Computational workflow for functional characterization of COVID-19 through secondary data analysis

STAR Protoc. 2021 Sep 24;2(4):100873. doi: 10.1016/j.xpro.2021.100873. eCollection 2021 Dec 17.

Abstract

Standard transcriptomic analyses cannot fully capture the molecular mechanisms underlying disease pathophysiology and outcomes. We present a computational heterogeneous data integration and mining protocol that combines transcriptional signatures from multiple model systems, protein-protein interactions, single-cell RNA-seq markers, and phenotype-genotype associations to identify functional feature complexes. These feature modules represent a higher order multifeatured machines collectively working toward common pathophysiological goals. We apply this protocol for functional characterization of COVID-19, but it could be applied to many other diseases. For complete details on the use and execution of this protocol, please refer to Ghandikota et al. (2021).

Keywords: Bioinformatics; Gene Expression; Genomics; Health Sciences; Immunology; RNAseq; Single Cell; Systems biology.