We present a generic, flexible, reproducible, open-access data harmonisation framework that can be scaled out to future multi-omics analysis to study a phenotype in a holistic manner. Our git repository along with code, documentation and sample data on two case studies are available with install instructions. The pipeline can also be installed as an R package: install.packages(devtools) install_gitlab("tyagilab/sars-cov-2", subdir="multiomics", build_vignettes=TRUE) Please view our publication for more information: @article{10.1093/bib/bbab185, author = {Chen, Tyrone and Philip, Melcy and Lê Cao, Kim-Anh and Tyagi, Sonika}, title = "{A multi-modal data harmonisation approach for discovery of COVID-19 drug targets}", journal = {Briefings in Bioinformatics}, year = {2021}, month = {05}, issn = {1477-4054}, doi = {10.1093/bib/bbab185}, url = {https://doi.org/10.1093/bib/bbab185}, note = {bbab185}, eprint = {https://academic.oup.com/bib/advance-article-pdf/doi/10.1093/bib/bbab185/38130519/bbab185.pdf}, }

{"references": ["https://doi.org/10.1093/bib/bbab185"]}