BIODICA: A computational environment for Independent Component Analysis of omics data
Captier N. Merlevede J. Molkenov A. Seisenova A. Zhubanchaliyev A. Nazarov P.V. Barillot E. Kairov U. Zinovyev A.
15 May 2022Oxford University Press
Bioinformatics
2022#38Issue 102963 - 2964 pp.
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.
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Institut National de la Sante et de la Recherche Medicale (INSERM), U900, Paris, F-75005, France
Institut Curie, PSL Research University, Paris, F-75005, France
MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, Paris, F-75006, France
Laboratoire dImagerie Translationnelle en Oncologie, Institut Curie, INSERM U1288, PSL Research University, Orsay, 91400, France
National Laboratory Astana, Center for Life Sciences, Nazarbayev University, Nur-Sultan, 010000, Kazakhstan
Multiomics Data Science Research Group, Department of Cancer Research & Bioinformatics Platform, Luxembourg Institute of Health, Strassen, L-1445, Luxembourg
Institut National de la Sante et de la Recherche Medicale (INSERM)
Institut Curie
MINES ParisTech
Laboratoire dImagerie Translationnelle en Oncologie
National Laboratory Astana
Multiomics Data Science Research Group
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