Identifying cancer cells from calling single-nucleotide variants in scRNA-seq data.

ABSTRACT:

Motivation

Single-cell RNA sequencing (scRNA-seq) data are widely used to study cancer cell states and their heterogeneity. However, the tumour microenvironment is usually a mixture of healthy and cancerous cells and it can be difficult to fully separate these two populations based on transcriptomics alone. If available, somatic single-nucleotide variants (SNVs) observed in the scRNA-seq data could be used to identify the cancer population and match that information with the single cells' expression profile. However, calling somatic SNVs in scRNA-seq data is a challenging task, as most variants seen in the short-read data are not somatic, but can instead be germline variants, RNA edits or transcription, sequencing, or processing errors. In addition, only variants present in activel

SUBMITTER: Marot-Lassauzaie V 

PROVIDER: S-EPMC11379463 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature