diff --git a/R/challengeR.R b/R/challengeR.R
index 45d53d0..e437d2e 100644
--- a/R/challengeR.R
+++ b/R/challengeR.R
@@ -1,207 +1,211 @@
 # Copyright (c) German Cancer Research Center (DKFZ)
 # All rights reserved.
 #
 # This file is part of challengeR.
 #
 # challengeR is free software: you can redistribute it and/or modify
 # it under the terms of the GNU General Public License as published by
 # the Free Software Foundation, either version 2 of the License, or
 # (at your option) any later version.
 #
 # challengeR is distributed in the hope that it will be useful,
 # but WITHOUT ANY WARRANTY; without even the implied warranty of
 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
 # GNU General Public License for more details.
 #
 # You should have received a copy of the GNU General Public License
 # along with challengeR. If not, see <https://www.gnu.org/licenses/>.
 
 #' Constructs a challenge object
 #'
 #' Constructs an S3 object to represent the configuration of an assessment data set originating from a benchmarking competition (so-called "challenge").
 #'
 #' @section Assessment data set:
 #' The toolkit provides visualization approaches for both challenges designed around a single task (single-task challenges) and for challenges comprising multiple tasks (multi-task challenges).
 #' For a single-task challenge, the assessment data set (argument \code{object}) requires the following columns:
 #' \itemize{
 #'   \item test case identifier (string or numeric)
 #'   \item algorithm identifier (string or numeric)
 #'   \item performance value (numeric)
 #' }
 #'
 #' For a multi-task challenge, the assessment data set (argument \code{object}) requires the following columns:
 #' \itemize{
 #'   \item task identifier (string or numeric)
 #'   \item test case identifier (string or numeric)
 #'   \item algorithm identifier (string or numeric)
 #'   \item performance value (numeric)
 #' }
 #'
 #' @section Sanity check:
 #' It is highly recommended that the sanity check is not disabled when the data set is provided initially.
 #' It checks that:
 #' \itemize{
 #'   \item performance values are numeric (if not, raises error)
 #'   \item algorithm performances are observed for all cases (if not, adds them as NA and emits a message)
 #'   \item cases appear only once for the same algorithm (if not, raises error)
 #' }
 #' If the argument \code{na.treat} for treatment of NA is specified, NAs will be handled respectively.
 #'
 #' It might be reasonable to disable the sanity check for further computations (e.g., for performance reasons
 #' during bootstrapping (\code{\link{bootstrap.ranked.list}}) where cases are actually allowed to appear more than once for the same algorithm).
 #'
 #' @param object A data frame containing the assessment data.
 #' @param case A string specifying the name of the column that contains the case identifiers.
 #' @param algorithm A string specifying the name of the column that contains the algorithm identifiers.
 #' @param value A string specifying the name of the column that contains the performance values.
 #' @param by A string specifying the name of the column that contains the task identifiers. Required for multi-task data set.
 #' @param taskName A string specifying the task name for single-task data set that does not contain a task column.
 #'   This argument is optional for a single-task data set and is ignored for a multi-task data set.
 #' @param annotator If multiple annotators annotated the test cases, a string specifying the name of the column that contains the annotator identifiers. Only applies to rang-then-aggregate. Use with caution: Currently not tested.
 #' @param smallBetter A boolean specifying whether small performance values indicate better algorithm performance.
 #' @param na.treat Indicates how missing perfomance values are treated if sanity check is enabled. It can be 'na.rm', numeric value or function.
 #'   For a numeric value or function, NAs will be replaced by the specified values. For 'na.rm', rows that contain missing values will be removed.
 #' @param check A boolean to indicate to perform a sanity check of the specified data set and arguments if set to \code{TRUE}.
 #'
 #' @return An S3 object to represent the configuration of an assessment data set.
 #'
 #' @examples
 #' # single-task data set
 #'
 #' # multi-task data set
 #'
 #' @export
 as.challenge=function(object,
                       case,
                       algorithm,
                       value,
                       by=NULL,
                       taskName=NULL,
                       annotator=NULL,
                       smallBetter=FALSE,
                       na.treat=NULL, # optional
                       check=TRUE) {
 
   object=as.data.frame(object[,c(value, algorithm, case, by, annotator)])
   object[[algorithm]] <- as.factor(object[[algorithm]])
   # sanity checks
   if (check) {
  
     if (!is.null(by) && !is.null(taskName)) {
       warning("Argument 'taskName' is ignored for multi-task data set.")
     }
 
     # Add task column for data set without task column by using the specified task name.
     if (is.null(by) && !is.null(taskName)) {
       taskName <- trimws(taskName)
 
       if (taskName == "") {
         stop("Argument 'taskName' is empty.")
       }
 
       object <- cbind(task=taskName, object)
       by = "task"
     }
 
     # Add task column for data set without task column by using a dummy task name.
     if (is.null(by) && is.null(taskName)) {
       object <- cbind(task="dummyTask", object)
       by = "task"
     }
 
     object=splitby(object,by=by)
     object=lapply(object,droplevels)
     missingData = n.missing = list()
     for (task in names(object)) {
       if (!all(is.numeric(object[[task]][[value]]))) stop("Performance values must be numeric.")
 
       n.missing[[task]] <- sum(is.na(object[[task]][[value]])) # already missing before na.treat; for report
       if (n.missing[[task]]>0) message("Note: ", n.missing, " missing cases have been found in the data set.")
       # check for missing cases
         missingData[[task]]=object[[task]] %>%
           expand(!!as.symbol(algorithm),
                  !!as.symbol(case))%>%
           anti_join(object[[task]],
                     by=c( algorithm,case))
         if (nrow(missingData[[task]])>0) {
              if (length(object) == 1 ) { # single task
-            message("Performance of not all algorithms has been observed for all cases. Therefore, missings have been inserted in the following cases:")
+            message("Performance of not all algorithms has been observed for all cases.\nTherefore, missings have been inserted in the following cases:")
           } else { # multi task
             message("Performance of not all algorithms has been observed for all cases in task '",
                     task,
-                    "'. Therefore, missings have been inserted in the following cases:")
+                    "'.\nTherefore, missings have been inserted in the following cases:")
 
           }
           print(as.data.frame(missingData[[task]]))
           object[[task]]=as.data.frame(object[[task]] %>%
                                          complete(!!as.symbol(by),
                                                   !!as.symbol(algorithm),
                                                   !!as.symbol(case)))
         }
       # check duplicate cases
          all1=apply(table(object[[task]][[algorithm]],
                            object[[task]][[case]]),
                      2,
                      function(x) all(x==1))
           if (!all(all1)) {
             n.duplicated <- sum(all1!=1)
 
             if (length(object) == 1 ) { # single task
               if (n.duplicated/length(all1) >= 1/5) { # at least a quarter of the cases is duplicated
                 stop ("The following case(s) appear(s) more than once for the same algorithm. Please revise. ",
                       "Or are you considering a multi-task challenge and forgot to specify argument 'by'?\n",
                       "Case(s): ",
                       paste(names(which(all1!=1)), collapse=", ")
                       )
               } else {
                 stop ("The following case(s) appear(s) more than once for the same algorithm. Please revise.\n",
                       "Case(s): ",
                       paste(names(which(all1!=1)), collapse=", ")
                       )
               }
             } else { # multi task
               stop ("The following case(s) appear(s) more than once for the same algorithm in task '",
                     task, "'. Please revise.\n",
                      "Case(s): ",
                     paste(names(which(all1!=1)), collapse=", ")
                     )
 
             }
           }
 
       if (!is.null(na.treat)) {
         if (is.numeric(na.treat)) object[[task]][,value][is.na(object[[task]][,value])]=na.treat
         else if (is.function(na.treat)) object[[task]][,value][is.na(object[[task]][,value])]=na.treat(object[[task]][,value][is.na(object[[task]][,value])])
         else if (is.character(na.treat) && na.treat=="na.rm") object[[task]]=object[[task]][!is.na(object[[task]][,value]),]
       }
     }
   }
-  if (check==TRUE && (any(sapply(missingData, function(x) nrow(x))>0) |any(n.missing>0)))  {
-    if (is.null(na.treat)) message("For aggregate-then-rank, na.treat will have to be specified. ",
-                                   "For rank-then-aggregate, missings will implicitly lead to the algorithm ranked last for the missing test case.",
-                                   "na.treat obligatory if report is intended to be compiled."
-                               )
-    else if (is.numeric(na.treat)) message("All missings have been replaced by the value ", na.treat,".\n")
+
+  if (check==TRUE && (any(sapply(missingData, function(x) nrow(x))>0) | any(n.missing>0)))  {
+    ##
+    ## The message below was disabled because it can cause misinformation even we supply na.treat to as.challenge object
+    ##
+    # if (is.null(na.treat)) message("For aggregate-then-rank, na.treat will have to be specified. ",
+    #                                "For rank-then-aggregate, missings will implicitly lead to the algorithm ranked last for the missing test case.",
+    #                                "na.treat obligatory if report is intended to be compiled."
+    #                            )
+    if (is.numeric(na.treat)) message("All missings have been replaced by the value ", na.treat,".\n")
     else if (is.character(na.treat) && na.treat=="na.rm") message("All missings have been removed.")
     else if (is.function(na.treat)) {
       message("Missings have been replaced using function ")
       print(na.treat)
     }
   }
 
   if (check==TRUE){
     attr(object,"n.missing")=n.missing
     attr(object,"missingData")=missingData
   }
   attr(object,"na.treat")=na.treat
 
   attr(object,"algorithm")=algorithm
   attr(object,"value")=value
   attr(object,"case")=case
   attr(object,"annotator")=annotator
   attr(object,"by")=by
   attr(object,"smallBetter")=smallBetter
   attr(object,"check")=check
   class(object)=c("challenge", class(object))
   object
 }