Allow different labels for QC samples

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: sbcms
 Type: Package
 Title: Signal batch correction for (LC)-MS data
-Version: 0.99.0
+Version: 0.99.1
 Author: Andris Jankevics
 Maintainer: Andris Jankevics <[email protected]>
 Description: This signal batch correction package for LC-MS data. This version supports missing vallues in your data (at least 4 data point for QC are needed) and has moduler desing to add different fitting/correction functions.

R/sbc_main.R

@@ -24,6 +24,7 @@ NULL
 ##' @param log TRUE or FALSE to perform the signal correction fit on the log
 ##'scaled data. Default is TRUE.
 ##' @param minQC Minimum number of QC samples required for signal correction.
+##' @param qc_label Class label for QC sample.
 ##'
 ##' @return A data frame of corrected values.
 ##'
@@ -37,19 +38,21 @@ NULL
 ##' 
 ##' @export
 
-QCRSC <- function(df, order, batch, classes, spar = 0, log = TRUE, minQC = 5) {
+QCRSC <- function(df, order, batch, classes, spar = 0, log = TRUE,
+    minQC = 5, qc_label="QC") {
 
-    if (length(which(classes == "QC")) <= 0) {
-        message("QC samples are not defined! Class label has to be QC.")
+    if (length(which(classes == qc_label)) <= 0) {
+        message("QC samples are not defined! Please see help page for
+            parameter qc_label.")
         stop()
     }
 
     message("The number of NA and <= 0 values in peaksData before QC-RSC: ",
         sum(is.na(df) | df <= 0))
 
-    qcData <- df[, classes == "QC"]
-    qc_batch <- batch[classes == "QC"]
-    qc_order <- order[classes == "QC"]
+    qcData <- df[, classes == qc_label]
+    qc_batch <- batch[classes == qc_label]
+    qc_order <- order[classes == qc_label]
     QC_fit <- lapply(seq_len(nrow(df)), sbcWrapper, qcData = qcData, 
         order = order, qcBatch = qc_batch, qcOrder = qc_order, 
         log = log, spar = spar, batch = batch, minQC = minQC)

R/sbcmsPlot.R

@@ -18,6 +18,7 @@ NULL
 ##'plot. If set to NULL will plot the first 100.
 ##' @param output Filename of the output pdf file. Can include the path.
 ##'If set to NULL output will be list object containing ggplot2 plots.
+##' @param qc_label Class label for QC sample.
 ##' 
 ##' @return Pdf file or list object showing data before and after 
 ##'signal correction
@@ -35,10 +36,10 @@ NULL
 ##' @export
 
 sbcmsPlot <- function(df, corrected_df, classes, batch, indexes = NULL,
-    output = "sbcms_plots.pdf") {
+    qc_label="QC", output = "sbcms_plots.pdf") {
 
     shapes <- rep(19, length(classes))
-    shapes[classes == "QC"] <- 3
+    shapes[classes == qc_label] <- 3
     manual_color <- c("#386cb0", "#ef3b2c", "#7fc97f", "#fdb462", "#984ea3", 
         "#a6cee3", "#778899", "#fb9a99", "#ffff33")
     gg_THEME <- theme(panel.background = element_blank(), 

tests/testthat/test-sbcmsPlot.R

@@ -51,3 +51,23 @@ test_that ("sbcmsPlot returns output for the first 100 features if
 
   testthat::expect_true(length(plots) == 100)
 })
+
+test_that ("sbcmsPlot returns ggplot output, with different QC sample label", {
+
+  classes <- sbcdata$class
+  classes[classes == "QC"] <- "Quality"
+  batch <- sbcdata$batch
+  order <- c(1:nrow(sbcdata$data))
+  data <- t(sbcdata$data[, 1:10])
+
+  out <- QCRSC(df = data, order = order, batch = batch, classes = classes,
+    spar = 0, minQC = 4, qc_label="Quality")
+
+  plots <- sbcmsPlot(df = data, corrected_df = out, 
+    classes, batch, output=NULL, indexes=c(1,5,7), qc_label="Quality")
+
+  testthat::expect_s3_class(plots[[1]], "ggplot")
+  # Empty plots are getting removed from the list object
+  testthat::expect_true(length(plots) == 3)
+
+})