Minimizing Reference Bias with an Impute-First Approach.

ABSTRACT: Pangenome indexes reduce reference bias in sequencing data analysis. However, bias can be reduced further by using a personalized reference, e.g. a diploid human reference constructed to match a donor individual's alleles. We present a novel impute-first alignment framework that combines elements of genotype imputation and pangenome alignment. It begins by genotyping the individual using only a subsample of the input reads. It next uses a reference panel and efficient imputation algorithm to impute a personalized diploid reference. Finally, it indexes the personalized reference and applies a read aligner, which could be a linear or graph aligner, to align the full read set to the personalized reference. This framework achieves higher variant-calling recall (99.54% vs. 99.37%), precision (9

SUBMITTER: Vaddadi K 

PROVIDER: S-EPMC10705441 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature