iMOKA: k-mer based software to analyze large collections of sequencing data.

Autor: Lorenzi C; IGH, Centre National de la Recherche Scientifique, University of Montpellier, Montpellier, France., Barriere S; IGH, Centre National de la Recherche Scientifique, University of Montpellier, Montpellier, France., Villemin JP; IGH, Centre National de la Recherche Scientifique, University of Montpellier, Montpellier, France., Dejardin Bretones L; IGH, Centre National de la Recherche Scientifique, University of Montpellier, Montpellier, France., Mancheron A; LIRMM, Université de Montpellier, CNRS, Montpellier, France., Ritchie W; IGH, Centre National de la Recherche Scientifique, University of Montpellier, Montpellier, France. william.ritchie@igh.cnrs.fr.
Jazyk: angličtina
Zdroj: Genome biology [Genome Biol] 2020 Oct 13; Vol. 21 (1), pp. 261. Date of Electronic Publication: 2020 Oct 13.
DOI: 10.1186/s13059-020-02165-2
Abstrakt: iMOKA (interactive multi-objective k-mer analysis) is a software that enables comprehensive analysis of sequencing data from large cohorts to generate robust classification models or explore specific genetic elements associated with disease etiology. iMOKA uses a fast and accurate feature reduction step that combines a Naïve Bayes classifier augmented by an adaptive entropy filter and a graph-based filter to rapidly reduce the search space. By using a flexible file format and distributed indexing, iMOKA can easily integrate data from multiple experiments and also reduces disk space requirements and identifies changes in transcript levels and single nucleotide variants. iMOKA is available at https://github.com/RitchieLabIGH/iMOKA and Zenodo https://doi.org/10.5281/zenodo.4008947 .
Databáze: MEDLINE
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