The DISCOVER Module: Seamlessly building new polygenic risk scores

A user friendly, cloud-based computing solution to build state-of-the-art, publication ready polygenic risk scores

The DISCOVER module allows users to build their own polygenic risk scores (PRS) from genetic data and summary statistics from a Genome Wide Association Study (GWAS).

PRS needs genotype data with matched phenotype measurements together with GWAS summary statistics

Currently Allelica’s DISCOVER module includes genomic imputation. We’ve outlined how our IMPUTE module works here. Before using the DISCOVER module, genomic data needs to be imputed. So to use the DISCOVER module, you need the following three pieces of information:

  1. Measurements of the phenotype of interest in the Discovery dataset.
  2. Summary statistics from a GWAS on the trait or disease of interest.

Running the DISCOVER module: fast and flexible

With the three datasets above, we can start building a PRS for our disease of interest. There are many different ways to develop a PRS depending on how you use summary statistics. It’s important to remember that when a genetic variant is found to be associated with a phenotype in a GWAS, this is a statistical association. This means that an allele is not necessarily (and in fact is very rarely) causal to a given phenotype.

Next steps

The outputs of the DISCOVER module provide the user with a set of PRSs and a quantification of their predictive performance. Having the ability to choose the best PRS from three different methods allows users to align their research with best practice reporting standards. With the PRS in hand, users can now move on to either further validate their PRS in a population with a different ancestry using the VALIDATE module or alternatively move on to PRS prediction using the PREDICT module. These steps in Allelica’s full PRS pipeline will be covered in the next articles in this series describing our Software as a Service.

Allelica is a Software Genomics Company developing algorithms and digital tools to accelerate the integration of Polygenic Risk Score in the clinical practice