Fast, lightweight, and accurate metagenomic functional profiling using FracMinHash sketches

Author:

Hera Mahmudur RahmanORCID,Liu Shaopeng,Wei Wei,Rodriguez Judith S.,Ma Chunyu,Koslicki DavidORCID

Abstract

AbstractMotivationFunctional profiling of metagenomic samples is essential to decipher the functional capabilities of these microbial communities. Traditional and more widely used functional profilers in the context of metagenomics rely on aligning reads against a known reference database. However, aligning sequencing reads against a large and fast-growing database is computationally expensive. In general,k-mer-based sketching techniques have been successfully used in metagenomics to address this bottleneck, notably in taxonomic profiling. In this work, we describe leveraging FracMinHash (implemented insourmash, a publicly available software), ak-mer-sketching algorithm, to obtain functional profiles of metagenome samples. We show how pieces of thesourmashsoftware (and the resulting FracMinHash sketches) can be put together in a pipeline to functionally profile a metagenomic sample.ResultsWe report that the functional profiles obtained using this pipeline demonstrate superior completeness and purity compared to the profiles obtained using other alignment-based methods when applied to simulated metagenomic data. At the same time, we also report that our functional profiling pipeline is 42-51x faster in CPU time, 10-15.8x faster in running time, and consumes up to 20% less memory. Coupled with the KEGG database, this method not only replicates fundamental biological insights but also highlights novel signals from the Human Microbiome Project datasets.ReproducibilityThis fast and lightweight metagenomic functional profiler is freely available and can be accessed here:https://github.com/KoslickiLab/funprofiler. All scripts of the analyses we present in this manuscript can be found onGitHub.

Publisher

Cold Spring Harbor Laboratory

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