An information-theoretic approach for measuring the distance of organ tissue samples using their transcriptomic signatures

Abstract

MotivationRecapitulating aspects of human organ functions using in-vitro (e.g., plates, transwells, etc.), in-vivo (e.g., mouse, rat, etc.), or ex-vivo (e.g., organ chips, 3D systems, etc.) organ models are of paramount importance for precision medicine and drug discovery. It will allow us to identify potential side effects and test the effectiveness of therapeutic approaches early in their design phase and will inform the development of accurate disease models. Developing mathematical methods to reliably compare the "distance/similarity" of organ models from/to the real human organ they represent is an understudied problem with important applications in biomedicine and tissue engineering. ResultsWe introduce the Transctiptomic Signature Distance, TSD, an information-theoretic distance for assessing the transcriptomic similarity of two tissue samples, or two groups of tissue samples. In developing TSD, we are leveraging next-generation sequencing data and information retrieved from well-curated databases providing signature gene sets characteristic for human organs. We present the justification and mathematical development of the new distance and demonstrate its effectiveness in different scenarios of practical importance using several publicly available RNA-seq datasets. Contactdimitris.manatakis@emulatebio.com Supplementary informationSupplementary data are available at bioRxiv.