{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Shaw J"],"funding":["Natural Sciences and Engineering Research Council of Canada"],"pagination":["151"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11323348"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["12(1)"],"pubmed_abstract":["<h4>Background</h4>Metagenomic binning, the clustering of assembled contigs that belong to the same genome, is a crucial step for recovering metagenome-assembled genomes (MAGs). Contigs are linked by exploiting consistent signatures along a genome, such as read coverage patterns. Using coverage from multiple samples leads to higher-quality MAGs; however, standard pipelines require all-to-all read alignments for multiple samples to compute coverage, becoming a key computational bottleneck.<h4>Results</h4>We present fairy ( https://github.com/bluenote-1577/fairy ), an approximate coverage calculation method for metagenomic binning. Fairy is a fast k-mer-based alignment-free method. For multi-sample binning, fairy can be >250× faster than read alignment and accurate enough for binning. Fairy "],"journal":["Microbiome"],"pubmed_title":["Fairy: fast approximate coverage for multi-sample metagenomic binning."],"pmcid":["PMC11323348"],"funding_grant_id":["CGS-D","RGPIN-2022-309 03074"],"pubmed_authors":["Yu YW","Shaw J"],"additional_accession":[]},"is_claimable":false,"name":"Fairy: fast approximate coverage for multi-sample metagenomic binning.","description":"<h4>Background</h4>Metagenomic binning, the clustering of assembled contigs that belong to the same genome, is a crucial step for recovering metagenome-assembled genomes (MAGs). Contigs are linked by exploiting consistent signatures along a genome, such as read coverage patterns. Using coverage from multiple samples leads to higher-quality MAGs; however, standard pipelines require all-to-all read alignments for multiple samples to compute coverage, becoming a key computational bottleneck.<h4>Results</h4>We present fairy ( https://github.com/bluenote-1577/fairy ), an approximate coverage calculation method for metagenomic binning. Fairy is a fast k-mer-based alignment-free method. For multi-sample binning, fairy can be >250× faster than read alignment and accurate enough for binning. Fairy ","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Aug","modification":"2025-05-18T12:13:03.576Z","creation":"2025-04-05T10:09:15.166Z"},"accession":"S-EPMC11323348","cross_references":{"pubmed":["39143609"],"doi":["10.1186/s40168-024-01861-6"]}}