TriPoly: a haplotype estimation approach for polyploids using sequencing data of related individuals
Knowledge of "haplotypes", i.e. phased and ordered marker alleles on a chromosome, is essential to answer many questions in genetics and genomics. By generating short pieces of DNA sequence, high-throughput modern sequencing technologies make estimation of haplotypes possible for single individuals. In polyploids, however, haplotype estimation methods usually require deep coverage to achieve sufficient accuracy. This often renders sequencing-based approaches too costly to be applied to large populations needed in studies of Quantitative Trait Loci (QTL). We propose a novel haplotype estimation method for polyploids, TriPoly, that combines sequencing data with Mendelian inheritance rules to infer haplotypes in parent-offspring trios. Using realistic simulations of short-read sequencing data for potato (Solanum tuberosum) and banana (Musa acuminata) trios, we show that TriPoly yields more accurate progeny haplotypes at low coverages compared to the existing methods that work on single individuals.
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