BIODICA: A COMPUTATIONAL ENVIRONMENT FOR INDEPENDENT COMPONENT ANALYSIS OF OMICS DATA
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Date
2022
Authors
Captier, Nicolas
Merlevede, Jane
Molkenov, Askhat
Seisenova, Ainur
Zhubanchaliyev, Altynbek
Nazarov, Petr V
Barillot, Emmanuel
Kairov, Ulykbek
Zinovyev, Andrei
Journal Title
Journal ISSN
Volume Title
Publisher
Bioinformatics
Abstract
We developed BIODICA, an integrated computational environment for application of independent component analysis (ICA) to bulk and single-cell molecular profiles, interpretation of the results in terms of biological functions and correlation with metadata. The computational core is the novel Python package stabilized-ica which provides interface to several ICA algorithms, a stabilization procedure, meta-analysis and component interpretation tools. BIODICA is equipped with a user-friendly graphical user interface, allowing non-experienced users to perform the ICA-based omics data analysis. The results are provided in interactive ways, thus facilitating communication with biology experts.
Description
Keywords
Type of access: Open Access, BIODICA, Independent Component Analysis
Citation
Captier, N., Merlevede, J., Molkenov, A., Seisenova, A., Zhubanchaliyev, A., Nazarov, P. V., Barillot, E., Kairov, U., & Zinovyev, A. (2022). BIODICA: a computational environment for Independent Component Analysis of omics data. Bioinformatics, 38(10), 2963–2964. https://doi.org/10.1093/bioinformatics/btac204