Skip to Main content Skip to Navigation
Journal articles

BIODICA: a computational environment for Independent Component Analysis of omics data

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 nonexperienced users to perform the ICA-based omics data analysis. The results are provided in interactive ways, thus facilitating communication with biology experts. Availability and Implementation: BIODICA is implemented in Java, Python and JavaScript. The source code is freely available on GitHub under the MIT and the GNU LGPL licenses. BIODICA is supported on all major operating systems. Url:
Document type :
Journal articles
Complete list of metadata
Contributor : Nicolas Captier Connect in order to contact the contributor
Submitted on : Monday, April 4, 2022 - 3:28:17 PM
Last modification on : Wednesday, September 28, 2022 - 5:49:32 AM
Long-term archiving on: : Tuesday, July 5, 2022 - 6:48:01 PM


 Restricted access
To satisfy the distribution rights of the publisher, the document is embargoed until : 2022-10-06

Please log in to resquest access to the document



Nicolas Captier, Jane Merlevede, Askhat Molkenov, Ainur Seisenova, Altynbek Zhubanchaliyev, et al.. BIODICA: a computational environment for Independent Component Analysis of omics data. Bioinformatics, Oxford University Press (OUP), 2022, pp.btac204. ⟨10.1093/bioinformatics/btac204⟩. ⟨inserm-03629778⟩



Record views