WebGestalt 2024: faster gene set analysis and new support for metabolomics and multi-omics
Baylor College of Medicine · Gladstone Institutes
Abstract
Enrichment analysis, crucial for interpreting genomic, transcriptomic, and proteomic data, is expanding into metabolomics. Furthermore, there is a rising demand for integrated enrichment analysis that combines data from different studies and omics platforms, as seen in meta-analysis and multi-omics research. To address these growing needs, we have updated WebGestalt to include enrichment analysis capabilities for both metabolites and multiple input lists of analytes. We have also significantly increased analysis speed, revamped the user interface, and introduced new pathway visualizations to accommodate these updates. Notably, the adoption of a Rust backend reduced gene set enrichment analysis time by 95% from…
Citation impact
- FWCI
- 73.80
- Percentile
- 100%
- References
- 32
Authors
6Topics & keywords
- Python (programming language)
- Metabolomics
- Biology
- Computational biology
- Omics
- Proteomics
- Set (abstract data type)
- Genomics