R Under development (unstable) (2024-01-23 r85822 ucrt) -- "Unsuffered Consequences"
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> # Tests on residuals and corresponding postfit filter
> 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)
+ {
+   IC <- "AICc"
+   ### test on microarray data ######################
+   datafilename <- system.file("extdata", "transcripto_sample.txt", package="DRomics")
+   datafilename <- system.file("extdata", "transcripto_very_small_sample.txt", package="DRomics")
+   
+   (o <- microarraydata(datafilename, check = TRUE, norm.method = "cyclicloess"))
+   (s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.05))
+   (f <- drcfit(s_quad, progressbar = TRUE, information.criterion = IC))
+   plot(f, plot.type = "fitted_residuals")
+   nrow(f$fitres)
+   nrow(f$unfitres)
+   length(which(f$residualtests$resivartrendP < 0.05))
+   length(which(f$residualtests$resivartrendP < 0.05)) / length(f$residualtests$resivartrendP)
+   
+   # Look at the table of results for successful fits
+   head(f$fitres)
+   
+   # Look at the table of results for unsuccessful fits
+   head(f$unfitres)
+   
+   # count the number of unsuccessful fits for each cause
+   table(f$unfitres$cause)
+   
+   # Plot of the data corresponding to unsuccessful fits
+   targetplot(f$unfitres$id[f$unfitres$cause == "constant.model"], f)
+   targetplot(f$unfitres$id[f$unfitres$cause == "trend.in.residuals"], f)
+ 
+   # Fit without postfit filtering
+   (f2 <- drcfit(s_quad, postfitfilter = FALSE, progressbar = TRUE))
+   nrow(f2$fitres)
+   nrow(f2$unfitres)
+   
+   # count the number of unsuccessful fits for each cause
+   table(f2$unfitres$cause)
+   
+   # Plot of the data corresponding to unsuccessful fits in f
+   (itemseliminatedinf <- f$unfitres$id[f$unfitres$cause == "trend.in.residuals"])
+   
+   targetplot(itemseliminatedinf, f2)
+   
+   f2$residualtests
+   (itemswithmeantrendinf2 <- 
+       f2$fitres$id[f2$residualtests$resimeantrendP < 0.05])
+   targetplot(itemswithmeantrendinf2[1:20], f2)
+   
+   (itemswithvartrendinf2 <- 
+       f2$fitres$id[f2$residualtests$resivartrendP < 0.05])
+   targetplot(itemswithvartrendinf2[1:20], f2)
+   
+   (itemsbothPB <- f2$fitres$id[f2$residualtests$resimeantrendP < 0.05 
+                               & f2$residualtests$resivartrendP < 0.05])
+   ### test on RNAseq data #################
+   data(Zhou_kidney_pce)
+   d <- Zhou_kidney_pce
+   (o <- RNAseqdata(d))
+   (s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.05))
+   (f <- drcfit(s_quad, progressbar = TRUE, information.criterion = IC))
+   # (f <- drcfit(s_quad, progressbar = FALSE, parallel = "snow", ncpus = 4))
+   plot(f, dose_log_transfo = TRUE) + scale_x_log10(limits = c(0.1, 10))
+   
+   # count the number of unsuccessful fits for each cause
+   table(f$unfitres$cause)
+   
+   # Plot of the data corresponding to unsuccessful fits
+   targetplot(f$unfitres$id[f$unfitres$cause == "constant.model"], f)
+   targetplot(f$unfitres$id[f$unfitres$cause == "trend.in.residuals"], f)
+   nrow(f$fitres)
+   nrow(f$unfitres)
+   length(which(f$residualtests$resivartrendP < 0.05))
+   length(which(f$residualtests$resivartrendP < 0.05)) / length(f$residualtests$resivartrendP)
+   
+   ### test on RNAseqdata incorrectly entered as metabolomic data
+   ### and with a high FDR
+   data(Zhou_kidney_pce)
+   d <- Zhou_kidney_pce
+   (o <- continuousomicdata(d))
+   (s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.20))
+   (f <- drcfit(s_quad, progressbar = TRUE, information.criterion = IC))
+   plot(f, items = 49)
+   nrow(f$fitres)
+   nrow(f$unfitres)
+   length(which(f$residualtests$resivartrendP < 0.05))
+   length(which(f$residualtests$resivartrendP < 0.05)) / length(f$residualtests$resivartrendP)
+   # count the number of unsuccessful fits for each cause
+   table(f$unfitres$cause)
+   
+   
+   ### test on metabolomic data #################
+   data(Scenedesmus_metab)
+   (o <- continuousomicdata(Scenedesmus_metab))
+   plot(o)
+   (s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.05))
+   (f <- drcfit(s_quad, progressbar = TRUE, information.criterion = IC))
+   plot(f, plot.type = "fitted_residuals")
+   nrow(f$fitres)
+   nrow(f$unfitres)
+   length(which(f$residualtests$resivartrendP < 0.05))
+   length(which(f$residualtests$resivartrendP < 0.05)) / length(f$residualtests$resivartrendP)
+   # count the number of unsuccessful fits for each cause
+   table(f$unfitres$cause)
+   
+   which(f$residualtests$resivartrendP < 0.05)
+   (itemswithvartrendinf <- 
+        f$fitres$id[f$residualtests$resivartrendP < 0.05])
+    targetplot(itemswithvartrendinf, f)
+   
+    ### test on metabolomic data not in log scale #################
+    data(Scenedesmus_metab)
+    metabnotinlog <- Scenedesmus_metab
+    metabnotinlog[-1, -1] <- 10^metabnotinlog[-1, -1] 
+    
+    (o <- continuousomicdata(metabnotinlog))
+    plot(o)
+    (s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.05))
+    (f <- drcfit(s_quad, progressbar = TRUE, information.criterion = IC))
+    plot(f, plot.type = "fitted_residuals")
+    nrow(f$fitres)
+    nrow(f$unfitres)
+    length(which(f$residualtests$resivartrendP < 0.05))
+    length(which(f$residualtests$resivartrendP < 0.05)) / length(f$residualtests$resivartrendP)
+    
+    which(f$residualtests$resivartrendP < 0.05)
+    (itemswithvartrendinf <- 
+        f$fitres$id[f$residualtests$resivartrendP < 0.05])
+    targetplot(itemswithvartrendinf, f)
+    
+ }
> 
> proc.time()
   user  system elapsed 
   9.39    0.81   10.20