ePRS CLUSTER
Enabling Genomics
Discovery and Innovation
Accelerating scientific
discovery and knowledge
application via data integration.
Problem Statement
The current widely used methodology (GWAS) identifies statistically significant associations between scattered markers and a certain condition or trait, ignoring the fact that genes operate in networks and code for precise biological functions in specific tissues.
Data processing and analysis requires extensive resources limiting the possibility of innovation and discovery in genomics
The Solution
Our lab has created a novel approach to genomic profiling based on biological function of the genes. It aggregates genes into the networks considering the levels of co-expression and enables a new approach to create expression-based polygenic risk score (ePRS).
We have established expertise in several pipelines for advanced
functional genomics.
How it works: ePRS
Step 1
Identification of co-expression
networks using genome-wide,
tissue specific RNA sequencing
data from relevant animal
models or human postmortem
data
Step 2
Triangulation between gene network composition, gene variants from research participants and variant-gene expression association slope (GľeX)
Step 3
Investigation of main effectsof gene networks or gene network- environment interactions on the outcome
Key Partners
