I'm looking at integrating genome data (not expression) to pathways for analysis? Is there any examples of it been done before. Does it makes sense to link these two datasets for disease analysis without expression data?
You need to supply many more details for a precise answer.
In general, collecting variants onto sets of genes is all pathway analysis is. A pathway being some defined set of genes. You can download KEGG or pathjam or Gene Ontology as gene sets. See GSEA for "gene set enrichment analysis" or VAAST for a case-control population style variant enrichment method.
No, that is all gene set analysis is. Pathways analysis could indeed integrate different types of analysis (like network extensions, flux balance results) since pathways also know about the edges between the genes. But I agree you need a lot more information to give a sensible answer to Hranjeev's question.
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What hypothesis do you want to test? From what data are you starting?
Starting data would be an assembled human genome or its precursor - contigs. And the information is pathway networks which may be metabolic, regulatory, interaction, etc. Would we be able to link these information? And detect variations among different sample sets?
So, you are sequencing a bunch of samples, calling variants, and want to look at enrichment of variants in gene sets? Are these cancer samples with matched normals or just germline samples?
yes diseased vs normal