Contents
What is go KEGG?
Gene ontology (GO) is a major bioinformatics tool that standardizes representation and the product attributes of genes across species [23]. The Kyoto Encyclopedia of Genes and Genomes (KEGG) [24, 25] pathway database is a collection of manually drawn diagrams and comprehensive inferences for pathway mapping.
How do you use KEGG?
You can use the KEGG database directly @ https://www.genome.jp/kegg/. Click on the KEGG mapping displayed on the left side, then click on the search pathway, and paste the gene ID in the displayed box. finally, execute to get the results of your analysis. It is user friendly and works perfectly.
How is GSEA used to analyze gene expression?
Gene Set Enrichment Analysis (GSEA) is a powerful analytical method for interpreting gene expression data. It evaluates cumulative changes in the expression of groups of multiple genes defined based on prior biological knowledge.
What’s the best way to rank genes in GSEA?
However, for GSEA we usually use a prerank-list (a text file with extension ‘.rnk’) where gene official symbols were ranked based on p-value and we also provide the direction based on Fold change. There is a good repository of geneset collections at Broad institute’s MSig database http://www.broadinstitute.org/gsea/msigdb/index.jsp .
How to specify gene sets on GSEA-MSigDB?
▪ Specify gene sets that list genes by their HGNC gene symbol. The gene sets on the GSEA-MSigDB file servers are from the Molecular Signature Database (MSigDB) and list genes by HGNC gene symbol. ▪ Specify a chip annotation file that maps the probe identifiers in your expression dataset to their HGNC gene symbols.
How does the chip annotation work in GSEA?
GSEA uses the chip annotation file to collapse each probe set into a single vector for the gene, which gets identified by its HGNC gene symbol, and to include HGNC gene annotations in the analysis report. This approach is recommended by the GSEA team; therefore, by default the Collapse/Remap to gene symbols parameter is set to “Collapse”.