test_that("test the bmdplotwithgradient function", { skip_on_cran() # (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") })