The ability to characterize repetitive regions of the human genome is limited by the read lengths of short-read sequencing technologies. Although long-read sequencing technologies such as Pacific Biosciences and Oxford Nanopore can potentially overcome this limitation, long segmental duplications with high sequence identity pose challenges for long-read mapping. We describe a probabilistic method, DuploMap, designed to improve the accuracy of long read mapping in segmental duplications. It

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... zes reads mapped to segmental duplications using existing long-read aligners and leverages paralogous sequence variants (PSVs) - sequence differences between paralogous sequences - to distinguish between multiple alignment locations. On simulated datasets, Duplomap increased the percentage of correctly mapped reads with high confidence for multiple long-read aligners including Minimap2 (74.3% to 90.6%) and BLASR (82.9% to 90.7%) while maintaining high precision. Across multiple whole-genome long-read datasets, DuploMap aligned an additional 8-21% of the reads in segmental duplications with high confidence relative to Minimap2. Using Duplomap aligned PacBio CCS reads, an additional 8.9 Mbp of DNA sequence was mappable, variant calling achieved a higher F1-score and 14,713 additional variants supported by linked-read data were identified. Finally, we demonstrate that a significant fraction of PSVs in segmental duplications overlap with variants and adversely impact short-read variant calling.