KOunt: a reproducible KEGG orthologue abundance workflow
Open Access
- 1 August 2023
- journal article
- research article
- Published by Oxford University Press (OUP) in Bioinformatics
- Vol. 39 (8)
Abstract
Summary: Accurate gene prediction is essential for successful metagenome analysis. We present KOunt, a Snakemake pipeline, that precisely quantifies KEGG orthologue abundance. Availability and implementation: KOunt is available on GitHub: https://github.com/WatsonLab/KOunt. The KOunt reference database is available on figshare: https://doi.org/10.6084/m9.figshare.21269715. Test data are available at https://doi.org/10.6084/m9.figshare.22250152 and version 1.2.0 of KOunt at https://doi.org/10.6084/m9.figshare.23607834.Keywords
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Funding Information
- Biotechnology and Biological Sciences Research Council (BB/S006567/1, BB/S006680/1)
This publication has 18 references indexed in Scilit:
- Species-level functional profiling of metagenomes and metatranscriptomesNature Methods, 2018
- fastp: an ultra-fast all-in-one FASTQ preprocessorBioinformatics, 2018
- Bioconda: sustainable and comprehensive software distribution for the life sciencesNature Methods, 2018
- MMseqs2 enables sensitive protein sequence searching for the analysis of massive data setsNature Biotechnology, 2017
- FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studiesBMC Bioinformatics, 2016
- Near-optimal probabilistic RNA-seq quantificationNature Biotechnology, 2016
- MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graphBioinformatics, 2015
- Snakemake—a scalable bioinformatics workflow engineBioinformatics, 2012
- Prodigal: prokaryotic gene recognition and translation initiation site identificationBMC Bioinformatics, 2010
- BEDTools: a flexible suite of utilities for comparing genomic featuresBioinformatics, 2010