HAT
haplotype assembly tool using short and error-prone long reads
Ramin Shirali Hossein Zade (TU Delft - Pattern Recognition and Bioinformatics)
A. Urhan (Broad Institute of MIT and Harvard, TU Delft - Pattern Recognition and Bioinformatics)
A. Assis de Souza (TU Delft - Pattern Recognition and Bioinformatics)
Akash Singh (TU Delft - Pattern Recognition and Bioinformatics)
T.E.P.M.F. Abeel (TU Delft - Pattern Recognition and Bioinformatics, Broad Institute of MIT and Harvard)
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Abstract
Motivation: Haplotypes are the set of alleles co-occurring on a single chromosome and inherited together to the next generation. Because a monoploid reference genome loses this co-occurrence information, it has limited use in associating phenotypes with allelic combinations of genotypes. Therefore, methods to reconstruct the complete haplotypes from DNA sequencing data are crucial. Recently, several attempts have been made at haplotype reconstructions, but significant limitations remain. High-quality continuous haplotypes cannot be created reliably, particularly when there are few differences between the homologous chromosomes. Results: Here, we introduce HAT, a haplotype assembly tool that exploits short and long reads along with a reference genome to reconstruct haplotypes. HAT tries to take advantage of the accuracy of short reads and the length of the long reads to reconstruct haplotypes. We tested HAT on the aneuploid yeast strain Saccharomyces pastorianus CBS1483 and multiple simulated polyploid datasets of the same strain, showing that it outperforms existing tools.
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