Fix Bioconductor warnings before release

Bioconductor Warnings
bhklab · Apr 16, 2024 · 3dab6c1 · 3dab6c1
2 parents 43cadc9 + c4967cc
commit 3dab6c1
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diff --git a/.Rbuildignore b/.Rbuildignore
@@ -6,3 +6,4 @@ CONTRIBUTING.md
 ^docs$
 ^pkgdown$
 ^LICENSE\.md$
+.github
diff --git a/.github/workflows/R-CMD-check-bioc.yml b/.github/workflows/R-CMD-check-bioc.yml
@@ -22,10 +22,6 @@
 
 on:
   push:
-    branches:
-      - master
-      - main
-      - devel
   pull_request:
     branches:
       - master

diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,8 +1,8 @@
 Package: PharmacoGx
 Type: Package
 Title: Analysis of Large-Scale Pharmacogenomic Data
-Version: 3.7.2
-Date: 2024-02-02
+Version: 3.7.5
+Date: 2024-04-08
 Authors@R: c(
     person(given="Petr", family="Smirnov", email="[email protected]",
         role=c("aut")),

diff --git a/NAMESPACE b/NAMESPACE
@@ -111,8 +111,6 @@ importClassesFrom(CoreGx,CoreSet)
 importClassesFrom(CoreGx,LongTable)
 importClassesFrom(CoreGx,TreatmentResponseExperiment)
 importClassesFrom(MultiAssayExperiment,MultiAssayExperiment)
-importClassesFrom(S4Vectors,DataFrame)
-importClassesFrom(S4Vectors,List)
 importFrom(Biobase,AnnotatedDataFrame)
 importFrom(BiocParallel,bplapply)
 importFrom(CoreGx,"sampleInfo<-")
@@ -145,7 +143,6 @@ importFrom(CoreGx,sampleNames)
 importFrom(CoreGx,subsetByFeature)
 importFrom(CoreGx,treatmentNames)
 importFrom(CoreGx,updateSampleId)
-importFrom(MultiAssayExperiment,MultiAssayExperiment)
 importFrom(S4Vectors,DataFrame)
 importFrom(S4Vectors,SimpleList)
 importFrom(S4Vectors,metadata)
@@ -162,22 +159,11 @@ importFrom(SummarizedExperiment,colData)
 importFrom(SummarizedExperiment,rowData)
 importFrom(boot,boot)
 importFrom(boot,boot.ci)
-importFrom(checkmate,assert)
-importFrom(checkmate,assertCharacter)
-importFrom(checkmate,assertClass)
-importFrom(checkmate,assertDataFrame)
 importFrom(checkmate,assertDataTable)
 importFrom(checkmate,assertInt)
-importFrom(checkmate,assertList)
 importFrom(checkmate,assertLogical)
 importFrom(checkmate,assertNumeric)
-importFrom(checkmate,assertSubset)
 importFrom(coop,pcor)
-importFrom(data.table,":=")
-importFrom(data.table,as.data.table)
-importFrom(data.table,data.table)
-importFrom(data.table,merge.data.table)
-importFrom(data.table,tstrsplit)
 importFrom(downloader,download)
 importFrom(grDevices,dev.off)
 importFrom(grDevices,palette)
@@ -225,8 +211,6 @@ importFrom(utils,sessionInfo)
 importFrom(utils,setTxtProgressBar)
 importFrom(utils,txtProgressBar)
 importFrom(utils,write.table)
-importMethodsFrom(BiocGenerics,"annotation<-")
-importMethodsFrom(BiocGenerics,annotation)
 importMethodsFrom(CoreGx,"annotation<-")
 importMethodsFrom(CoreGx,"curation<-")
 importMethodsFrom(CoreGx,"datasetType<-")

diff --git a/R/PharmacoSet-class.R b/R/PharmacoSet-class.R
@@ -341,130 +341,6 @@ checkPsetStructure <-
       }
     }
 
