0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessAbstract How tumors evolve affects cancer progression, therapy response, and relapse. However, whether tumor evolution is driven primarily by selectively advantageous or neutral mutations remains under debate. Resolving this controversy has so far been limited by the use of bulk sequencing data. Here, we leverage the high resolution of single-cell DNA sequencing (scDNA-seq) to test for clock-like, neutral evolution. Under neutrality, different cell lineages evolve at a similar rate, accumulating mutations according to a molecular clock. We developed and benchmarked a test of the somatic clock based on single-cell phylogenies and applied it to 22 scDNA-seq datasets. We rejected the clock in 10/13 cancer and 5/9 healthy datasets. The clock rejection in seven cancer datasets could be related to known driver mutations. Our findings demonstrate the power of scDNA-seq for studying somatic evolution and suggest that some cancer and healthy cell populations are driven by selection while others seem to evolve under neutrality.
Nico Borgsmüller, Monica Valecha, Jack Kuipers, Niko Beerenwinkel, David Posada (2022). Single-cell phylogenies reveal deviations from clock-like, neutral evolution in cancer and healthy tissues. , DOI: https://doi.org/10.1101/2022.08.09.503287.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Preprint
Year
2022
Authors
5
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1101/2022.08.09.503287
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access