Description
The Polygenic Risk Scores eMERGE track shows variants that are part of selected polygenic risk
scores for ten common diseases. Polygenic risk scores (PRS) have clinical utility and are the result
of many years of GWAS studies. A score is given for a combination of SNPs to calculate the risk of
getting a disease in a healthy population. The risk scores were selected by the NHGRI eMERGE project, and the selection process is described in
Lennon et al. 2023. Many PRS models were evaluated, and the 9 models shown here
were selected based on quality and are part of this track:
- Asthma
- Atrial Fibrillation
- Breast Cancer
- Coronary Heart Disease
- Chronic Kidney Disease
- Hypercholesterolemia
- Prostate Cancer
- T1 Diabetes
- T2 Diabetes
The BMI (body mass index) model cannot currently be shown on the browser, pending publication.
Methods
Text files provided by eMerge were converted to bigBed format. The scripts are available in our
GitHub repo.
Data access
The raw data can be explored interactively with the Table Browser
or the Data Integrator. The data can be accessed from scripts
through our API, the track name is "prsEmerge".
For automated download and analysis, the genome annotations are stored in files that can be
obtained from our
download server. The data is stored in our bigBed
format. Individual regions or the whole genome annotation can be obtained using our tool
bigBedToBed which can be compiled from the source code or downloaded as a precompiled
binary for your system. Instructions for downloading source code and binaries can be found
here.
The tool can be used to obtain all features or only features within a given range, e.g.
bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/hg19/prsEmerge/t2d.bb -chrom=chr21 -start=0 -end=100000000 stdout
Credits
Thanks to Elisabeth McNally for advice, to Zia Truong for building this track and to Niall Lennon
for sharing the data with us.
References
Lennon NJ, Kottyan LC, Kachulis C, Abul-Husn N, Arias J, Belbin G, Below JE, Berndt S, Chung W,
Cimino JJ et al.
Selection, optimization, and validation of ten chronic disease polygenic risk scores for clinical
implementation in diverse populations.
medRxiv. 2023 Jun 5;.
PMID: 37333246; PMC: PMC10275001
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