diff --git a/vignettes/Interpret_ColocBoost_Output.Rmd b/vignettes/Interpret_ColocBoost_Output.Rmd index 925f73f..9c7f2cf 100644 --- a/vignettes/Interpret_ColocBoost_Output.Rmd +++ b/vignettes/Interpret_ColocBoost_Output.Rmd @@ -100,7 +100,6 @@ In this section, we will provide a detailed explanation of the components for de ```{r load-mixed-data} # Load example data -# Load example data data(Ind_5traits) data(Sumstat_5traits) # Create a mixed dataset @@ -222,13 +221,33 @@ plot(res$model_info$outcome_profile_loglik[[i]], type="p", col="#CC3333", lwd=2, - **`outcome_proximity_obj`**: trait-specific proximity smoothed objective for each trait. - **`outcome_coupled_best_update_obj`**: objective at the (coupled) best update variant for each outcome. -```{r objetive} -par(mfrow=c(2,5), mar=c(4,4,2,1)) -plot(res$model_info$outcome_proximity_obj[[1]], type="p", col="#3366CC", lwd=2, xlab="", ylab="Trait-specific Objective", main = paste0("Trait ", 1)) -for(i in 2:5){ -plot(res$model_info$outcome_proximity_obj[[i]], type="p", col="#3366CC", lwd=2, xlab="", ylab="", main = paste0("Trait ", i)) + +```{r objetive-proximity} +par(mfrow=c(2,3), mar=c(4,4,2,1)) +for(i in 1:5){ +plot(res$model_info$outcome_proximity_obj[[i]], type="p", col="#3366CC", lwd=2, xlab="", ylab="Trait-specific Objective", main = paste0("Trait ", i)) } -plot(res$model_info$outcome_coupled_best_update_obj[[1]], type="p", col="#CC3333", lwd=2, xlab="", ylab=paste0("Objetive at best update variant")) -for(i in 2:5){ plot(res$model_info$outcome_coupled_best_update_obj[[i]], type="p", col="#CC3333", lwd=2, xlab="", ylab="") } ``` +```{r objetive-best} +par(mfrow=c(2,3), mar=c(4,4,2,1)) +for(i in 1:5){ + plot(res$model_info$outcome_coupled_best_update_obj[[i]], type="p", col="#CC3333", lwd=2, xlab="", ylab=paste0("Objetive at best update variant"), main = paste0("Trait ", i)) +} +``` + + + +## 4. Trait-specific effects information (UCoS) + +TO-DO-LIST + +```{r ucos-details} +res <- colocboost(X = X, Y = Y, sumstat = sumstat, LD = LD, output_level = 2) +``` + +## 5. Diagnostic details + +TO-DO-LIST + +For more diagnosis of ColocBoost model fitting, please refer to our Tutorial (TO-DO-LIST).