diff --git a/src/1.JWAS/src/MCMC/DRY.jl b/src/1.JWAS/src/MCMC/DRY.jl
index d3b8c1a2..1649fea3 100644
--- a/src/1.JWAS/src/MCMC/DRY.jl
+++ b/src/1.JWAS/src/MCMC/DRY.jl
@@ -41,6 +41,8 @@ function errors_args(mme,methods)
             error("GBLUP runs with genotypes.")
         elseif mme.M.genetic_variance == false
             error("Please provide values for the genetic variance for GBLUP analysis")
+        elseif estimatePi == true
+            error("GBLUP runs with estimatePi = false.")
         end
     end
     if mme.nModels > 1 && mme.M!=0
diff --git a/src/1.JWAS/src/MCMC/MCMC.jl b/src/1.JWAS/src/MCMC/MCMC.jl
index 1e0bb588..f1b6ceb2 100644
--- a/src/1.JWAS/src/MCMC/MCMC.jl
+++ b/src/1.JWAS/src/MCMC/MCMC.jl
@@ -150,8 +150,7 @@ function runMCMC(mme::MME,df;
                             sol                      = starting_value,
                             outFreq                  = printout_frequency,
                             output_samples_frequency = output_samples_frequency,
-                            output_file              = output_samples_file,
-                            update_priors_frequency  = update_priors_frequency)
+                            output_file              = output_samples_file)
         else
             error("No options!!!")
         end
diff --git a/src/1.JWAS/src/MCMC/MCMC_GBLUP.jl b/src/1.JWAS/src/MCMC/MCMC_GBLUP.jl
index 9623b4a8..066e429e 100644
--- a/src/1.JWAS/src/MCMC/MCMC_GBLUP.jl
+++ b/src/1.JWAS/src/MCMC/MCMC_GBLUP.jl
@@ -54,7 +54,7 @@ function MCMC_GBLUP(nIter,mme,df;
     D           = eigenG.values#eigenvalues
 
     dfEffectVar = mme.df.marker                #actually for genetic effect here
-    vEff        = mme.M.G                      #genetic variance
+    vEff        = mme.M.genetic_variance             #genetic variance
     scaleVar    = vEff*(dfEffectVar-2)/dfEffectVar   #scale factor for locus effects
     meanVara    = 0.0
     meanVarg    = 0.0
@@ -104,7 +104,6 @@ function MCMC_GBLUP(nIter,mme,df;
         if iter > burnin
             meanAlpha += (α - meanAlpha)/(iter-burnin)
         end
-
         ########################################################################
         # 2.1 Genetic Covariance Matrix (Polygenic Effects) (variance.jl)
         ########################################################################
@@ -158,7 +157,7 @@ function MCMC_GBLUP(nIter,mme,df;
             println("\nPosterior means at iteration: ",iter)
             println("Residual variance: ",round(meanVare,digits=6))
             if mme.pedTrmVec !=0
-              println("Polygenic effects covariance matrix \n",round(G0Mean,digits=3))
+              println("Polygenic effects covariance matrix \n",round.(G0Mean,digits=3))
             end
             println("Genetic variance (G matrix): ",round(meanVara,digits=6))
             println("Genetic variance (GenSel): ",round(meanVarg,digits=6))