Integrating single-cell RNA-Seq and machine learning to dissect tryptophan metabolism in ulcerative colitis.

ABSTRACT:

Background

Ulcerative colitis (UC) is a persistent inflammatory bowels disease (IBD) characterized by immune response dysregulation and metabolic disruptions. Tryptophan metabolism has been believed as a significant factor in UC pathogenesis, with specific metabolites influencing immune modulation and gut microbiota interactions. However, the precise regulatory mechanisms and key genes involved remain unclear.

Methods

AUCell, Ucell, and other functional enrichment algorithms were utilized to determine the activation patterns of tryptophan metabolism at the UC cell level. Differential analysis identified key genes associated with tryptophan metabolism. Five machine learning algorithms, including Random Forest, Boruta algorithm, LASSO, SVM-RFE, and GBM were integrated to ident

SUBMITTER: Chen G 

PROVIDER: S-EPMC11662780 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature