ScSelector: A Flexible Single-Cell Data Analysis Assistant for Biomedical Researchers.

ABSTRACT: Background: Standard single-cell RNA sequencing (scRNA-seq) analysis workflows face significant limitations, particularly the rigidity of clustering-dependent methods that can obscure subtle cellular heterogeneity and the potential loss of biologically meaningful cells during stringent quality control (QC) filtering. This study aims to develop scSelector (v1.0), an interactive software toolkit designed to empower researchers to flexibly select and analyze cell populations directly from low-dimensional embeddings, guided by their expert biological knowledge. Methods: scSelector was developed using Python, relying on core dependencies such as Scanpy (v1.9.0), Matplotlib (v3.4.0), and NumPy (v1.20.0). It integrates an intuitive lasso selection tool with backend analytical module

SUBMITTER: Gao X 

PROVIDER: S-EPMC12841117 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature