Merck Research Laboratory is part of Merck & Co., Inc. The Data and Genome Sciences department focus on Genomics and Data Science for early pre-clinical to clinical research.
Novel drug-targeting modalities often rely on the co-occurrence of target proteins to deliver a drug to the target site of interest. Co-occurrence can be estimated from protein or RNA profiling data on a bulk tissue level. However, for greater cell specificity, estimations on the single-cell level are of high interest. Single-cell level estimation of feature co-occurrence is non-trivial because of the inherent data sparsity. To address this, novel network-based and statistical methods have been developed in the last few years. This study aims to survey, evaluate, and compare single-cell co-expression estimation methods by applying them to a public cancer single-cell RNA-seq dataset. The results of this study will greatly impact the method of choice for future drug development support using co-expression estimations.
