CytokineFindeR: an R-package for benchmarking methods and databases for identifying cytokines

Abstract

Cytokines play a central role in disease but are hard to study due to their short half-life and low abundance. Computational approaches have utilized gene-expression for pinpointing cytokine drivers of diseases. We benchmark various cytokine identification methods and found little congruency between gene sets for the same ligand, and variable performance in identifying cytokines based on curated ligand-receptor interactions. CytoSig, a model-based approach, was generally better at identifying the correct disease cytokine but failed for certain cytokines such as IL-13. We developed CytokinefindeR, an R package that enables comparative analysis of cytokine detection across 10 databases and four computational approaches.