Uncovering disease-related multicellular pathway modules on large-scale single-cell transcriptomes with scPAFA.

ABSTRACT: Pathway analysis is a crucial analytical phase in disease research on single-cell RNA sequencing (scRNA-seq) data, offering biological interpretations based on prior knowledge. However, currently available tools for generating cell-level pathway activity scores (PAS) exhibit computational inefficacy in large-scale scRNA-seq datasets. Additionally, disease-related pathways are often identified through cross-condition comparisons within specific cell types, overlooking potential patterns that involve multiple cell types. Here, we present single-cell pathway activity factor analysis (scPAFA), a Python library designed for large-scale single-cell datasets allowing rapid PAS computation and uncovering biologically interpretable disease-related multicellular pathway modules, which are low-dimens

SUBMITTER: Huang Z 

PROVIDER: S-EPMC11569158 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature