CF-Seq

CF-Seq reanalyzes RNA sequencing datasets from cystic fibrosis pathogens by integrating public RNA-seq studies and enabling differential gene expression analysis across experimental conditions.

Key Features:

• Integrated RNA-seq Compendium: Aggregates 128 RNA-seq studies comprising 1,322 samples from 13 cystic fibrosis pathogens sourced from the Gene Expression Omnibus (GEO).
• Study Filtering by Experimental Attributes: Enables dataset filtering based on pathogen strain, treatment condition, and growth media.
• Gene Expression Visualization: Provides visualization of gene expression patterns within individual RNA-seq studies.
• Differential Gene Expression Analysis: Performs differential gene expression analysis across selected experimental conditions.

Scientific Applications:

• Cystic Fibrosis Pathogen Transcriptomics: Investigates gene expression patterns in pathogens associated with cystic fibrosis infections.
• Treatment Response Analysis: Examines transcriptional responses of pathogens to antimicrobial treatments.
• Comparative Transcriptomic Studies: Compares RNA-seq datasets across strains, growth media, and experimental conditions.

Methodology:

CF-Seq integrates RNA-seq datasets from the Gene Expression Omnibus and performs differential gene expression analysis and visualization of transcriptomic profiles across experimental conditions.