SNP-slice resolves mixed infections: simultaneously unveiling strain haplotypes and linking them to hosts.

ABSTRACT:

Motivation

Multi-strain infection is a common yet under-investigated phenomenon of many pathogens. Currently, biologists analyzing SNP information sometimes have to discard mixed infection samples as many downstream analyses require monogenomic inputs. Such a protocol impedes our understanding of the underlying genetic diversity, co-infection patterns, and genomic relatedness of pathogens. A scalable tool to learn and resolve the SNP-haplotypes from polygenomic data is an urgent need in molecular epidemiology.

Results

We develop a slice sampling Markov Chain Monte Carlo algorithm, named SNP-Slice, to learn not only the SNP-haplotypes of all strains in the populations but also which strains infect which hosts. Our method reconstructs SNP-haplotypes and individual heterozygosi

SUBMITTER: Ju N 

PROVIDER: S-EPMC11187496 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature