R Under development (unstable) (2024-01-23 r85822 ucrt) -- "Unsuffered Consequences"
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> library(DRomics)
Loading required package: limma
Loading required package: DESeq2
Loading required package: S4Vectors
Loading required package: stats4
Loading required package: BiocGenerics

Attaching package: 'BiocGenerics'

The following object is masked from 'package:limma':

    plotMA

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
    as.data.frame, basename, cbind, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
    pmin.int, rank, rbind, rownames, sapply, setdiff, table, tapply,
    union, unique, unsplit, which.max, which.min


Attaching package: 'S4Vectors'

The following object is masked from 'package:utils':

    findMatches

The following objects are masked from 'package:base':

    I, expand.grid, unname

Loading required package: IRanges

Attaching package: 'IRanges'

The following object is masked from 'package:grDevices':

    windows

Loading required package: GenomicRanges
Loading required package: GenomeInfoDb
Loading required package: SummarizedExperiment
Loading required package: MatrixGenerics
Loading required package: matrixStats

Attaching package: 'MatrixGenerics'

The following objects are masked from 'package:matrixStats':

    colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
    colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
    colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
    colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
    colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
    colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
    colWeightedMeans, colWeightedMedians, colWeightedSds,
    colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
    rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
    rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
    rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
    rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
    rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
    rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
    rowWeightedSds, rowWeightedVars

Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.


Attaching package: 'Biobase'

The following object is masked from 'package:MatrixGenerics':

    rowMedians

The following objects are masked from 'package:matrixStats':

    anyMissing, rowMedians


DRomics has been loaded.
!!!! IMPORTANT CHANGES IN DEFAULT PLOT ARGUMENTS !!!!
Now all the plot functions use by default a log10 scale
for dose and BMD values, except curvesplot(),
for which the use of a dose log scale requires the specification
by the user of a non null minimal value (xmin).
We also put the default value of the argument scaling at TRUE
in curvesplot() and bmdplotwithgradient(),
to focus on shapes of dose-responses rather than on their amplitude.

> visualize <- FALSE # put to TRUE for a manual check of plots
> 
> if(visualize) 
+ {
+   # (1) Plot of BMD values with color dose-response gradient
+   # faceted by metabolic pathway (from annotation of the selected items)
+   # and shaped by dose-response trend
+   
+   # An example from the paper published by Larras et al. 2020
+   # in Journal of Hazardous Materials
+   # https://doi.org/10.1016/j.jhazmat.2020.122727
+   # A example of plot obtained with this function is in Figure 5 in Larras et al. 2020
+   
+   
+   # the dataframe with metabolomic results (output $res of bmdcalc() or bmdboot() functions)
+   resfilename <- system.file("extdata", "triclosanSVmetabres.txt", package="DRomics")
+   res <- read.table(resfilename, header = TRUE, stringsAsFactors = TRUE)
+   str(res)
+   
+   # the dataframe with annotation of each item identified in the previous file
+   # each item may have more than one annotation (-> more than one line)
+   annotfilename <- system.file("extdata", "triclosanSVmetabannot.txt", package="DRomics")
+   annot <- read.table(annotfilename, header = TRUE, stringsAsFactors = TRUE)
+   str(annot)
+   
+   # Merging of both previous dataframes
+   # in order to obtain an extenderes dataframe
+   extendedres <- merge(x = res, y = annot, by.x = "id", by.y = "metab.code")
+   head(extendedres)
+   
+   
+   ### (1.a) BMDplot with gradient by pathway
+   bmdplotwithgradient(extendedres, BMDtype = "zSD",
+                       facetby = "path_class", 
+                       shapeby = "trend") 
+   
+   # (1.b) BMDplot with gradient by pathway and trend
+   bmdplotwithgradient(extendedres, BMDtype = "zSD",
+                       facetby = "path_class",
+                       facetby2 = "trend") 
+   
+   # (1.b) BMDplot with gradient by pathway
+   # forcing the limits of the colour gradient at other 
+   # values than observed minimal and maximal values of the signal
+   bmdplotwithgradient(extendedres, BMDtype = "zSD",
+                       facetby = "path_class", 
+                       shapeby = "trend",
+                       limits4colgradient = c(-1, 1)) 
+   
+   # (1.c) The same example changing the gradient colors and the line size
+   bmdplotwithgradient(extendedres, BMDtype = "zSD",
+                       facetby = "path_class", 
+                       shapeby = "trend",
+                       line.size = 3, 
+                       lowercol = "darkgreen", uppercol = "orange") 
+   
+   # (1.d) The same example with only lipid metabolism pathclass
+   # and identification of the metabolites
+   LMres <- extendedres[extendedres$path_class == "Lipid metabolism", ]
+   bmdplotwithgradient(LMres, BMDtype = "zSD",
+                       line.size = 3, 
+                       add.label = TRUE, label.size = 3) 
+  
+    # (1.e) The same example with only membrane transport pathclass
+   # and identification of the metabolites
+   LMres <- extendedres[extendedres$path_class == "Membrane transport", ]
+   bmdplotwithgradient(LMres, BMDtype = "zSD",
+                       line.size = 3, 
+                       add.label = TRUE, label.size = 3) 
+   bmdplotwithgradient(LMres, BMDtype = "zSD", xmax = 7.76,
+                       line.size = 3, 
+                       add.label = FALSE, label.size = 3) 
+   curvesplot(LMres, facetby = "id", xmax = 7.76, scaling = TRUE) 
+   LMres[LMres$id == "NP_92", ]
+   
+   
+   
+   # (2) 
+   # An example on a microarray data set (a subsample of a greater data set)
+   #
+   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 <- bmdcalc(f))
+   
+   bmdplotwithgradient(r$res, BMDtype = "zSD",
+                       facetby = "trend", 
+                       shapeby = "model") 
+   bmdplotwithgradient(r$res, BMDtype = "zSD",
+                       xmax = max(f$omicdata$dose), facetby = "trend", 
+                       shapeby = "model") 
+ 
+ 
+ }
> 
> proc.time()
   user  system elapsed 
   8.81    0.81    9.62