PepGM: a probabilistic graphical model for taxonomic inference of viral proteome samples with associated confidence scores.

ABSTRACT:

Motivation

Inferring taxonomy in mass spectrometry-based shotgun proteomics is a complex task. In multi-species or viral samples of unknown taxonomic origin, the presence of proteins and corresponding taxa must be inferred from a list of identified peptides, which is often complicated by protein homology: many proteins do not only share peptides within a taxon but also between taxa. However, the correct taxonomic inference is crucial when identifying different viral strains with high-sequence homology-considering, e.g., the different epidemiological characteristics of the various strains of severe acute respiratory syndrome-related coronavirus-2. Additionally, many viruses mutate frequently, further complicating the correct identification of viral proteomic samples.

Results

SUBMITTER: Holstein T 

PROVIDER: S-EPMC10182852 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature