Inference of intra-tumor heterogeneity can provide valuable insight into cancer evolution. Somatic mutations detected by sequencing can help estimate the purity of a tumor sample and reconstruct its subclonal composition. While several methods have been developed to infer intra-tumor heterogeneity, the majority of these tools rely on variant allele frequencies as estimated via ultra-deep sequencing from multiple samples of the same tumor. In practice, obtaining sequencing data from a large number of samples per patient is only feasible in a few cancer types such as liquid tumors, or in rare cases involving solid tumors selected for research. We introduce CTPsingle, which aims to infer the subclonal composition using low-coverage sequencing data from a single tumor sample. We show that CTPsingle is able to infer the purity and the clonality of single-sample tumors with high accuracy even restricted to a coverage depth of ∼30x.
CITATION STYLE
Donmez, N., Malikic, S., Wyatt, A. W., Gleave, M. E., Collins, C. C., & Sahinap, S. C. (2016). Clonality inference from single tumor samples using low coverage sequence data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9649, pp. 83–94). Springer Verlag. https://doi.org/10.1007/978-3-319-31957-5_6
Mendeley helps you to discover research relevant for your work.