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 towards common pathophysiological goals. We apply this protocol for functional characterization of COVID-19, but it could be applied to many other diseases.
Fuente: STAR Protocols
Available online 24 September 2021, 100873
In Press, Journal Pre-proof
