SUPR
pQTL and mQTL
Dnr:

NAISS 2023/23-492

Type:

NAISS Small Storage

Principal Investigator:

Jing Wang

Affiliation:

Linköpings universitet

Start Date:

2023-09-26

End Date:

2024-10-01

Primary Classification:

10203: Bioinformatics (Computational Biology) (applications to be 10610)

Webpage:

Allocation

Abstract

The aim of this project is to integrate genome, proteome and metabolome data to identify the pQTL and mQTL loci in healthy individuals. And then, they will be used for association analysis with complex diseases to further identify a number of biomarkers related to the risk of disease or treatment efficacy. Our data includes whole genome sequencing data, o-link proteome data and metabonimics data.