View source: R/sensitivityplot.R
sensitivityplot | R Documentation |
Plot of a summary of BMD values per group of items (with groups defined for example from biological annotation), with groups ordered by values of the chosen summary (as an ECDF plot) or ordered as they are in the definition of the factor coding for them, with points sized by the numbers of items per group.
sensitivityplot(extendedres, BMDtype = c("zSD", "xfold"), group, ECDF_plot = TRUE, colorby, BMDsummary = c("first.quartile", "median" , "median.and.IQR"), BMD_log_transfo = FALSE)
extendedres |
the dataframe of results provided by bmdcalc (res)
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 replicated if their corresponding item has more than one annotation.
This extended dataframe
must at least contain the column giving the chosen BMD values
on which to compute the sensitivity (column |
BMDtype |
The type of BMD used, |
group |
the name of the column of extendedres coding for the groups
on which we want to estimate a global sensitivity.
If |
ECDF_plot |
if TRUE (default choice) groups appear ordered by
values of the BMD summary value
from the bottom up, else they are ordered as their corresponding levels in the factor
given in |
colorby |
optional argument naming the column of |
BMDsummary |
The type of summary used for sensitivity plot,
|
BMD_log_transfo |
If TRUE a log transformation of the BMD is used in the plot. |
The chosen summary is calculated on the BMD values for each group (groups can be for example defined as pathways from biological annotation of items) and plotted as an ECDF plot (ordered by the BMD summary) or in the order of the levels of the factor defining the groups from bottom to up. In this plot each point is sized according to the number of items in the corresponding group. Optionally a different levels (e.g. different molecular levels in a multi-omics approach) can be coded by different colors.
a ggplot object.
Marie-Laure Delignette-Muller
See ecdfquantileplot
.
# (1) An example from data published by Larras et al. 2020 # in Journal of Hazardous Materials # https://doi.org/10.1016/j.jhazmat.2020.122727 # a dataframe with metabolomic results (output $res of bmdcalc() or bmdboot() functions) resfilename <- system.file("extdata", "triclosanSVmetabres.txt", package="DRomics") res <- read.table(resfilename, header = TRUE, stringsAsFactors = TRUE) str(res) # a dataframe with annotation of each item identified in the previous file # each item may have more than one annotation (-> more than one line) annotfilename <- system.file("extdata", "triclosanSVmetabannot.txt", package="DRomics") annot <- read.table(annotfilename, header = TRUE, stringsAsFactors = TRUE) str(annot) # Merging of both previous dataframes # in order to obtain an extenderes dataframe # bootstrap results and annotation annotres <- merge(x = res, y = annot, by.x = "id", by.y = "metab.code") head(annotres) ### an ECDFplot of 25th quantiles of BMD-zSD calculated by pathway sensitivityplot(annotres, BMDtype = "zSD", group = "path_class", BMDsummary = "first.quartile") # same plot in log10 BMD scale (not interesting on this example # but could be on another one) sensitivityplot(annotres, BMDtype = "zSD", group = "path_class", BMDsummary = "first.quartile", BMD_log_transfo = TRUE) ### Plot of 25th quantiles of BMD-zSD calculated by pathway ### in the order of the levels as defined in the group input levels(annotres$path_class) sensitivityplot(annotres, BMDtype = "zSD", group = "path_class", ECDF_plot = FALSE, BMDsummary = "first.quartile") ### an ECDFplot of medians of BMD-zSD calculated by pathway sensitivityplot(annotres, BMDtype = "zSD", group = "path_class", BMDsummary = "median") ### an ECDFplot of medians of BMD-zSD calculated by pathway ### with addition of interquartile ranges (IQRs) sensitivityplot(annotres, BMDtype = "zSD", group = "path_class", BMDsummary = "median.and.IQR") # (2) # An example with two molecular levels # ### Rename metabolomic results metabextendedres <- annotres # Import the dataframe with transcriptomic results contigresfilename <- system.file("extdata", "triclosanSVcontigres.txt", package = "DRomics") contigres <- read.table(contigresfilename, header = TRUE, stringsAsFactors = TRUE) str(contigres) # Import the dataframe with functional annotation (or any other descriptor/category # you want to use, here KEGG pathway classes) contigannotfilename <- system.file("extdata", "triclosanSVcontigannot.txt", package = "DRomics") contigannot <- read.table(contigannotfilename, header = TRUE, stringsAsFactors = TRUE) str(contigannot) # Merging of both previous dataframes contigextendedres <- merge(x = contigres, y = contigannot, by.x = "id", by.y = "contig") # to see the structure of this dataframe str(contigextendedres) ### Merge metabolomic and transcriptomic results extendedres <- rbind(metabextendedres, contigextendedres) extendedres$molecular.level <- factor(c(rep("metabolites", nrow(metabextendedres)), rep("contigs", nrow(contigextendedres)))) str(extendedres) ### Plot of 25th quantiles of BMD-zSD calculated by pathway ### and colored by molecular level # optional inverse alphabetic ordering of groups for the plot extendedres$path_class <- factor(extendedres$path_class, levels = sort(levels(extendedres$path_class), decreasing = TRUE)) sensitivityplot(extendedres, BMDtype = "zSD", group = "path_class", colorby = "molecular.level", BMDsummary = "first.quartile") ### Plot of medians and IQRs of BMD-zSD calculated by pathway ### and colored by molecular level sensitivityplot(extendedres, BMDtype = "zSD", group = "path_class", colorby = "molecular.level", BMDsummary = "median.and.IQR")
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