@@ -1,6 +1,6 @@

 Package: mia

 Type: Package

-Version: 1.13.43

+Version: 1.13.44

 Authors@R:

     c(person(given = "Felix G.M.", family = "Ernst", role = c("aut"),

              email = "felix.gm.ernst@outlook.com",

@@ -1,4 +1,5 @@

-#' Convert a \code{TreeSummarizedExperiment} object to/from \sQuote{BIOM} results

+#' Convert a \code{TreeSummarizedExperiment} object to/from \sQuote{BIOM}

+#' results

 #'

 #' For convenience, a few functions are available to convert BIOM, DADA2 and 

 #' phyloseq objects to 

@@ -9,8 +10,8 @@

 #' 

 #' @param prefix.rm \code{Logical scalar}. Should

 #' taxonomic prefixes be removed? The prefixes is removed only from detected

-#' taxa columns meaning that \code{rank.from.prefix} should be enabled in the most cases.

-#' (Default: \code{FALSE})

+#' taxa columns meaning that \code{rank.from.prefix} should be enabled in the

+#' most cases. (Default: \code{FALSE})

 #' 

 #' @param removeTaxaPrefixes Deprecated. Use \code{prefix.rm} instead.

 #' 

@@ -27,7 +28,8 @@

 #' @param remove.artifacts Deprecated. Use \code{artifact.rm} instead.

 #' 

 #' @details 

-#' \code{convertFromBIOM} coerces a \code{\link[biomformat:biom-class]{biom}} object to a 

+#' \code{convertFromBIOM} coerces a \code{\link[biomformat:biom-class]{biom}}

+#' object to a 

 #' \code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-class]{TreeSummarizedExperiment}}

 #' object.

 #' 

@@ -37,7 +39,7 @@

 #'   

 #' @return

 #' \code{convertFromBIOM} returns an object of class

-#'   \code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-class]{TreeSummarizedExperiment}}

+#' \code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-class]{TreeSummarizedExperiment}}

 #'   

 #' @name importBIOM

 #' 

@@ -75,7 +77,7 @@ NULL

 #' 

 #' @return 

 #' \code{importBIOM} returns an object of class

-#'   \code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-class]{TreeSummarizedExperiment}}

+#' \code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-class]{TreeSummarizedExperiment}}

 #' 

 #' @name importBIOM

 #' 

@@ -187,7 +189,8 @@ convertFromBIOM <- function(

         # Transposing feature_data and make it df object

         feature_data <- as.data.frame(feature_data)

         # Add column that includes all the data

-        feature_data[["taxonomy_unparsed"]] <- apply(feature_data, 1, paste0, collapse = ";")

+        merged_col <- apply(feature_data, 1, paste0, collapse = ";")

+        feature_data <- cbind(feature_data, merged_col)

         # Add correct colnames

         colnames(feature_data) <- c(colnames, "taxonomy_unparsed")

     }

@@ -195,27 +198,29 @@ convertFromBIOM <- function(

     # that the taxonomy is not parsed. Try to parse it.

     if( ncol(feature_data) == 1 ){

         colnames(feature_data) <- "taxonomy_unparsed"

-        tax_tab <- .parse_taxonomy(feature_data, column_name = colnames(feature_data))

+        tax_tab <- .parse_taxonomy(

+            feature_data, column_name = colnames(feature_data))

         feature_data <- cbind(tax_tab, feature_data)

         feature_data <- as.data.frame(feature_data)

     }

-    # Clean feature_data from possible character artifacts if specified

+    # Clean feature_data from possible character artifacts if specified.

     if( artifact.rm ){

         feature_data <- .detect_taxa_artifacts_and_clean(feature_data, ...)

     }

-    

-    # Replace taxonomy ranks with ranks found based on prefixes

-    if( rank.from.prefix && all(

-        unlist(lapply(colnames(feature_data),

-                        function(x) !x %in% TAXONOMY_RANKS)))){

+    # Replace taxonomy ranks with ranks found based on prefixes. Test first

+    # if columns are already ranks. If they are, do not change them.

