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MetaPhat is an open sourced program to detect optimal subset traits on lead SNP associations from multiple biomarker GWAS summary results. Best traits are derived from systematic decomposing multivariate associations into central traits based on optimal BIC and P-value from multivariate CCA models. SNP trace results are plotted and clustered to dissect and improve the specificity of mv phenotype-genotype associations.
released with LD function https://sourceforge.net/projects/meta-pheno-association-tracer/files/Dist/meta_phat.tar.gz/download
Quick start https://sourceforge.net/p/meta-pheno-association-tracer/wiki/Quick%20Start
Inputs https://sourceforge.net/p/meta-pheno-association-tracer/wiki/Inputs
Global Lipids example https://sourceforge.net/p/meta-pheno-association-tracer/wiki/Installation_global_lipids
Cite: Lin et al. (2020) MetaPhat: Detecting and decomposing multivariate associations from univariate genome-wide association statistics. Front. Genet. doi: 10.
Features
- multivariate genome-wide trait analysis
- p-value and BIC based optimal trait subset selection
- trait decomposition trace plots
- Population and LD block clumping
- lead SNP and driver trait summary file
- snp-snp trait rank spearman cluster
Project Samples
