NBF {PAGWAS} | R Documentation |
A vector of the computed Bayes factors for the tested pathways.
NBF(y, G, P, a, b, s2, nu)
y |
Response vector of length N |
G |
Genotype matrix, with N rows and L columns (number of tested SNPs) |
P |
Pathway matrix, with L columns and M columns (number of tested pathways) |
a |
Hyper-parameter of the variance assumed for the integrated out SNP effects |
b |
Hyper-parameter of the variance assumed for the pathway effects |
s2 |
Hyper-parameter of the Inverse-Chi-squared distribution assumed for the variance of the response vector |
nu |
Hyper-parameter of the Inverse-Chi-squared distribution assumed for the variance of the response vector |
A vector of the computed Bayes factors of the same length as the number of tested pathways
Evangelou, M., Dudbridge, F., Wernisch, L. (2014). Two novel pathway analysis methods based on a hierarchical model. Bioinformatics, 30(5), 690 - 697.
## Not run:
data(genotypes)
G=genotypes
data(pathways)
data(SNPs)
data(genes)
snps.genes=snps.to.genes(SNPs,genes,distance=0)
snps.paths=snps.to.pathways(pathways,snps.genes)
P=create.pathway.df(G,snps.paths)
y=rnorm(nrow(G),mean=0,sd=10)
NBF(y,G,P,a,b,s2,nu)
## End(Not run)