+    cols_not_already_ranks <- lapply(

+        colnames(feature_data), function(x) !x %in% TAXONOMY_RANKS) |>

+        unlist() |> all()

+    if( rank.from.prefix && cols_not_already_ranks ){

         # Find ranks

-        ranks <- lapply(colnames(feature_data),

-                        .replace_colnames_based_on_prefix, x=feature_data)

+        ranks <- lapply(

+            colnames(feature_data), .replace_colnames_based_on_prefix,

+            x = feature_data)

         # Replace old ranks with found ranks

         colnames(feature_data) <- unlist(ranks)

     }

-    

     # Adjust row and colnames

     rownames(counts) <- rownames(feature_data) <- biomformat::rownames(x)

     colnames(counts) <- rownames(sample_data) <- biomformat::colnames(x)

@@ -225,27 +230,24 @@ convertFromBIOM <- function(

     feature_data <- DataFrame(feature_data)

     # Convert into list

     assays <- SimpleList(counts = counts)

-    

     # Create TreeSE

     tse <- TreeSummarizedExperiment(

         assays = assays,

         colData = sample_data,

         rowData = feature_data)

-    

     # Set ranks based on rowData columns if user has specified to do so

     temp <- .set_ranks_based_on_rowdata(tse, ...)

-    

     # Remove prefixes if specified and rowData includes info

     if(prefix.rm && ncol(rowData(tse)) > 0){

         rowData(tse) <- .remove_prefixes_from_taxa(rowData(tse), ...)

     }

-    

     return(tse)

 }

 #' @rdname importBIOM

 #' 

-#' @param x \code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-class]{TreeSummarizedExperiment}}

+#' @param x

+#' \code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-class]{TreeSummarizedExperiment}}

 #' 

 #' @param assay.type \code{Character scaler}. The name of assay.

 #' (Default: \code{"counts"})

@@ -280,7 +282,7 @@ setMethod(

         feature_tab,

         prefixes = paste0(

             "(", paste0(.taxonomy_rank_prefixes, collapse = "|"), ")__"),

-        only.taxa.col = TRUE, ...){

+        only.taxa.col = TRUE, ignore.col = "taxonomy_unparsed", ...){

     #

     if( !.is_a_bool(only.taxa.col) ){

         stop("'only.taxa.col' must be TRUE or FALSE.", call. = FALSE)

@@ -289,17 +291,22 @@ setMethod(

     if( !.is_a_string(prefixes) ){

         stop("'prefixes' must be a single character value.", call. = FALSE)

     }

+    #

+    if( !(is.character(ignore.col) || is.null(ignore.col)) ){

+        stop("'ignore.col' must be a character value or NULL.", call. = FALSE)

+    }

+    #

     # Subset by taking only taxonomy info if user want to remove the pattern 

     # only from those. (Might be too restricting, e.g., if taxonomy columns are 

     # not detected in previous steps. That is way the default is FALSE)

+    ind <- rep(TRUE, ncol(feature_tab))

     if( only.taxa.col ){

         ind <- tolower(colnames(feature_tab)) %in% TAXONOMY_RANKS

-        temp <- feature_tab[, ind, drop = FALSE]

-    } else{

-        ind <- rep(TRUE, ncol(feature_tab))

-        temp <- feature_tab

     }

-    

+    # Also remove those columns that are specified to ignore (by default the

+    # column that has unparsed data)

+    ind <- ind & !colnames(feature_tab) %in% ignore.col

+    temp <- feature_tab[, ind, drop = FALSE]

     # If there are columns left for removing the pattern

     if( ncol(temp) > 0 ){

         # Remove patterns

@@ -321,7 +328,7 @@ setMethod(

 # rank that is fed to function.

 .replace_colnames_based_on_prefix <- function(colname, x){

     # Get column

-    col = x[ , colname]

