Multi-omics data harmonisation for the discovery of COVID-19 drug targets

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},
}