FoldGO

FoldGO performs fold-change-specific functional enrichment analysis of transcriptome data by applying Fold-change-Specific Enrichment Analysis (FSEA) to identify Gene Ontology (GO) terms associated with specific magnitudes of differential expression.

Key Features:

• Fold-Change Specificity: FSEA identifies GO terms enriched among gene sets with similar fold-change magnitudes, enabling functional interpretation tied to expression magnitude.
• Detection of Subtle Responses: The method reveals GO terms associated with weak or strong expression responses that may be overlooked by traditional algorithms such as SEA and GSEA.
• Identification of Regulated Intervals: FoldGO detects GO terms that are not enriched relative to the genome background but are strictly regulated within specific fold-change intervals.
• Response Pattern Characterization: The approach characterizes predominant response patterns among functionally related gene groups, emphasizing weak and strong responses.

Scientific Applications:

• Functional Annotation: Linking GO terms to fold-change magnitudes to elucidate how gene functions are modulated by stimuli including abiotic factors, mutations, treatments, and diseases.
• Research on Oncogenic Processes: Analyzing cancer-related transcriptomes to identify tightly coordinated gene responses that may indicate potential regulators, markers, or therapeutic targets in oncogenesis.

Methodology:

FSEA assesses GO terms shared by groups of genes with similar fold-change magnitudes and determines whether these changes are weakly, moderately, or strongly affected by the stimulus. The method highlights two predominant response patterns among functionally related gene groups: weak and strong responses.