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HipHap: Haplotype Assignment and Confidence Scoring for Diploid Reference Genomes

Heinz, J. M.; Marin, M. G.; Meyerson, M.; Li, H.

2026-09-29 bioinformatics
10.64898/2026.09.24.754153 bioRxiv
Show abstract

Diploid genome assemblies are now routinely available, but most read aligners were designed for haploid references, which have long been the gold standard. When reads are aligned to a diploid assembly, the aligner sees two nearly identical alignments to either haplotype, thus reducing the mapping quality (MapQ) score to reflect this ambiguity. This can cause downstream tools to discard reads from easily mappable regions. Here, we present HipHap (HIgh- Performance HAPlotype assigner) to resolve this issue by aligning reads to each haplotype assembly separately and assigning each read to its best-supported haplotype. HipHap increased the fraction of reads mapping to the diploid genome with high MapQ, outperforming alignment to either parental haplotype. Additionally, we introduce a haplotype assignment quality score (HapQ) in HipHap to quantify confidence in the haplotype of origin of a read. HipHap is implemented in Rust, supports SAM, BAM, CRAM, and PAF formats, and is freely available at: https://github.com/jheinz27/hiphap.

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