SDrecall: a sensitive approach for variant detection in segmental duplications

SDrecall:一种灵敏的片段重复序列变异检测方法

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Abstract

Variant calling in segmental duplications is challenging for short-read sequencing because of ambiguous read origins. We present SDrecall, a method for sensitive variant detection in these regions. Upon constructing a network of homologous sequences, SDrecall realigns reads to each segmental duplication from its homologous counterparts. Realignments are phased and assembled into haplotypes via graph-based algorithms, followed by integer linear programming to retain the two most plausible haplotypes. Tested against long-read benchmarks, SDrecall achieved 95% sensitivity, while maintaining manageable false positives for short variants. SDrecall thus offers significant value for molecular diagnosis in terms of causal mutation detection within homologous regions.

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