GBScleanR: robust genotyping error correction using a hidden Markov model with error pattern recognition.

ABSTRACT: Reduced-representation sequencing (RRS) provides cost-effective and time-saving genotyping platforms. Despite the outstanding advantage of RRS in throughput, the obtained genotype data usually contain a large number of errors. Several error correction methods employing the hidden Markov model (HMM) have been developed to overcome these issues. These methods assume that markers have a uniform error rate with no bias in the allele read ratio. However, bias does occur because of uneven amplification of genomic fragments and read mismapping. In this paper, we introduce an error correction tool, GBScleanR, which enables robust and precise error correction for noisy RRS-based genotype data by incorporating marker-specific error rates into the HMM. The results indicate that GBScleanR improves the

SUBMITTER: Furuta T 

PROVIDER: S-EPMC10213493 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature