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

Genome Biology

Sylvain Barriere¹  Laureline Dejardin Bretones¹  Jean-Philippe Villemin¹  Claudio Lorenzi¹  William Ritchie¹  Alban Mancheron² 

[1] IGH, Centre National de la Recherche Scientifique, University of Montpellier, Montpellier, France;LIRMM, Université de Montpellier, CNRS, Montpellier, France;

关键词: k;    NGS analysis;    Personalized medicine;    Bioinformatics software;    Data reduction;    Machine learning;   

DOI  :  10.1186/s13059-020-02165-2

来源: Springer

【 摘 要 】

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 10.5281/zenodo.4008947.

【 授权许可】

CC BY