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

Author:

Captier Nicolas1234ORCID,Merlevede Jane123,Molkenov Askhat5,Seisenova Ainur5,Zhubanchaliyev Altynbek5,Nazarov Petr V6ORCID,Barillot Emmanuel123,Kairov Ulykbek5,Zinovyev Andrei123ORCID

Affiliation:

1. Institut National de la Santé et de la Recherche Médicale (INSERM), U900 , F-75005 Paris, France

2. Institut Curie, PSL Research University , F-75005 Paris, France

3. MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology , F-75006 Paris, France

4. Laboratoire d’Imagerie Translationnelle en Oncologie, Institut Curie, INSERM U1288, PSL Research University , 91400 Orsay, France

5. National Laboratory Astana, Center for Life Sciences, Nazarbayev University, Nur-Sultan 010000, Kazakhstan

6. Multiomics Data Science Research Group, Department of Cancer Research & Bioinformatics Platform, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg

Abstract

Abstract Summary 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. 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: https://sysbio-curie.github.io/biodica-environment/.

Funder

French government under management of Agence Nationale de la Recherche as part of the ‘Investissements d’avenir’ program

PRAIRIE 3IA Institute) and by the European Union’s Horizon 2020 program

TIPIT project (Towards an Integrative approach for Precision ImmunoTherapy) funded by Fondation ARC call «SIGN’IT 2020—Signatures in Immunotherapy

Innovative Medicines Initiative 2 Joint Undertaking

Ministry of Education and Science of the Republic of Kazakhstan

RNA

Luxembourg National Research Fund

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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