Minor changes before CRAN release

R/RNAseqdata.R

@@ -21,8 +21,13 @@ RNAseqdata <- function(file, check = TRUE,
   subdata4check <- data[1:min(nrow(data), 10), ]
   subdata4checkT <- trunc(subdata4check)
   if (!identical(subdata4check, subdata4checkT))
-    warning("Your data contain non integer values. 
+    stop("Your data contain non integer values. 
             Make sure that your RNAseq data are imported in raw counts.\n") 
+  if (nrowd < 100)
+    warning("Your dataset contains less than 100 lines. Are you sure you really
+            work on RNAseq data ? This function should
+            not be used with another type of data.")
+
 
   if (check)
   {

R/metabolomicdata.R

@@ -24,6 +24,10 @@ metabolomicdata <- function(file, check = TRUE)
   if (any(data > 100))
     warning("Your data contain high values (> 100). 
     Make sure that your data (metabolomic signal) are in log-scale.\n") 
+  if (nrowd < 100)
+    warning("Your dataset contains less than 100 lines. Are you sure you really
+            work on metabolomics data ? This function should
+            not be used with another type of data.")
 
   if (check)
   {

R/microarraydata.R

@@ -21,6 +21,10 @@ microarraydata <- function(file, check = TRUE,
   if (any(data > 100))
     warning("Your data contain high values (> 100). 
             Make sure that your data (microarray signal) are in log-scale.\n") 
+  if (nrowd < 100)
+    warning("Your dataset contains less than 100 lines. Are you sure you really
+            work on microarray data ? This function should
+            not be used with another type of data.")
 
   if (check)
   {

man/DRomics.Rd

@@ -13,10 +13,11 @@ DRomics provides several functions for dose-response (or concentration-response)
 \item and \code{\link{bmdcalc}} to derive a benchmark dose or concentration from each fitted curve.
 }
 
-The available version supports three types of data:
+The available version supports three types of data and should not be used 
+with other types of data:
 \itemize{
 \item Single-channel microarray data (previously transformed in log2)
-that must imported  using the function\code{\link{microarraydata}}, 
+that must imported  using the function \code{\link{microarraydata}}, 
 \item RNAseq (in raw counts) that must imported using the function 
 \code{\link{RNAseqdata}} and 
 \item metabolomic data that must imported using the function 
@@ -54,8 +55,8 @@ Marie-Laure Delignette-Muller, Elise Billoir, Floriane Larras and Aurelie Siberc
 ## here cyclicloess normalization of a small microarray data set
 ## (sample of a real data set)
 
-datatxt <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
-(o <- microarraydata(datatxt, check = TRUE, norm.method = "cyclicloess"))
+datafilename <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
+(o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess"))
 plot(o)
 
 # Step 2: item selection using the quadratic method

man/RNAseqdata.Rd

@@ -108,11 +108,11 @@ Marie-Laure Delignette-Muller
 # (in Toxicological sciences, 160, 95-110)
 # Effect on kidney transcriptomes of tetrachloroethylene
 #
-datatxt <- system.file("extdata", "RNAseq_sample.txt", package="DRomics")
-(o <- RNAseqdata(datatxt, check = TRUE, transfo.method = "rlog"))
+datafilename <- system.file("extdata", "RNAseq_sample.txt", package="DRomics")
+(o <- RNAseqdata(datafilename, check = TRUE, transfo.method = "rlog"))
 plot(o)
 
-# If you want to use your own data set just replace datatxt, 
+# If you want to use your own data set just replace datafilename, 
 # the first argument of RNAseqdata(), 
 # by the name of your data file (e.g. "mydata.txt")
 # 
@@ -124,14 +124,14 @@ plot(o)
 
 # (2) transformation with two methods on the whole data set
 \donttest{
-datatxt <- system.file("extdata", "Zhou_kidney_pce.txt", package="DRomics")
+datafilename <- system.file("extdata", "Zhou_kidney_pce.txt", package="DRomics")
 
 # variance stabilizing tranformation
-(o1 <- RNAseqdata(datatxt, check = TRUE, transfo.method = "vst"))
+(o1 <- RNAseqdata(datafilename, check = TRUE, transfo.method = "vst"))
 plot(o1)
 
 # regularized logarithm
-(o2 <- RNAseqdata(datatxt, check = TRUE, transfo.method = "vst"))
+(o2 <- RNAseqdata(datafilename, check = TRUE, transfo.method = "vst"))
 plot(o2)
 }
 

man/bmdboot.Rd

@@ -126,14 +126,14 @@ Marie-Laure Delignette-Muller
 \examples{
 # (1) a toy example (a very small subsample of a microarray data set) 
 #
-datatxt <- system.file("extdata", "transcripto_very_small_sample.txt",
+datafilename <- system.file("extdata", "transcripto_very_small_sample.txt",
 package="DRomics")
 
 # to test the package on a small but not very small data set
 # use the following commented line
-# datatxt <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
+# datafilename <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
 
-o <- microarraydata(datatxt, check = TRUE, norm.method = "cyclicloess")
+o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess")
 s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.001)
 f <- drcfit(s_quad, progressbar = TRUE)
 r <- bmdcalc(f)
@@ -167,9 +167,9 @@ b.lin.90$res
 # (2) an example on a microarray data set (a subsample of a greater data set) 
 #
 \donttest{
-datatxt <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
+datafilename <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
 
-(o <- microarraydata(datatxt, check = TRUE, norm.method = "cyclicloess"))
+(o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess"))
 (s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.001))
 (f <- drcfit(s_quad, progressbar = TRUE))
 (r <- bmdcalc(f))

man/bmdcalc.Rd

@@ -108,13 +108,13 @@ Marie-Laure Delignette-Muller and Elise Billoir
 
 # (1) a toy example (a very small subsample of a microarray data set) 
 #
-datatxt <- system.file("extdata", "transcripto_very_small_sample.txt", package="DRomics")
+datafilename <- system.file("extdata", "transcripto_very_small_sample.txt", package="DRomics")
 
 # to test the package on a small (for a quick calculation) but not very small data set
 # use the following commented line
-# datatxt <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
+# datafilename <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
 
-(o <- microarraydata(datatxt, check = TRUE, norm.method = "cyclicloess"))
+(o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess"))
 (s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.01))
 (f <- drcfit(s_quad, progressbar = TRUE))
 (r <- bmdcalc(f))
@@ -127,13 +127,13 @@ plot(rb)
 # (2) an example on a microarray data set (a subsample of a greater data set) 
 #
 \donttest{
-datatxt <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
+datafilename <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
 
 # to test the package on a small (for a quick calculation) but not very small data set
 # use the following commented line
-# datatxt <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
+# datafilename <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
 
-(o <- microarraydata(datatxt, check = TRUE, norm.method = "cyclicloess"))
+(o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess"))
 (s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.01))
 (f <- drcfit(s_quad, progressbar = TRUE))
 (r <- bmdcalc(f))

man/curvesplot.Rd

@@ -14,8 +14,10 @@ curvesplot(extendedres, xmin = 0, xmax, y0shift = TRUE,
 
 \arguments{
 \item{extendedres}{the dataframe of results provided by bmdcalc (res) or drcfit (fitres) 
- or a subset of this data frame (selected lines) potentially extended with additional columns
- coming for example from the annotation of items. This extended dataframe
+ or a subset of this data frame (selected lines). This dataframe can be extended 
+ with additional columns coming for example from the annotation of items, and some lines 
+ can be duplicated if their corresponding item has more than one annotation. 
+ This extended dataframe
  must at least contain the column giving the identification of each curve (\code{id}),
  the column \code{model} naming the fitted model and the values of 
 the parameters (columns \code{b}, \code{c}, \code{d}, \code{e}, \code{f}).}
@@ -69,10 +71,10 @@ Marie-Laure Delignette-Muller
 
 # A toy example on a very small subsample of a microarray data set) 
 #
-datatxt <- system.file("extdata", "transcripto_very_small_sample.txt", 
+datafilename <- system.file("extdata", "transcripto_very_small_sample.txt", 
 package="DRomics")
 
-o <- microarraydata(datatxt, check = TRUE, norm.method = "cyclicloess")
+o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess")
 s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.01)
 f <- drcfit(s_quad, progressbar = TRUE)
 
@@ -109,9 +111,9 @@ curvesplot(f$fitres, xmax = max(f$omicdata$dose),
 
 # (4) an example on a microarray data set (a subsample of a greater data set)
 #
-datatxt <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
+datafilename <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
 
-(o <- microarraydata(datatxt, check = TRUE, norm.method = "cyclicloess"))
+(o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess"))
 (s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.001))
 (f <- drcfit(s_quad, progressbar = TRUE))
 (r <- bmdcalc(f))

man/drcfit.Rd

@@ -129,13 +129,13 @@ Marie-Laure Delignette-Muller
 
 # (1) a toy example (a very small subsample of a microarray data set) 
 #
-datatxt <- system.file("extdata", "transcripto_very_small_sample.txt", package="DRomics")
+datafilename <- system.file("extdata", "transcripto_very_small_sample.txt", package="DRomics")
 
 # to test the package on a small (for a quick calculation) but not very small data set
 # use the following commented line
-# datatxt <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
+# datafilename <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
 
-(o <- microarraydata(datatxt, check = TRUE, norm.method = "cyclicloess"))
+(o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess"))
 (s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.05))
 (f <- drcfit(s_quad, progressbar = TRUE))
 
@@ -153,9 +153,9 @@ plot(f, plot.type = "fitted_residuals")
 # (2) an example on a microarray data set (a subsample of a greater data set) 
 #
 \donttest{
-datatxt <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
+datafilename <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
 
-(o <- microarraydata(datatxt, check = TRUE, norm.method = "cyclicloess"))
+(o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess"))
 (s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.05))
 (f <- drcfit(s_quad, progressbar = TRUE))
 

man/ecdfplotwithCI.Rd

@@ -59,9 +59,9 @@ Marie-Laure Delignette-Muller
 
 # (1) a toy example (a very small subsample of a microarray data set) 
 #
-datatxt <- system.file("extdata", "transcripto_very_small_sample.txt",
+datafilename <- system.file("extdata", "transcripto_very_small_sample.txt",
 package="DRomics")
-o <- microarraydata(datatxt, check = TRUE, norm.method = "cyclicloess")
+o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess")
 s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.001)
 f <- drcfit(s_quad, progressbar = TRUE)
 r <- bmdcalc(f)
@@ -83,9 +83,9 @@ ecdfplotwithCI(variable = a$BMD.zSD, CI.lower = a$BMD.zSD.lower,
 # (2) an example on a microarray data set (a subsample of a greater data set) 
 #
 \donttest{
-datatxt <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
+datafilename <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
 
-(o <- microarraydata(datatxt, check = TRUE, norm.method = "cyclicloess"))
+(o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess"))
 (s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.001))
 (f <- drcfit(s_quad, progressbar = TRUE))
 (r <- bmdcalc(f))

man/itemselect.Rd

@@ -117,9 +117,9 @@ Marie-Laure Delignette-Muller
 
 # (1) an example on a microarray data set (a subsample of a greater data set) 
 #     
-datatxt <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
+datafilename <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
 
-(o <- microarraydata(datatxt, check = TRUE, norm.method = "cyclicloess"))
+(o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess"))
 
 # 1.a using the quadratic trend test
 #

man/metabolomicdata.Rd

@@ -99,13 +99,13 @@ Marie-Laure Delignette-Muller
 # (1) import and check of metabolomic data 
 # (an example on a subsample of a greater data set)
 #
-datatxt <- system.file("extdata", "metabolo_sample.txt", package="DRomics")
+datafilename <- system.file("extdata", "metabolo_sample.txt", package="DRomics")
 
-o <- metabolomicdata(datatxt, check = TRUE)
+o <- metabolomicdata(datafilename, check = TRUE)
 print(o)
 plot(o)
 
-# If you want to use your own data set just replace datatxt, 
+# If you want to use your own data set just replace datafilename, 
 # the first argument of metabolomicdata(), 
 # by the name of your data file (e.g. "mydata.txt")
 # 

man/microarraydata.Rd

@@ -106,12 +106,12 @@ Marie-Laure Delignette-Muller
 # (1) import, check and normalization of microarray data 
 # (an example on a subsample of a greater data set)
 #
-datatxt <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
-o <- microarraydata(datatxt, check = TRUE, norm.method = "cyclicloess")
+datafilename <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
+o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess")
 print(o)
 plot(o)
 
-# If you want to use your own data set just replace datatxt, 
+# If you want to use your own data set just replace datafilename, 
 # the first argument of microarraydata(), 
 # by the name of your data file (e.g. "mydata.txt")
 # 
@@ -122,9 +122,9 @@ plot(o)
 