+    col <- x[ , colname]

     # List prefixes

     all_ranks <- .taxonomy_rank_prefixes

     prefixes <- paste0("^", all_ranks, "__")

@@ -340,35 +347,53 @@ setMethod(

 }

 # Detect and clean non wanted characters from Taxonomy data if needed.

-.detect_taxa_artifacts_and_clean <- function(x, pattern = "auto", ...) {

+.detect_taxa_artifacts_and_clean <- function(

+        x, pattern = "auto", ignore.col = "taxonomy_unparsed", ...) {

     #

     if( !.is_non_empty_character(pattern) ){

         stop("'pattern' must be a single character value.", call. = FALSE)

     }

     #

+    if( !(is.character(ignore.col) || is.null(ignore.col)) ){

+        stop("'ignore.col' must be a character value or NULL.", call. = FALSE)

+    }

+    #

+    # Store rownames because they are lost during modifications

     row_names <- rownames(x)

-    # Remove artifacts

-    if( pattern == "auto" ){

-        .require_package("stringr")

-        # Remove all but these characters

-        pattern <- "[[:alnum:]]|-|_|\\[|\\]|,|;\\||[[:space:]]"

-        x <- lapply(x, function(col){

-            # Take all specified characters as a matrix where each column is a 

-            # character

-            temp <- stringr::str_extract_all(col, pattern = pattern, simplify = TRUE)

-            # Collapse matrix to strings

-            temp <- apply(temp, 1, paste, collapse = "")

-            # Now NAs are converted into characters. Convert them back

-            temp[ temp == "NA" ] <- NA

-            # Convert also empty strings to NA

-            temp[ temp == "" ] <- NA

-            return(temp)

-        })

-    } else{

-        # Remove pattern specified by user

-        x <- lapply(x, gsub, pattern = pattern, replacement = "")

+    # Get those columns that are not modified

+    not_mod <- x[ , colnames(x) %in% ignore.col, drop = FALSE]

+    # Subset the data being modified so that it includes only those that user

+    # wants to modify

+    x <- x[ , !colnames(x) %in% ignore.col, drop = FALSE]

+    # If there are still columns to clean after subsetting

+    if( ncol(x) > 0 ){

+        # Remove artifacts

+        if( pattern == "auto" ){

+            .require_package("stringr")

+            # Remove all but these characters

+            pattern <- "[[:alnum:]]|-|_|\\[|\\]|,|;\\||[[:space:]]"

+            x <- lapply(x, function(col){

+                # Take all specified characters as a matrix where each column

+                # is a character

+                temp <- stringr::str_extract_all(

+                    col, pattern = pattern, simplify = TRUE)

+                # Collapse matrix to strings

+                temp <- apply(temp, 1, paste, collapse = "")

+                # Now NAs are converted into characters. Convert them back

+                temp[ temp == "NA" ] <- NA

+                # Convert also empty strings to NA

+                temp[ temp == "" ] <- NA

+                return(temp)

+            })

+        } else{

+            # Remove pattern specified by user

+            x <- lapply(x, gsub, pattern = pattern, replacement = "")

+        }

     }

+    # Ensure that the data is data.frame

     x <- as.data.frame(x)

+    # Combine modified and non-modified data

+    x <- cbind(x, not_mod)

     # Add rownames because they are dropped while removing artifacts

     rownames(x) <- row_names

     return(x)

@@ -400,4 +425,4 @@ setMethod(

     # Create biom

     biom <- do.call(biomformat::make_biom, args)

     return(biom)

