# Introduction

![](https://248420963-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-M7YP6loPZ5G89uZfEwr%2F-MGx2i6s_Dgl_C-5m-Un%2F-MGx2ohnFyhJc7lm-BUk%2FAllelica_Marchio_Payoff_Colori.png?alt=media\&token=a9b73731-fad6-4ba6-9bb5-ffb77fabb60d)

Allelica enables users to impute Low-Coverage and Microarray data, discover new Polygenic Risk Scores (PRSs), validate their predictive performance and construct reports on individual PRS.

This user guide provides assistance for: 

* [Allelica Modules](#allelica-app)
* [Low Pass Impute (Illumina BaseSpace App)](#loss-pass-impute)

## Allelica Modules

The [Allelica Modules](https://saas.allelica.com/site/app) support the following functions:

* [Discover](https://allelica-1.gitbook.io/saas/allelica-app-user-guide/discover) 
* [Validate](https://allelica-1.gitbook.io/saas/allelica-app-user-guide/validate)
* [Predict](https://allelica-1.gitbook.io/saas/allelica-app-user-guide/predict)

One of the major barriers to PRS usage in clinical practice is the computational complexity needed to calculate per-individual PRSs. Extensive bioinformatics expertise is required to run the entire pipeline, from imputing genomic data, through quality control to result visualization. For these reasons, we developed Software as a Service (SaaS) for genomic risk prediction of complex diseases. Allelica's SaaS is fully automated, GDPR complaint and has been certified as a CE-marked medical device. Researchers wishing to use this SaaS can [contact](mailto:%20research@genomicriskscore.io) us directly.

The synergy of large Human Genome Biobanks with improved statistical methods to model genomes has revolutionized our ability to predict phenotypic expression from a person's genetic makeup. Allelica's SaaS provides a set of tools to estimate disease risk. The PRS metric that Allelica provides estimates the genetic risk of an individual to develop a disease based on a combination of a large number of genetic variants.

Allelica utilizes the largest prospective genotyped cohort available to date, the [UK Biobank](https://www.ukbiobank.ac.uk/). The predicted efficacy of this SaaS tool has [been confirmed against](https://www.biorxiv.org/content/10.1101/763722v2) Coronary Artery Disease (CAD), Breast Cancer (BC), and Prostate Cancer (PC) at the time of writing (May 2020).

## Low Pass Impute

[Low Pass Impute](https://allelica-1.gitbook.io/saas/impute-app-user-guide-and-benchmark/impute) allows users to analyze their data directly from [Illumina's dashboard](https://basespace.illumina.com/dashboard).


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