DeepGSEA: explainable deep gene set enrichment analysis for single-cell transcriptomic data.

ABSTRACT:

Motivation

Gene set enrichment (GSE) analysis allows for an interpretation of gene expression through pre-defined gene set databases and is a critical step in understanding different phenotypes. With the rapid development of single-cell RNA sequencing (scRNA-seq) technology, GSE analysis can be performed on fine-grained gene expression data to gain a nuanced understanding of phenotypes of interest. However, with the cellular heterogeneity in single-cell gene profiles, current statistical GSE analysis methods sometimes fail to identify enriched gene sets. Meanwhile, deep learning has gained traction in applications like clustering and trajectory inference in single-cell studies due to its prowess in capturing complex data patterns. However, its use in GSE analysis remains limited, d

SUBMITTER: Xiong G 

PROVIDER: S-EPMC11236288 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature