PhyliCS: a Python library to explore scCNA data and quantify spatial tumor heterogeneity.

ABSTRACT:

Background

Tumors are composed by a number of cancer cell subpopulations (subclones), characterized by a distinguishable set of mutations. This phenomenon, known as intra-tumor heterogeneity (ITH), may be studied using Copy Number Aberrations (CNAs). Nowadays ITH can be assessed at the highest possible resolution using single-cell DNA (scDNA) sequencing technology. Additionally, single-cell CNA (scCNA) profiles from multiple samples of the same tumor can in principle be exploited to study the spatial distribution of subclones within a tumor mass. However, since the technology required to generate large scDNA sequencing datasets is relatively recent, dedicated analytical approaches are still lacking.

Results

We present PhyliCS, the first tool which exploits scCNA data from mu

SUBMITTER: Montemurro M 

PROVIDER: S-EPMC8254361 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature