K-mer based prediction of Clostridioides difficile relatedness and ribotypes.

ABSTRACT: Comparative analysis of Clostridioides difficile whole-genome sequencing (WGS) data enables fine scaled investigation of transmission and is increasingly becoming part of routine surveillance. However, these analyses are constrained by the computational requirements of the large volumes of data involved. By decomposing WGS reads or assemblies into k-mers and using the dimensionality reduction technique MinHash, it is possible to rapidly approximate genomic distances without alignment. Here we assessed the performance of MinHash, as implemented by sourmash, in predicting single nucleotide differences between genomes (SNPs) and C. difficile ribotypes (RTs). For a set of 1905 diverse C. difficile genomes (differing by 0-168 519 SNPs), using sourmash to screen for closely

SUBMITTER: Moore MP 

PROVIDER: S-EPMC9453075 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature