Sign in
BioinformaticsFrontiers in Microbiology
Peer-reviewed journal article

CHAMP delivers accurate taxonomic profiles of the prokaryotes, eukaryotes, and bacteriophages in the human microbiome

Sara PitaiD, Pernille Neve MyersiD, Joachim JohanseniD, Jakob RusseliD, Mads Cort NielseniD, Aron Charles EklundiD, Henrik Bjørn NielseniD

Abstract

Accurate taxonomic profiling of the human microbiome composition is crucial for linking microbial species to health outcomes. Therefore, we created the Clinical Microbiomics Human Microbiome Profiler (CHAMP), a comprehensive tool designed for the profiling of prokaryotes, eukaryotes, and viruses across all body sites. Boasting a reference database derived from 30,382 human microbiome samples, CHAMP covers 6,567 prokaryotic and 244 eukaryotic species as well as 64,003 viruses. We used a diverse set of in silico metagenomes and DNA mock communities to benchmark CHAMP against the established profiling tools MetaPhlAn 4, Bracken 2, mOTUs 3, and Phanta. CHAMP demonstrated unparalleled species recall, F1 score, and significantly reduced false positives compared to all other tools benchmarked. Indeed, the false positive relative abundance (FPRA) for CHAMP was, on average, 50-fold lower than the second-best performing profiler. CHAMP also proved to be more robust than the other tools to low sequencing depths, highlighting its application for low biomass samples. Taken together, this establishes CHAMP as a best-in-class human microbiome profiler of prokaryotes, eukaryotes, and viruses in diverse and complex communities across low and high biomass samples. CHAMP profiling is offered as a service by Clinical Microbiomics A/S and available for a fee at https://cosmosidhub.com.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers
Citations
23
FWCI
3.14
Field percentile
top 6%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.