Merge pull request #9 from uclahs-cds/danknight-rcc-csv

Replace Excel format RCC loading with CSV

DESCRIPTION

@@ -1,14 +1,16 @@
 Package: NanoStringNorm
 Type: Package
 Title: Normalize NanoString miRNA and mRNA Data
-Version: 2.0.0
-Date: 2023-03-21
+Version: 3.0.0
+Date: 2025-01-15
 Authors@R: c(
 	person(c("Daryl", "M."), "Waggott", role = "aut"),
 	person("Paul", "Boutros", email = "[email protected]", role = "cre"),
 	person("Dan", "Knight", role = "ctb"))
-Depends: R (>= 2.14.0), gdata (>= 2.8.2), XML (>= 3.98-1.5)
-Imports: methods
+Depends:
+  R (>= 2.14.0)
+Imports:
+  methods
 Suggests: googleVis (>= 0.2.14), lme4, RUnit (>= 0.4.26)
 Description: A set of tools for normalizing, diagnostics and visualization of NanoString nCounter data.
 License: GPL-2

NAMESPACE

@@ -2,7 +2,7 @@ export(
 	'NanoStringNorm',
 	'Plot.NanoStringNorm',
 	'Plot.NanoStringNorm.gvis',
-	'read.xls.RCC',
+	'read.csv.RCC',
 	'read.markup.RCC',
 	'other.normalization',
 	'norm.comp',
@@ -20,10 +20,6 @@ importFrom("stats", "aov", "coef", "cor", "density", "lm", "lowess",
 importFrom("utils", "download.file", "packageDescription",
          "read.table")
 importFrom("utils", "read.csv")
-import(
-    'gdata',
-    'XML'
-	)
 
 
 

NEWS

@@ -1,5 +1,15 @@
+NanoStringNorm 3.0.0 2025-01-15
+----------------------------------------------------------------
+
+REMOVED
+* Removed Excel .xls support due to broken CRAN dependency
+
+ADDED
+* Added CSV support for nCounter Excel files. Excel files must be converted externally.
+
 NanoStringNorm 2.0.0 2023-03-21
 ----------------------------------------------------------------
+
 REMOVED
 * Removed vsn functionality due to broken CRAN dependency
 

R/read.csv.RCC.R

@@ -0,0 +1,84 @@
+read.csv.RCC <- function(path, sample.id.row = 'File.Name') {
+    if (!file.exists(path)) {
+        stop(paste('File not found:', path)) ;
+        }
+
+    prep.rcc <- function(path) {
+        data <- read.csv(
+            path,
+            header = FALSE,
+            strip.white = TRUE
+            );
+        data <- data[!sapply(data, function(x) all(is.na(x)))];
+
+        data.start.index <- min(which(data[, 1] == 'Reporter Counts'));
+        header <- data[1:(data.start.index - 1), ];
+        data <- data[data.start.index:nrow(data), ];
+
+        return(list(
+            header = header,
+            x = data
+            ));
+        }
+    rcc <- prep.rcc(path);
+
+    if (is.null(rcc$header)) {
+        stop('There appears to be a problem with the RCC CSV file. No header information found.');
+        }
+
+    rcc$header <- rcc$header[is.na(rcc$header[1]) | (rcc$header[1] != ''), ];
+    rownames(rcc$header) <- rcc$header[, 1];
+    rcc$header <- rcc$header[, -1];
+
+    rownames(rcc$header) <- gsub(' $', '', rownames(rcc$header));
+    rownames(rcc$header) <- gsub(' ', '.', rownames(rcc$header));
+    rownames(rcc$header) <- tolower(rownames(rcc$header));
+
+    if ('id' %in% rownames(rcc$header)) {
+        rownames(rcc$header)[rownames(rcc$header) == 'id'] <- 'sample.id';
+        }
+
+    if (!all(c('file.name', 'sample.id', 'binding.density') %in% rownames(rcc$header)))  {
+        stop('There appears to be a problem with the RCC CSV file. Rownames in header are missing "File name", "Sample id", "Binding density"');
+        }
+
+    rcc$header <- rcc$header[!rownames(rcc$header) %in% c('file.attributes', 'lane.attributes'), -c(1,2)];
+
+    sample.ids <- rcc$header[rownames(rcc$header) %in% tolower(sample.id.row),];
+    sample.ids <- gsub(' ', '.', sample.ids);
+    sample.ids <- gsub('^([0-9])', 'X\\1', sample.ids);
+    colnames(rcc$header) <- sample.ids;
+
+    if (is.null(rcc$x)) {
+        stop('There appears to be a problem with the RCC CSV file. Likely couldnt find the count specifically "Code Class" in header information.');
+        }
+
+    colnames(rcc$x) <- rcc$x[2, ];
+    rcc$x <- rcc$x[-c(1:2), 1:(3 + length(sample.ids))];
+
+    rows.with.missing.anno <- (rcc$x[, 1] == '' | rcc$x[, 2] == '');
+    if (any(rows.with.missing.anno)) {
+        rcc$x <- rcc$x[!rows.with.missing.anno,];
+        cat(paste('The following row(s)', paste(which(rows.with.missing.anno), collapse = ', '), 'have been dropped due to missing annotation.\n\t  You may want to double check the excel file.\n\n'));
+        }
+
+    colnames(rcc$x) <- gsub(' ', '.', colnames(rcc$x));
+    colnames(rcc$x) <- c(colnames(rcc$x)[1:3], sample.ids);
+
+    cat(paste('There were', length(sample.ids), 'samples imported. \nNote that spaces in sample names will be replaced by dots. \n'));
+
+    if (length(sample.ids) > 5) {
+        cat('The first and last 3 sample names found in the dataset are:\n');
+        cat(paste(c(sample.ids[1:3], rev(sample.ids)[1:3])));
+        }
+    else {
+        cat('The sample names found in the dataset are:\n');
+        cat(paste(sample.ids));
+        }
+
+    cat(paste('\n\nThere were', nrow(rcc$x), 'genes imported with the following Code Class breakdown:'));
+    print(table(rcc$x[, 'Code.Class']));
+
+    class(rcc) <- 'NanoString';
+    return(rcc);
+    }