Video Tip of the Week: PheGenI, Phenotype-Genotype Integrator

The hunt for variations in genes and genomes has been both fruitful and frustrating. We can see genome variations in a variety of ways, but we can’t always connect them with a phenotype easily. And vice versa, of course. Another problem is that the kinds of data that we want to mine for further analysis is stored in different silos. PheGenI (Phenotype-Genotype Integrator) is an attempt to wrangle some silos together.

As they describe on their landing page:

The Phenotype-Genotype Integrator (PheGenI), merges NHGRI genome-wide association study (GWAS) catalog data with several databases housed at the National Center for Biotechnology Information (NCBI), including Gene, dbGaP, OMIM, GTEx and dbSNP.

The GWAS catalog is something I’ve turned to a number of times looking for samples of studies on different topics. It’s possible to search it from their site, or just browse around the enormous table. But as of right now, it’s just getting bigger and bigger: “As of 05/03/14, the catalog includes 1912 publications and 13270 SNPs“. Kind of a lot to browse at this point.

But of course we use Gene, dbGaP, OMIM, and dbSNP too (and we have training on these). GTEx stands for Genotype-Tissue Expression eQTL (expression quantitative trait loci) browser (I have got to write up something on GTEx).

At the recent Biology of Genomes meeting (#BoG14), this problem was illustrated thus:

So PhenGenI offers a way to navigate among these different types of resources more easily. You can learn more about the resource in this video, and from the paper linked below.

The place they recommend in the video for an overview of the goals of PheGenI: New Web Portal Expands View of Genetic Association Data for Researchers. And, of course, check out their paper below.

Quick link:

PheGenI homepage:


Ramos E.M., Hoffman D., Junkins H.A., Maglott D., Phan L., Sherry S.T., Feolo M. & Hindorff L.A. (2013). Phenotype–Genotype Integrator (PheGenI): synthesizing genome-wide association study (GWAS) data with existing genomic resources, European Journal of Human Genetics, 22 (1) 144-147. DOI: