Unlocking biological insights from differentially expressed genes: Concepts, methods, and future perspectives.

Area of Science:

• Transcriptome analysis
• Genomics
• Bioinformatics

Background:

• Identifying differentially expressed genes (DEGs) is crucial for understanding biological processes.
• Interpreting large DEG lists is challenging, despite existing methods like gene ontology and pathway enrichment.
• Comprehensive guidelines for DEG interpretation are lacking.

Purpose of the Study:

• To provide an overview of concepts and methodologies for biological interpretation of DEGs.
• To address limitations and future perspectives of DEG analysis approaches.
• To introduce DEGMiner, a tool integrating over 300 databases and tools for DEG analysis.

Main Methods:

• Review of existing and emerging DEG interpretation strategies.
• Development and integration of databases and tools within DEGMiner.
• Focus on enhancing contextual understanding of DEGs.

Main Results:

• Identification of essential concepts and methodologies for DEG interpretation.
• Highlighting limitations and future directions in the field.
• Development of DEGMiner to facilitate DEG data mining.

Conclusions:

• This review offers guidance for exploring DEGs to accelerate biological discovery.
• DEGMiner assists users in extracting insights from extensive DEG datasets.
• The findings support systematic mining of biological information within genomes.