ScCancer2: data-driven in-depth annotations of the tumor microenvironment at single-level resolution.

ABSTRACT:

Summary

Single-cell RNA-seq (scRNA-seq) is a powerful technique for decoding the complex cellular compositions in the tumor microenvironment (TME). As previous studies have defined many meaningful cell subtypes in several tumor types, there is a great need to computationally transfer these labels to new datasets. Also, different studies used different approaches or criteria to define the cell subtypes for the same major cell lineages. The relationships between the cell subtypes defined in different studies should be carefully evaluated. In this updated package scCancer2, designed for integrative tumor scRNA-seq data analysis, we developed a supervised machine learning framework to annotate TME cells with annotated cell subtypes from 15 scRNA-seq datasets with 594 samples in total.

SUBMITTER: Chen Z 

PROVIDER: S-EPMC10868330 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature