MEDALT: single-cell copy number lineage tracing enabling gene discovery
Open Access
- 23 February 2021
- journal article
- research article
- Published by Springer Science and Business Media LLC in Genome Biology
- Vol. 22 (1), 1-22
- https://doi.org/10.1186/s13059-021-02291-5
Abstract
We present a Minimal Event Distance Aneuploidy Lineage Tree (MEDALT) algorithm that infers the evolution history of a cell population based on single-cell copy number (SCCN) profiles, and a statistical routine named lineage speciation analysis (LSA), whichty facilitates discovery of fitness-associated alterations and genes from SCCN lineage trees. MEDALT appears more accurate than phylogenetics approaches in reconstructing copy number lineage. From data from 20 triple-negative breast cancer patients, our approaches effectively prioritize genes that are essential for breast cancer cell fitness and predict patient survival, including those implicating convergent evolution. The source code of our study is available at https://github.com/KChen-lab/MEDALT .Funding Information
- National Institutes of Health (R01CA172652, U01CA211006, U01CA247760)
- CPRIT (RP180248, RP180684)
- University of Texas MD Anderson Cancer Center (U54CA112970)
- National Cancer Institute (P30 CA016672)
- Chan Zuckerberg Initiative DAF (CZF2019-002432)
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