Rescue Blood Contamination in scRNA-Seq Data by Originator, a Computational Deciphering Tool using Genetic and Contextual Information

Abstract

AbstractSingle-cell RNA sequencing (scRNA-Seq) data from complex human tissues have prevalent blood cell contamination due to the sample preparation process and may comprise cells of different genetic makeups. To reveal such complexity and annotate cells appropriately, we propose the first-of-its-kind computational framework, Originator, which deciphers single cells by genetic origin and separates blood cells from tissue-resident cells. We show that blood contamination is widely spread in scRNA-Seq data from a variety of tissues. We warn of the significant biases in downstream analysis without considering blood contamination and genetic contexts using pancreatic ductal adenocarcinoma and placenta data, respectively.