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Single Trait Analysis
Hao Cheng edited this page Feb 17, 2021
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# Step 1: Load packages
using JWAS,DataFrames,CSV,Statistics,JWAS.Datasets
# Step 2: Read data
phenofile = dataset("phenotypes.csv")
pedfile = dataset("pedigree.csv")
genofile = dataset("genotypes.csv")
phenotypes = CSV.read(phenofile,DataFrame,delim = ',',header=true,missingstrings=["NA"])
pedigree = get_pedigree(pedfile,separator=",",header=true);
genotypes = get_genotypes(genofile,separator=',',method="BayesC");
first(phenotypes,5)
# Step 3: Build Model Equations
model_equation ="y1 = intercept + x1 + x2 + x2*x3 + ID + dam + genotypes"
model = build_model(model_equation);
# Step 4: Set Factors or Covariates
set_covariate(model,"x1");
# Step 5: Set Random or Fixed Effects
set_random(model,"x2");
set_random(model,"ID dam",pedigree);
# Step 6: Run Analysis
out=runMCMC(model,phenotypes);
# Step 7: Check Accuruacy
results = innerjoin(out["EBV_y1"], phenotypes, on = :ID)
accuruacy = cor(results[!,:EBV],results[!,:bv1])
To run analysis without genomic data, just remove "genotypes" in the model_equation from the script above.