@@ -2,7 +2,7 @@ Package: evaluomeR

 Type: Package

 Title: Evaluation of Bioinformatics Metrics

 URL: https://github.com/neobernad/evaluomeR

-Version: 1.6.5

+Version: 1.6.6

 Authors@R: c(

     person("José Antonio", "Bernabé-Díaz", email = "[email protected]", role = c("aut", "cre")),

     person("Manuel", "Franco", email = "[email protected]", role = "aut"),

@@ -21,6 +21,8 @@

 metricsCorrelations <- function(data, margins=c(0,10,9,11), getImages=TRUE) {

   data <- as.data.frame(assay(data))

+  data <- removeNAValues(data)

+  dfStats(data)

   MatCorr <- cor(data[,2:length(data)])

@@ -168,6 +168,39 @@ helperGetCBI <- function(cbi=pkg.env$cbi, krange) {

          }

   )

 }

+# Remove rows from a dataframe 'df' where for a certain column the row provides 'NA' value

+removeNAValues <- function(df, verbose=TRUE) {

+  rowNames = df[[1]]

+  affected = which(rowSums(is.na(df)) > 0)

+  if (verbose && length(affected) > 0) {

+    message("Warning: There are rows with NA values. I will remove these...")

+  }

+  for (row_i in affected) {

+    if (verbose) {

+      message("Row '", rowNames[row_i], "' was removed. NA values found in columns:")

+    }

+    for (column in colnames(df)) {

+      naDetected = is.na(df[row_i, column])

+      if (verbose && naDetected) {

+        message("- '", column,"' ")

+      }

+    }

+  }

+  df <- na.omit(df)

+  if (verbose) {

+    message("")

+  }

+  return (df)

+}

+

+# Basic stats of a dataframe

+dfStats <- function(df) {

+  message("Data loaded.\n",

+          "Number of rows: ", nrow(df), "\n",

+          "Number of columns: ", ncol(df), "\n\n"

+  )

+}

+

 #' @title Get supported CBIs in evaluomeR.

 #' @aliases evaluomeRSupportedCBI

 #' @description

@@ -208,6 +208,10 @@ runQualityIndicesSilhouette <- function(data, k.min=NULL, k.max=NULL, bs,

   if (is.null(k.min) && is.null(k.max) && is.null(k.set)) {

     stop("runQualityIndicesSilhouette: All k parameters are null!")

   }

+

+  data <- removeNAValues(data)

+  dfStats(data)

+

   datos.bruto=data

   names.metr=names(datos.bruto)[-c(1)]

   pkg.env$names.metr = names.metr

@@ -588,6 +592,7 @@ runSilhouetteIMG <- function(data, k) {

 }

 runSilhouetteTable <- function(data, k) {

+  data = removeNAValues(data, verbose=FALSE)

   names.metr = pkg.env$names.metr

   datos.bruto = data

   estable = pkg.env$estable

@@ -202,6 +202,10 @@ runStabilityIndex <- function(data, k.min=NULL, k.max=NULL, bs,

   if (is.null(k.min) && is.null(k.max) && is.null(k.set)) {

     stop("runStabilityIndex: All k parameters are null!")

   }

+

+  data <- removeNAValues(data)

+  dfStats(data)

+

   inversa=NULL

   m.stab.global = NULL

   m.stab.global.csv = NULL # To store new CSV output measures without altering legacy code

deleted file mode 100755

@@ -1,4 +0,0 @@

-library(evaluomeR)

-

-globalMetricDf = globalMetric(rnaMetrics, k.range = c(2,3), nrep=10, criterion="AIC", PCA=TRUE)

-globalMetricDf