PyBSASeq: a simple and effective algorithm for bulked segregant analysis with whole-genome sequencing data.

ABSTRACT: BACKGROUND:Bulked segregant analysis (BSA), coupled with next-generation sequencing, allows the rapid identification of both qualitative and quantitative trait loci (QTL), and this technique is referred to as BSA-Seq here. The current SNP index method and G-statistic method for BSA-Seq data analysis require relatively high sequencing coverage to detect significant single nucleotide polymorphism (SNP)-trait associations, which leads to high sequencing cost. RESULTS:We developed a simple and effective algorithm for BSA-Seq data analysis and implemented it in Python; the program was named PyBSASeq. Using PyBSASeq, the significant SNPs (sSNPs), SNPs likely associated with the trait, were identified via Fisher's exact test, and then the ratio of the sSNPs to total SNPs in a chromosomal interval

SUBMITTER: Zhang J 

PROVIDER: S-EPMC7060572 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature