updated vignette and used custom glmpredict function for prediction of...

updated vignette and used custom glmpredict function for prediction of diagnostic signatures in validation data

R/diagnostic_sig.R

@@ -328,7 +328,9 @@ validateDiagnosticSignature_ <- function(validationstudylist,
 
       for (j in c("min", "1se")){
 
-        predicted <- predict(models[[i]][[j]]$model, v.data.all, type = "response")
+        predicted <- predictGLM_(model = models[[i]][[j]]$model,
+                                 test.x = v.data.all,
+                                 type = "response")
 
         confmat <- caret::confusionMatrix(data = factor(ifelse(as.numeric(as.character(predicted)) < 0.5, 0, 1)),
                                           reference = factor(diagnosis),

vignettes/sigident-Howto_Microarray.Rmd

@@ -1367,7 +1367,7 @@ dir.create(csvdir)
 species <- "Hs"
 OrgDb <- "org.Hs.eg.db"
 organism <- "hsa"
-pathwayid <- "hsa04110"
+pathwayid <- "hsa04151"
 
 # diagnostig signature
 seed <- 111
@@ -1435,11 +1435,11 @@ sigident::sigidentEnrichment(mergeset = mergeset,
                              csvdir = csvdir)
 ```
 ```{r eval = FALSE}
-filename <- paste0(plotdir, "/", organism, "04110.png")
+filename <- paste0(plotdir, "/", pathwayid, ".png")
 knitr::include_graphics(filename)
 ```
 ```{r eval = FALSE}
-filename <- paste0(plotdir, "/", organism, "04110.pathview.png")
+filename <- paste0(plotdir, "/", pathwayid, ".pathview.png")
 knitr::include_graphics(filename)
 ```
 
@@ -1466,6 +1466,31 @@ knitr::kable(
 )
 ```
 
+### Validation of the diagnostic signatures 
+
+Some users may validate the resulting models using new data sets. This can be conducted running the function `validateDiagnosticSignature_`. First, a list containing meta information on the validation study must be created.
+
+```{r eval = FALSE}
+validationstudylist <- list(studyname = "GSE30219",
+                            setid = 1, 
+                            targetcolname = "source_name_ch1",
+                            controllevelname = "Non Tumoral Lung",
+                            targetlevelname = "Lung Tumour")
+```
+
+```{r eval = FALSE}
+GSE30219_validation <- sigident::validateDiagnosticSignature_(
+  validationstudylist = validationstudylist,
+  models = diagnosticModels,
+  genes = genes,
+  idtype = idtype,
+  targetname = targetname,
+  controlname = controlname,
+  targetcol = targetcol,
+  datadir = datadir
+)
+```
+
 ## Run `sigidentPrognostic`-Function 
 
 ### First, define meta information lists