Haplotype and Repeat Separation in Long Reads
Resolving the correct structure and succession of highly similar sequence stretches is one of the main open problems in genome assembly. For non haploid genomes this includes determining the sequences of the different haplotypes. For all but the smallest genomes it also involves separating different repeat instances. In this paper we discuss methods for resolving such problems in third generation long reads by classifying alignments between long reads according to whether they represent true or false read overlaps. The main problem in this context is the high error rate found in such reads, which greatly exceeds the variance between the similar regions we want to separate. Our methods can separate read classes stemming from regions with as little as \(1\%\) difference.
We thank Gene Myers for interesting algorithmical discussions related to this paper and Shilpa Garg for advice on running WhatsHap.
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