Description
EM Bayesian Adaptive LASSO Variational Inference Based GWAS.
Description
Performs Genome-Wide Association Study (GWAS) analysis using Expectation-Maximization Bayesian Adaptive LASSO with Variational Inference (emBALVI). Includes genotype preprocessing, genomic relationship matrix construction, GWAS analysis, Manhattan and QQ plotting.s.
README.md
emBALVI
The goal of emBALVI is to ...
Installation
You can install the development version of emBALVI like so:
# FILL THIS IN! HOW CAN PEOPLE INSTALL YOUR DEV PACKAGE?
Example
This is a basic example which shows you how to solve a common problem:
library(emBALVI)
data(phenotypes_potatoyield)
data(snp_NN_10_hmp)
# Prepare genotype
hmp <- as.data.frame(t(snp_NN_10_hmp),stringsAsFactors = FALSE)
colnames(hmp) <- hmp[1, ]
hmp <- hmp[-1, ]
hmp$Taxa <- rownames(hmp)
snp_matrix <- hmp[, -ncol(hmp)]
rownames(snp_matrix) <- hmp$Taxa
X <- convert_to_dosage(snp_matrix)
G <- buildGRM(X)
pheno <- phenotypes_potatoyield
Y <- pheno$y
B <- model.matrix(~1, pheno)
results <- emBALVI(Y, X, B, G, max_iter = 5)
plot_manhattan(results)
qq_plot <- plot_qq(results)
print(qq_plot)
head(results)