-#    #####
-#    # Checking cell
-#    #####
-#    if('tissueid' %in% colnames(sampleInfo(object))) {
-#      if('unique.tissueid' %in% colnames(curation(object)$tissue))
-#      {
-#        if(length(intersect(rownames(curation(object)$tissue),
-#                            sampleNames(object)) != nrow(sampleInfo(object))) {
-#          message('rownames of curation tissue slot should be the same as cell
-#                  slot (curated cell ids)')
-#        } else{
-#          if(length(intersect(sampleInfo(object)$tissueid,
-#                              curation(object)$tissue$unique.tissueid)) !=
-#             length(table(sampleInfo(object)$tissueid))){
-#            message('tissueid should be the same as unique tissue id from tissue
-#                    curation slot')
-#          }
-#        }
-#      } else {
-#        message('unique.tissueid which is curated tissue id across data set
-#                should be a column of tissue curation slot')
-#      }
-#      if(any(is.na(sampleInfo(object)[,'tissueid']) | sampleInfo(object)[,'tissueid']=='',
-#             na.rm=TRUE)){
-#        message(sprintf('There is no tissue type for this cell line(s): %s',
-#                        paste(rownames(sampleInfo(object))[which(is.na(
-#                          sampleInfo(object)[,'tissueid']) |
-#                            sampleInfo(object)[,'tissueid']=='')], collapse=' ')))
-#      }
-#    } else {
-#      warning('tissueid does not exist in cell slot')
-#    }
-#
-#    if('unique.sampleid' %in% colnames(curation(object)$cell)) {
-#      if(length(intersect(curation(object)$cell$unique.sampleid,
-#                          sampleNames(object)) != nrow(sampleInfo(object))) {
-#        print('rownames of cell slot should be curated cell ids')
-#      }
-#    } else {
-#      print('unique.sampleid which is curated cell id across data set should be a
-#            column of cell curation slot')
-#    }
-##     if("sampleid" %in% colnames(sampleInfo(object))) {
-##       if(length(intersect(curation(object)$cell$sampleid, sampleNames(object))
-##    != nrow(sampleInfo(object))) {
-##         print('values of sampleid column should be curated cell line ids')
-##       }
-##     } else {
-##       print('sampleid which is curated cell id across data set should be a column of cell slot')
-##     }
-#
-#    if(length(intersect(rownames(curation(object)$cell),
-#                        sampleNames(object)) != nrow(sampleInfo(object))) {
-#      print('rownames of curation cell slot should be the same as cell slot
-#            (curated cell ids)')
-#    }
-#
-#    if('unique.treatmentid' %in% colnames(curation(object)$treatment)) {
-#      if(length(intersect(curation(object)$treatment$unique.treatmentid,
-#                          rownames(treatmentInfo(drug)))) != nrow(treatmentInfo(drug))) {
-#        print('rownames of drug slot should be curated drug ids')
-#      }
-#    } else {
-#      print('unique.treatmentid which is curated drug id across data set should be a
-#            column of drug curation slot')
-#    }
-#
-##     if("treatmentid" %in% colnames(treatmentInfo(drug))) {
-##       if(length(intersect(curation(object)$treatment$treatmentid,
-##    rownames(treatmentInfo(drug)))) != nrow(treatmentInfo(drug))) {
-##         print('values of treatmentid column should be curated drug ids')
-##       }
-##     } else {
-##       print('treatmentid which is curated drug id across data set should be a
-##    column of drug slot')
-##     }
-#
-#    if(length(intersect(rownames(curation(object)$cell),
-#                        sampleNames(object)) != nrow(sampleInfo(object))) {
-#      print('rownames of curation drug slot should be the same as drug
-#            slot (curated drug ids)')
-#    }
-#
-#    if(!is(sampleInfo(object), 'data.frame')) {
-#      warning('cell slot class type should be dataframe')
-#    }
-#    if(!is(treatmentInfo(drug), 'data.frame')) {
-#      warning('drug slot class type should be dataframe')
-#    }
-#    if(datasetType(object) %in% c('sensitivity', 'both'))
-#    {
-#      if(!is(sensitivityInfo(object), 'data.frame')) {
-#        warning('sensitivity info slot class type should be dataframe')
-#      }
-#      if("sampleid" %in% colnames(sensitivityInfo(object))) {
-#        if(!all(sensitivityInfo(object)[,"sampleid"] %in% sampleNames(object)){
-#          warning('not all the cell lines in sensitivity data are in cell slot')
-#        }
-#      }else {
-#        warning('sampleid does not exist in sensitivity info')
-#      }
-#      if("treatmentid" %in% colnames(sensitivityInfo(object))) {
-#        drug.ids <- unique(sensitivityInfo(object)[,"treatmentid"])
-#        drug.ids <- drug.ids[grep('///',drug.ids, invert=TRUE)]
-#        if(!all(drug.ids %in% rownames(treatmentInfo(drug)))) {
-#          print('not all the drugs in sensitivity data are in drug slot')
-#        }
-#      }else {
-#        warning('treatmentid does not exist in sensitivity info')
-#      }
-#
-#      if(any(!is.na(sensitivityRaw(object)))) {
-#        if(!all(dimnames(sensitivityRaw(object))[[1]] %in%
-#                rownames(sensitivityInfo(object)))) {
-#          warning('For some experiments there is raw sensitivity data but no
-#                  experiment information in sensitivity info')
-#        }
-#      }
-#      if(!all(rownames(sensitivityProfiles(object)) %in%
-#              rownames(sensitivityInfo(object)))) {
-#        warning('For some experiments there is sensitivity profiles but no
-#                experiment information in sensitivity info')
-#      }
-#    }
 }
 
