Transcriptomic meta-analysis to identify potential antifungal targets in Candida albicans.

ABSTRACT:

Background

Candida albicans is a fungal pathogen causing human infections. Here we investigated differential gene expression patterns and functional enrichment in C. albicans strains grown under different conditions.

Methods

A systematic GEO database search identified 239 "Candida albicans" datasets, of which 14 were selected after rigorous criteria application. Retrieval of raw sequencing data from the ENA database was accompanied by essential metadata extraction from dataset descriptions and original articles. Pre-processing via the tailored nf-core pipeline for C. albicans involved alignment, gene/transcript quantification, and diverse quality control measures. Quality assessment via PCA and DESeq2 identified significant genes (FDR < = 0.05, log2-fold change > = 1 or <= -

SUBMITTER: Hefny ZA 

PROVIDER: S-EPMC10898158 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature