Curating gene sets: challenges and opportunities for integrative analysis.

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Genomic data interpretation often requires analyzing gene sets, not just individual genes.
• Curation of gene sets presents unique challenges compared to individual gene curation.
• Existing methods may lack flexibility and precision in gene set management.

Purpose of the Study:

• To present a literature curation workflow for gene sets using the GeneWeaver (GW) platform.
• To describe GW's features enabling precise and flexible gene set curation.
• To demonstrate the value of curated gene sets through functional analysis.

Main Methods:

• Developed a literature curation workflow for gene sets.
• Implemented GW as a data repository and analysis platform.
• Utilized GW's curation interface for workflow management and gene set release.

Main Results:

• GeneWeaver facilitates flexible and precise gene set curation from peer-reviewed data.
• Analysis of independently curated gene sets for the integrated stress response showed significant Jaccard similarity.
• GW provides reproducible analysis tools for functional investigation of user-submitted gene sets.

Conclusions:

• Gene set curation in GW enhances genomic data interpretation.
• The platform supports collaborative curation and analysis of biological data.
• GW offers a valuable resource for researchers studying gene sets and biological phenomena.