 

diff --git a/R/computeSynergy.R b/R/computeSynergy.R
@@ -1126,7 +1126,9 @@ setMethod("computeZIPdelta", signature(object = "TreatmentResponseExperiment"),
 #' @examples
 #' \dontrun{
 #' ## ZIP is optional. Will be recomputed if not provided.
-#' combo_profiles <- CoreGx::buildComboProfiles(tre, c("HS", "EC50", "E_inf", "ZIP", "combo_viability"))
+#' combo_profiles <- CoreGx::buildComboProfiles(
+#'      tre, 
+#'      c("HS", "EC50", "E_inf", "ZIP", "combo_viability"))
 #' combo_profiles[,
 #'         .computeZIPdelta(
 #'             treatment1id = treatment1id,

diff --git a/R/drugDoseResponseCurve.R b/R/drugDoseResponseCurve.R
@@ -18,7 +18,7 @@
 #'
 #' # Generate a plot from one or more PSets
 #' data(GDSCsmall)
-#' drugDoseResponseCurve(drug="Doxorubicin", cellline="22RV", pSets=GDSCsmall)
+#' drugDoseResponseCurve(drug="Doxorubicin", cellline="22RV1", pSets=GDSCsmall)
 #' }
 #'
 #' @param drug `character(1)` A drug name for which the drug response curve should be
@@ -61,6 +61,8 @@
 #' @param legend.loc And argument passable to xy.coords for the position to place the legend.
 #' @param trunc `logical(1)` Should the viability values be truncated to lie in \[0-100\] before doing the fitting
 #' @param verbose `logical(1)` Should warning messages about the data passed in be printed?
+#' @param sample_col `character(1)` The name of the column in the profiles assay that contains the sample IDs.
+#' @param treatment_col `character(1)` The name of the column in the profiles assay that contains the treatment IDs.
 #'
 #' @return Plots to the active graphics device and returns an invisible NULL.
 #'
@@ -91,7 +93,9 @@ function(drug,
          cex = 0.7,
          cex.main = 0.9,
          legend.loc = "topright",
-         verbose=TRUE) {
+         verbose=TRUE,
+         sample_col = "sampleid",
+         treatment_col = "treatmentid") {
   if(!missing(pSets)){
     if (!is(pSets, "list")) {
       if (is(pSets, "PharmacoSet")) {
@@ -167,28 +171,42 @@ function(drug,
     }
   }
 
