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

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.