Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Polygenic Traits01:18

Polygenic Traits

64.6K
When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
64.6K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

12.3K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
12.3K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

478
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
478
Improving Translational Accuracy02:07

Improving Translational Accuracy

8.5K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
8.5K
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

13.9K
A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
13.9K
Genomics02:02

Genomics

35.7K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
35.7K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Genetic and transcriptomic determinants of disseminated coccidioidomycosis identify a founder variant in <i>NLRX1</i> and ancestry-specific rare variants in immune response genes.

medRxiv : the preprint server for health sciences·2026
Same author

Quantitative trait loci mapping of gene expression and chromatin accessibility in primary fibroblasts reveals shared allelic effects between Latin American and European ancestries.

BMC genomics·2026
Same author

Challenges and recommendations in establishing national human diversity genomic projects.

Nature methods·2026
Same author

Leveraging tumor dynamics to discover mutations influencing progression and treatment response for precision oncology.

Genome medicine·2026
Same author

Genome-wide analysis implicates inner ear development in Ménière disease.

American journal of human genetics·2026
Same author

Comparison of infrared and solid-state <sup>13</sup>C NMR spectroscopy for assessing soil organic carbon composition following hydrofluoric acid treatment.

Fundamental research·2026

Related Experiment Video

Updated: May 26, 2025

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.1K

PennPRS: a centralized cloud computing platform for efficient polygenic risk score training in precision medicine.

Jin Jin1,2, Bingxuan Li3, Xiyao Wang4

  • 1Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.

Medrxiv : the Preprint Server for Health Sciences
|February 24, 2025
PubMed
Summary

PennPRS is a new cloud platform for training polygenic risk scores (PRS) without individual genetic data. This tool enhances accessibility to PRS model training, benefiting precision medicine research globally.

Keywords:
Cloud computingGWAS CatalogPolygenic risk scoresPrecision medicineResampling-based pseudo-training

More Related Videos

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
10:28

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

15.0K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.0K

Related Experiment Videos

Last Updated: May 26, 2025

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.1K
Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
10:28

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

15.0K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.0K

Area of Science:

  • Genetics
  • Computational Biology
  • Precision Medicine

Background:

  • Polygenic risk scores (PRS) are crucial for disease risk prediction and stratification in precision medicine.
  • Widespread adoption of PRS is hindered by computational resource limitations, complex methodologies, and data privacy concerns.

Purpose of the Study:

  • To introduce PennPRS, a scalable cloud platform for accessible online polygenic risk score (PRS) model training.
  • To enable PRS model training without individual-level genetic data through novel pseudo-training algorithms.

Main Methods:

  • Development of pseudo-training algorithms for multiple PRS methods and ensemble approaches.
  • Validation using extensive simulations and large-scale real data analyses across over 6,000 phenotypes.
  • Implementation of a cloud-based platform supporting single- and multi-ancestry PRS training with seven methods.

Main Results:

  • PennPRS enables PRS model training without direct access to individual genetic data.
  • The platform supports user data uploads and integration with the GWAS Catalog (over 27,000 datasets).
  • Trained PRS models for over 8,000 phenotypes are publicly accessible, along with their weights.

Conclusions:

  • PennPRS offers a novel cloud computing solution to democratize PRS applications.
  • The platform addresses computational resource disparities, improving accessibility for the global PRS research community.
  • Facilitates broader implementation of PRS in precision medicine research and clinical practice.