# Single-cell RNA-seq data have prevalent blood contamination but can be rescued by Originator, a computational tool separating single-cell RNA-seq by genetic and contextual information

## TL;DR

This paper introduces Originator, a computational tool that identifies and separates blood contamination in single-cell RNA-seq data to improve accuracy in complex tissues.

## Contribution

Originator is a novel computational framework that separates blood contamination and genetic origins in single-cell RNA-seq data.

## Key findings

- Originator accurately separates immune cells from blood and tissue in scRNA-seq data.
- The tool performs well on both artificial and real datasets, including pancreatic cancer and placenta samples.

## Abstract

Single-cell RNA sequencing (scRNA-seq) data from complex human tissues have prevalent blood cell contamination during the sample preparation process. They may also comprise cells of different genetic makeups. We propose a new computational framework, Originator, which deciphers single cells by genetic origin and separates immune cells of blood contamination from those of expected tissue-resident cells. We demonstrate the accuracy of Originator at separating immune cells from the blood and tissue as well as cells of different genetic origins, using a variety of artificially mixed and real datasets, including pancreatic cancer and placentas as examples.

The online version contains supplementary material available at 10.1186/s13059-025-03495-9.