@@ -27,7 +27,7 @@

 #'   abundance table.

 #' 

 #' @param pseudocount TRUE, FALSE, or a numeric value. When TRUE,

-#'   automatically adds the minimum positive value of \code{assay.type}.

+#'   automatically adds half of the minimum positive value of \code{assay.type}.

 #'   When FALSE, does not add any pseudocount (pseudocount = 0).

 #'   Alternatively, a user-specified numeric value can be added as pseudocount.

 #'

@@ -40,10 +40,9 @@

 #' }

 #' @details

 #'

-#' These \code{transformCount} function provides a variety of options for transforming abundance data.

-#' The transformed data is calculated and stored in a new \code{assay}. The previously available

-#' wrappers transformSamples, transformFeatures

-#' ZTransform, and relAbundanceCounts have been deprecated.

+#' \code{transformAssay} function provides a variety of options for

+#' transforming abundance data. The transformed data is calculated and stored

+#' in a new \code{assay}.

 #'

 #' The \code{transformAssay} provides sample-wise (column-wise) or feature-wise

 #' (row-wise) transformation to the abundance table

@@ -377,13 +376,11 @@ setMethod("transformAssay", signature = c(x = "SummarizedExperiment"),

             stop("The assay contains missing or negative values. ",

                  "'pseudocount' must be specified manually.", call. = FALSE)

         }

-        # If pseudocount TRUE, set it to

-        # a) counts: non-zero minimum value

-        # b) non-integers: half of non-zero minimum value

+        # If pseudocount TRUE, set it to  half of non-zero minimum value

         # else set it to zero.

         # Get min value

         value <- min(mat[mat>0])

-        value <- ifelse(all(mat %% 1 == 0), value, value / 2)

+        value <- value/2

         pseudocount <- ifelse(pseudocount, value, 0)

         # Report pseudocount if positive value

         if ( pseudocount > 0 ){

@@ -393,13 +390,16 @@ setMethod("transformAssay", signature = c(x = "SummarizedExperiment"),

     # Give warning if pseudocount should not be added

     # Case 1: only positive values

     if( pseudocount != 0 && all(mat > 0, na.rm = TRUE) ){

-        warning("The assay contains only positive values. ",

-                "Applying a pseudocount may be unnecessary.", call. = FALSE)

+        warning(

+            "The assay contains only positive values. ",

+            "Applying a pseudocount may be unnecessary.", call. = FALSE)

     }

     # Case 2: some negative values

     if( pseudocount != 0 && any(mat < 0, na.rm = TRUE) ){

-        warning("The assay contains some negative values. ",

-                "Applying a pseudocount may produce meaningless data.", call. = FALSE)

+        warning(

+            "The assay contains some negative values. ",

+            "Applying a pseudocount may produce meaningless data.",

+            call. = FALSE)

     }

     # Add pseudocount

     mat <- mat + pseudocount

@@ -56,7 +56,7 @@ transformation is applied sample (column) or feature (row) wise.

 abundance table.}

 \item{pseudocount}{TRUE, FALSE, or a numeric value. When TRUE,

-automatically adds the minimum positive value of \code{assay.type}.

+automatically adds half of the minimum positive value of \code{assay.type}.

 When FALSE, does not add any pseudocount (pseudocount = 0).

 Alternatively, a user-specified numeric value can be added as pseudocount.}

@@ -77,10 +77,9 @@ Variety of transformations for abundance data, stored in \code{assay}.

 See details for options.

 }

 \details{

-These \code{transformCount} function provides a variety of options for transforming abundance data.

-The transformed data is calculated and stored in a new \code{assay}. The previously available

-wrappers transformSamples, transformFeatures

-ZTransform, and relAbundanceCounts have been deprecated.

+\code{transformAssay} function provides a variety of options for

+transforming abundance data. The transformed data is calculated and stored

+in a new \code{assay}.

 The \code{transformAssay} provides sample-wise (column-wise) or feature-wise

 (row-wise) transformation to the abundance table

@@ -210,12 +210,14 @@ test_that("transformAssay", {

         expect_equal(assay(tse, "rel_pseudo1"), assay(tse, "rel_pseudo2"),

                      check.attributes = FALSE)

-        # Check that pseudocount = TRUE is the same as pseudocount = min

+        # Check that pseudocount = TRUE is the same as pseudocount = half of

+        # the minimum value

         # and pseudocount = FALSE is the same as pseudocount = 0

         tse <- transformAssay(tse, method = "relabundance", pseudocount = TRUE, name = "pseudo_true")

+        pseudocount <- (min(assay(tse, "counts")[assay(tse, "counts") > 0])) / 2

         tse <- transformAssay(

             tse, method = "relabundance", name = "pseudo_min",

-            pseudocount = (min(assay(tse, "counts")[assay(tse, "counts") > 0])),

+            pseudocount = pseudocount,

         )

         tse <- transformAssay(tse, method = "relabundance", pseudocount = FALSE, name = "pseudo_false")

         tse <- transformAssay(tse, method = "relabundance", pseudocount = 0, name = "pseudo_zero")