OmicsPred
An atlas of genetic scores for prediction of multi-omics data
OmicsPred is a resource for predicting multi-omics data (proteomics, metabolomics, transcriptomics, etc.) directly from genotypes. To do this, we use extensive multi-omics data to train genetic scores using machine learning. Here, you can explore and download the genetic scores for a wide range of biomolecular traits in human blood as well as the summary statistics of their associations with key traits and diseases in the UK Biobank.
Currently, genetic scores have been trained on the INTERVAL cohort using Bayesian Ridge regression with validation performed on independent individuals from other cohorts or on withheld subsets of INTERVAL (more info below). Detailed methods and validation steps can be found here .
A Phenome-wide association analysis in UK biobank
Genetic scores in OmicsPred have been applied to UK Biobank to test for associations with complex phenotypes.
PheWAS page
Quantifying genetic control of pathways
Genetic scores for proteomics were applied to assess the extent to which biological pathways are genetically controlled using data at Reactome.
Browse Pathways
Data files
Genetic scores and Phenotype data files are publicly accessible for download on BoxTM.
Downloads pageREST API
Programmatic access to the OmicsPred metadata is available via a REST API.
REST API documentationWe would love to hear from you! To provide feedback or ask a question, you can contact the OmicsPred team here.
OmicsPred is under active development. If you use OmicsPred in your research, we ask that you cite our publication:
An atlas of genetic scores to predict multi-omic traits
Xu Y, Ritchie SC, Liang Y, Timmers PRHJ, Pietzner M, Lannelongue L, Lambert SA, Tahir UA, May-Wilson S, Foguet C, Johansson A, Surendran P, Nath AP, Persyn E, Peters JE, Oliver-Williams C, Deng S, Prins B, Luan J, Bomba L, Soranzo N, Di Angelantonio E, Pirastu N, Tai ES, van Dam RM, Parkinson H, Davenport EE, Paul DS, Yau C, Gerszten RE, Malarstig M, Danesh J, Sim X, Langenberg C, Wilson JF, Butterworth AS, Inouye M.