-}

\ No newline at end of file

+}

@@ -540,7 +540,8 @@

 # This function sets taxonomy ranks based on rowData of TreeSE. With this,

 # user can automatically set ranks based on imported data.

 .set_ranks_based_on_rowdata <- function(

-        tse, set.ranks = FALSE, verbose = TRUE, ...){

+        tse, set.ranks = FALSE, verbose = TRUE,

+        ignore.col = "taxonomy_unparsed", ...){

     #

     if( !.is_a_bool(set.ranks) ){

         stop("'set.ranks' must be TRUE or FALSE.", call. = FALSE)

@@ -550,28 +551,38 @@

         stop("'verbose' must be TRUE or FALSE.", call. = FALSE)

     }

     #

-    # If user do not want to set ranks

-    if( !set.ranks ){

-        return(NULL)

+    if( !(is.character(ignore.col) || is.null(ignore.col)) ){

+        stop("'ignore.col' must be a character value or NULL.", call. = FALSE)

     }

+    #

     # Get ranks from rowData

-    ranks <- colnames(rowData(tse))

+    rd <- rowData(tse)

+    # Remove those columns that are ignored. By default, the column

+    # containing unparsed taxonomy.

+    rd <- rd[ , !colnames(rd) %in% ignore.col, drop = FALSE]

     # Ranks must be character columns

-    is_char <- lapply(rowData(tse), function(x) is.character(x) || is.factor(x))

+    is_char <- lapply(

+        rd, function(x) is.character(x) || is.factor(x))

     is_char <- unlist(is_char)

-    ranks <- ranks[ is_char ]

-    # rowData is empty, cannot set ranks

-    if( length(ranks) == 0 ){

+    rd <- rd[ , is_char, drop = FALSE]

+    # If user wants to set ranks and there are ranks after filtering out

+    # those columns that are not characters.

+    if( set.ranks && ncol(rd) > 0L ){

+        # Finally, set ranks and give message

+        ranks <- colnames(rd)

+        temp <- setTaxonomyRanks(ranks)

+        if( verbose ){

+            message(

+                "TAXONOMY_RANKS set to: '",

+                paste0(ranks, collapse = "', '"), "'")

+        }

+    }

+    # If user wanted to set ranks but there were no suitable columns in rowData,

+    # give warning

+    if( set.ranks && ncol(rd) == 0L ){

         warning(

             "Ranks cannot be set. rowData(x) does not include columns ",

             "specifying character values.", call. = FALSE)

-        return(NULL)

-    }

-    # Finally, set ranks and give message

-    temp <- setTaxonomyRanks(ranks)

-    if( verbose ){

-        message(

-            "TAXONOMY_RANKS set to: '", paste0(ranks, collapse = "', '"), "'")

     }

     return(NULL)

 }

@@ -5,7 +5,8 @@

 \alias{convertFromBIOM}

 \alias{convertToBIOM}

 \alias{convertToBIOM,SummarizedExperiment-method}

-\title{Convert a \code{TreeSummarizedExperiment} object to/from \sQuote{BIOM} results}

+\title{Convert a \code{TreeSummarizedExperiment} object to/from \sQuote{BIOM}

+results}

 \usage{

 importBIOM(file, ...)

@@ -33,8 +34,8 @@ convertToBIOM(x, assay.type = "counts", ...)

 \item{prefix.rm}{\code{Logical scalar}. Should

 taxonomic prefixes be removed? The prefixes is removed only from detected

-taxa columns meaning that \code{rank.from.prefix} should be enabled in the most cases.

-(Default: \code{FALSE})}

+taxa columns meaning that \code{rank.from.prefix} should be enabled in the

+most cases. (Default: \code{FALSE})}

 \item{removeTaxaPrefixes}{Deprecated. Use \code{prefix.rm} instead.}

@@ -69,7 +70,8 @@ objects, and

 objects to phyloseq objects.

 }

 \details{

-\code{convertFromBIOM} coerces a \code{\link[biomformat:biom-class]{biom}} object to a

+\code{convertFromBIOM} coerces a \code{\link[biomformat:biom-class]{biom}}

+object to a

 \code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-class]{TreeSummarizedExperiment}}

 object.