01-GM053275)

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