| Title: |
Precise identification of cancer cells from allelic imbalances in single cell transcriptomes. |
| Authors: |
Trinh, Mi K; Pacyna, Clarissa N; Kildisiute, Gerda; Thevanesan, Christine; Piapi, Alice; Ambridge, Kirsty; Anderson, Nathaniel D; Khabirova, Eleonora; Prigmore, Elena; Straathof, Karin; Behjati, Sam; Young, Matthew D |
| Source: |
essn: 2399-3642 ; nlmid: 101719179 |
| Publisher Information: |
Springer Nature; //doi.org/10.1038/s42003-022-03808-9 |
| Publication Year: |
2022 |
| Collection: |
Apollo - University of Cambridge Repository |
| Subject Terms: |
Allelic Imbalance; Genotype; Humans; Neoplasms; Polymorphism; Single Nucleotide; RNA; Messenger; Transcriptome |
| Description: |
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. |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
English |
| Relation: |
PMC9452529; https://www.repository.cam.ac.uk/handle/1810/341850 |
| DOI: |
10.17863/CAM.89274 |
| Availability: |
https://www.repository.cam.ac.uk/handle/1810/341850; https://doi.org/10.17863/CAM.89274 |
| Rights: |
Attribution 4.0 International ; https://creativecommons.org/licenses/by/4.0/ |
| Accession Number: |
edsbas.E561DD31 |
| Database: |
BASE |