Pathways and GSEA Workbench
With Qlucore Omics Explorer it is easy to incorporate functional information such as pathways, gene sets and other structured lists of biologically functional information in your analysis.
Pathway analysis, or gene set analysis, is a collective name for methods aimed at statistical analysis of a collection of genes, rather than single genes. Typically, genes are grouped together in a collection if they have something in common, for example, if they are part of the same biological pathway, or if they are all located close to each other along the genome. Given such a collection of genes, gene set analysis is often used to examine whether the expression levels of the genes in the collection are 'collectively' significantly associated with a given covariate (for example, whether the genes in the collection are generally differentially expressed between two conditions).
How to undertake pathway and gene set analysis in Qlucore Omics Explorer is by using the integrated Gene Set Enrichment Analysis (GSEA) workbench. Close integration with all other functionality in the program and optimized performance provide extensive benefits over stand-alone solutions.
To begin the functional analysis, two components are needed: a data set with measurements of the features (variables) and the functional information such as pathways. Functional information is often acquired from open online repositories such as MSigDB and Reactome.
In Qlucore Omics Explorer you perform the GSEA analysis by starting “New GSEA Workbench” from the View menu, selecting your ranking criteria and pressing “Run”. It couldn’t be easier!
Login to read more about pathway analysis with Qlucore Omics Explorer in the “How to Do Pathway analysis” document where you will also find recorded webinars of various topics.