Published January 27, 2025 | Version v1
Software Open

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

Authors/Creators

  • 1. Department of Biomedical Engineering, University of Michigan, 2200 Bonisteel, Ann Arbor, MI, 48109, USA
  • 2. Department of Computation Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Ave Ann Arbor, MI, 48109, USA
  • 3. Department of Biostatistics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA
  • 4. Department of Statistics, University of Michigan,1085 S University Ave, Ann Arbor, MI, 48109, USA

Description

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.

Files

README.md

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Additional details

Software

Repository URL
https://github.com/lanagarmire/Originator