Cargando…

MEDALT: single-cell copy number lineage tracing enabling gene discovery

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-associat...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Fang, Wang, Qihan, Mohanty, Vakul, Liang, Shaoheng, Dou, Jinzhuang, Han, Jincheng, Minussi, Darlan Conterno, Gao, Ruli, Ding, Li, Navin, Nicholas, Chen, Ken
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7901082/
https://www.ncbi.nlm.nih.gov/pubmed/33622385
http://dx.doi.org/10.1186/s13059-021-02291-5
Descripción
Sumario: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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-021-02291-5.