 
 # (2) normalization with other methods
-(o.2 <- microarraydata(datatxt, check = TRUE, norm.method = "quantile"))
+(o.2 <- microarraydata(datafilename, check = TRUE, norm.method = "quantile"))
 plot(o.2)
-(o.3 <- microarraydata(datatxt, check = TRUE, norm.method = "scale"))
+(o.3 <- microarraydata(datafilename, check = TRUE, norm.method = "scale"))
 plot(o.3)
 
 }

tests/examplewithLprobit.R

@@ -1,6 +1,6 @@
 library(DRomics)
-datatxt <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
-(o <- microarraydata(datatxt, check = TRUE, norm.method = "cyclicloess"))
+datafilename <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
+(o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess"))
 (s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.001))
 (f <- drcfit(s_quad, sigmoid.model = "log-probit", progressbar = TRUE))
 itemslP <- as.character(f$fitres[f$fitres$model == "log-probit",]$id)

tests/examplewithRNAseq.R

@@ -2,8 +2,8 @@ library(DRomics)
 # importation and check of RNAseq data and normalization
 # with respect to library size and transformation 
 # options to put in shiny : transfo.method (2 methods, rlog or vst)
-datatxt <- system.file("extdata", "RNAseq_sample.txt", package="DRomics")
-(o <- RNAseqdata(datatxt, check = TRUE, transfo.method = "rlog"))
+datafilename <- system.file("extdata", "RNAseq_sample.txt", package="DRomics")
+(o <- RNAseqdata(datafilename, check = TRUE, transfo.method = "rlog"))
 plot(o)
 
 # item selection using the quadratic method

tests/examplewithmetabolomic.R

@@ -1,7 +1,7 @@
 library(DRomics)
 # importation and check of metabolomic data
-datatxt <- system.file("extdata", "metabolo_sample.txt", package="DRomics")
-(o <- metabolomicdata(datatxt, check = TRUE))
+datafilename <- system.file("extdata", "metabolo_sample.txt", package="DRomics")
+(o <- metabolomicdata(datafilename, check = TRUE))
 plot(o)
 
 # item selection using the quadratic method

tests/examplewithmicroarray.R

@@ -2,14 +2,14 @@ library(DRomics)
 # importation and check of data and normalization if needed
 # options to put in shiny : norm.method (4 methods)
 ## sample of the transcripto data set
-datatxt <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
-(o <- microarraydata(datatxt, check = TRUE, norm.method = "cyclicloess"))
+datafilename <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
+(o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess"))
 plot(o)
-(o.2 <- microarraydata(datatxt, check = TRUE, norm.method = "none"))
+(o.2 <- microarraydata(datafilename, check = TRUE, norm.method = "none"))
 plot(o.2)
-(o.3 <- microarraydata(datatxt, check = TRUE, norm.method = "quantile"))
+(o.3 <- microarraydata(datafilename, check = TRUE, norm.method = "quantile"))
 plot(o.3)
-(o.4 <- microarraydata(datatxt, check = TRUE, norm.method = "scale"))
+(o.4 <- microarraydata(datafilename, check = TRUE, norm.method = "scale"))
 plot(o.4)
 
 # item selection using the quadratic method

tests/testthat/test_bmdcalc.R

@@ -3,8 +3,8 @@ test_that("bmdcalc works as expected on the BMD results",
   {
     skip_on_cran()
     skip_on_os(c("mac", "linux", "solaris"))
-    datatxt <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
-    o <- microarraydata(datatxt, check = TRUE, norm.method = "cyclicloess")
+    datafilename <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
+    o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess")
     s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.001)
     f <- drcfit(s_quad, progressbar = TRUE)
     r.1 <- bmdcalc(f, z = 1, x = 10)

tests/testthat/test_drcfit.R

@@ -3,8 +3,8 @@ test_that("drcfit works as expected on the model results",
   {
     skip_on_cran()
     skip_on_os(c("mac", "linux", "solaris"))
-    datatxt <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
-    o <- microarraydata(datatxt, check = TRUE, norm.method = "cyclicloess")
+    datafilename <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
+    o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess")
     s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.001)
     f <- drcfit(s_quad, progressbar = TRUE)
     tmodel <- table(f$fitres$model)