Pathogen detection in RNA-seq data with Pathonoia.

ABSTRACT:

Background

Bacterial and viral infections may cause or exacerbate various human diseases and to detect microbes in tissue, one method of choice is RNA sequencing. The detection of specific microbes using RNA sequencing offers good sensitivity and specificity, but untargeted approaches suffer from high false positive rates and a lack of sensitivity for lowly abundant organisms.

Results

We introduce Pathonoia, an algorithm that detects viruses and bacteria in RNA sequencing data with high precision and recall. Pathonoia first applies an established k-mer based method for species identification and then aggregates this evidence over all reads in a sample. In addition, we provide an easy-to-use analysis framework that highlights potential microbe-host interactions by correlating

SUBMITTER: Liebhoff AM 

PROVIDER: S-EPMC9938591 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature