1.
Weighted SNP
Correlation
Network Analyisis

2.
• Polygenic risk scores or genome-wide scores help examine the joint
associations of genetic markers. Traditional methods involve summing
weighted allele counts. They don't capture the complex nature of biology.
• I illustrate how we can use the weighted SNP correlation network analysis
(WSCNA) method to build SNP networks from GWAS data. With this
method, we can generate network-specific polygenic scores, examine
network topology to identify hub SNPs, and gain biological insights into
complex traits.
• This method may help examine gene scores by environmental effect.

3.
Methodology
I divided the process into four steps.
1. Data pre-processing and cleaning
2. Resampling and data generation
3. Network construction
4. Data analysis