Polygenic risk score comparator ( PRScomp ): Test population vs. worldwide populations
International Journal of Medical Informatics, ISSN: 1386-5056, Vol: 183, Page: 105333
2024
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
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Article Description
Polygenic risk scores (PRS) are a powerful tool for predicting an individual's genetic risk for complex diseases. We have developed a web service ( PRScomp ) as a user-friendly tool to evaluate PRS of the user own population and compare it with worldwide populations. A disease/trait database has been constructed from GWAS Catalog summary statistics. Genotype data of test population is uploaded and merged with the reference dataset (1000 Genome Project and Human Genome Diversity Project) to obtain a file including the common SNPs. The user can select a disease/trait from the database and a curated set of risk markers is used to calculate summatory PRS. Distribution of z-scored PRS values is presented in publication-ready plots and text files that can be downloaded. PRScomp can be useful for public health decision-making by identifying population-specific genetic risk factors and informing the development of targeted interventions for at-risk populations.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S1386505623003519; http://dx.doi.org/10.1016/j.ijmedinf.2023.105333; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85182426403&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/38184939; https://linkinghub.elsevier.com/retrieve/pii/S1386505623003519; https://dx.doi.org/10.1016/j.ijmedinf.2023.105333
Elsevier BV
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