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

Abstract : 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.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-02987774
Contributor : Alban Mancheron <>
Submitted on : Wednesday, November 4, 2020 - 11:00:14 AM
Last modification on : Thursday, November 5, 2020 - 3:28:53 AM

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Claudio Lorenzi, Sylvain Barriere, Jean-Philippe Villemin, Laureline Dejardin Bretones, Alban Mancheron, et al.. iMOKA: k-mer based software to analyze large collections of sequencing data. Genome Biology, BioMed Central, 2020, 21 (1), ⟨10.1186/s13059-020-02165-2⟩. ⟨lirmm-02987774⟩

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