LineageFilter: Estimating the taxonomic composition of complex samples using metaproteomics and machine learning

ABSTRACT: In this study we developped LineageFilter, a new method for refined proteotyping of complex samples using metaproteomics raw data and machine learning. Given a tentative list of taxa, their abundance, and the scores associated to their identified peptides, LineageFilter computes a comprehensive set of features for each identified taxon at all taxonomical ranks. Its machine-learning model assesses the likelihood of each taxon's presence based on these features, enabling efficient filtration of false-positive taxa.

INSTRUMENT(S):

ORGANISM(S): Enterococcus Faecalis (streptococcus Faecalis) Limosilactobacillus Fermentum Acinetobacter Baumannii Streptoccous Pyogenes Viruses Candida Albicans (yeast) Salmonella Enterica Bacillus Subtilis Saccharomyces Cerevisiae (baker's Yeast) Cellulomonas Hominis Klebsiella Pneumoniae Bacteroides Thetaiotaomicron Cryptococcus Neoformans Clostridium Butyricum Escherichia Coli Bifidobacterium Longum Lactobacillus Plantarum Bacteria Staphylococcus Aureus Enterococcus Faecium Thomasclavelia Ramosa Listeria Monocytogenes Pseudomonas Aeruginosa Eukaryota (eucaryotes) Blautia Producta Anaerostipes Caccae

SUBMITTER: Jean ARMENGAUD  

LAB HEAD: Jean Armengaud

PROVIDER: PXD049349 | Pride | 2024-11-06

REPOSITORIES: Pride