Communications BiologyGenomicsPeer-reviewed journal article
Precise identification of cancer cells from allelic imbalances in single cell transcriptomes
Mi K. TrinhiD, Clarissa N. PacynaiD, Gerda KildisiuteiD, Christine ThevanesaniD, Alice PiapiiD, Kirsty Ambridge, Nathaniel D. AndersoniD, Eleonora KhabirovaiD, Elena PrigmoreiD, Karin C. M. StraathofiD, Sam BehjatiiD, Matthew D. YoungiD
Abstract
A fundamental step of tumour single cell mRNA analysis is separating cancer and non-cancer cells. We show that the common approach to separation, using shifts in average expression, can lead to erroneous biological conclusions. By contrast, allelic imbalances representing copy number changes directly detect the cancer genotype and accurately separate cancer from non-cancer cells. Our findings provide a definitive approach to identifying cancer cells from single cell mRNA sequencing data.
- Citations
- 18
- FWCI
- 1.22
- Field percentile
- top 22%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Simultaneous Enumeration Of Cancer And Immune Cell Types From Bulk Tumor Gene Expression Data
J. Racle, K. de Jonge, … D. Gfeller·bioRxiv·Sep 1, 2017
- A novel computational approach to identify cancer cells in scRNA-seq data
William Gasper, Francesca Rossi, … Dario Ghersi·bioRxiv·Apr 28, 2022
- A unique malignant cell type per patient tumor is encoded in each cancer cell transcriptome.
Mirca Saras Saurty-Seerunghen, Elias A. El-Habr, … Marie‐Pierre Junier·iSciencePeer-reviewed·Feb 25, 2026
- Identifying tumor cells at the single cell level
J. Dohmen, A. Baranovskii, … A. Akalin·bioRxiv·Oct 15, 2021
- High-confidence calling of normal epithelial cells allows identification of a novel stem-like cell state in the colorectal cancer microenvironment
T.-T. Wei, E. Blanc, … B. Obermayer·bioRxiv·Feb 23, 2024
- A Universal Algorithm to Detect Rare or Novel Cell Types in High-Throughput Single-Cell Gene Expression Data
Zoe Weiss, Daphne M. Tsoucas·bioRxiv·Oct 13, 2018