-  common.range.star <- FALSE
-
   if (missing(plot.type)) {
     plot.type <- "Actual"
   }
 
+  if(is(treatmentResponse(pSets[[1]]), "LongTable")){
+    pSets[[1]] <- subsetByTreatment(pSets[[1]], treatments=drug)
+  }
+  pSets[[1]] <- subsetBySample(pSets[[1]], samples=cellline)
+
   doses <- list(); responses <- list(); legend.values <- list(); j <- 0; pSetNames <- list()
   if(!missing(pSets)){
     for(i in seq_len(length(pSets))) {
-      exp_i <- which(sensitivityInfo(pSets[[i]])[ ,"sampleid"] == cellline & sensitivityInfo(pSets[[i]])[ ,"treatmentid"] == drug)
+      exp_i <- which(sensitivityInfo(pSets[[i]])[ ,sample_col] == cellline & sensitivityInfo(pSets[[i]])[ ,treatment_col] == drug)
       if(length(exp_i) > 0) {
         if (summarize.replicates) {
           pSetNames[[i]] <- name(pSets[[i]])
-          if (length(exp_i) == 1) {
-            drug.responses <- as.data.frame(cbind("Dose"=as.numeric(as.vector(sensitivityRaw(pSets[[i]])[exp_i, , "Dose"])),
+          drug.responses <- as.data.frame(cbind("Dose"=as.numeric(as.vector(sensitivityRaw(pSets[[i]])[exp_i, , "Dose"])),
               "Viability"=as.numeric(as.vector(sensitivityRaw(pSets[[i]])[exp_i, , "Viability"]))), stringsAsFactors=FALSE)
-            drug.responses <- drug.responses[complete.cases(drug.responses), ]
-          }else{
-            drug.responses <- as.data.frame(cbind("Dose"=apply(sensitivityRaw(pSets[[i]])[exp_i, , "Dose"], 2, function(x){median(as.numeric(x), na.rm=TRUE)}),
-              "Viability"=apply(sensitivityRaw(pSets[[i]])[exp_i, , "Viability"], 2, function(x){median(as.numeric(x), na.rm=TRUE)})), stringsAsFactors=FALSE)
-            drug.responses <- drug.responses[complete.cases(drug.responses), ]
-          }
+          drug.responses <- drug.responses[complete.cases(drug.responses), ]
+          # tryCatch(
+          #   drug.responses <- as.data.frame(cbind("Dose"=as.numeric(as.vector(sensitivityRaw(pSets[[i]])[exp_i, , "Dose"])),
+          #     "Viability"=as.numeric(as.vector(sensitivityRaw(pSets[[i]])[exp_i, , "Viability"]))), stringsAsFactors=FALSE)
+          #   drug.responses <- drug.responses[complete.cases(drug.responses), ]
+          # , error = function(e) {
+          #   if (length(exp_i) == 1) {
+          #   drug.responses <- as.data.frame(cbind("Dose"=as.numeric(as.vector(sensitivityRaw(pSets[[i]])[exp_i, , "Dose"])),
+          #     "Viability"=as.numeric(as.vector(sensitivityRaw(pSets[[i]])[exp_i, , "Viability"]))), stringsAsFactors=FALSE)
+          #   drug.responses <- drug.responses[complete.cases(drug.responses), ]
+          # }else{
+          #   drug.responses <- as.data.frame(cbind("Dose"=apply(sensitivityRaw(pSets[[i]])[exp_i, , "Dose"], 1, function(x){median(as.numeric(x), na.rm=TRUE)}),
+          #     "Viability"=apply(sensitivityRaw(pSets[[i]])[exp_i, , "Viability"], 2, function(x){median(as.numeric(x), na.rm=TRUE)})), stringsAsFactors=FALSE)
+          #   drug.responses <- drug.responses[complete.cases(drug.responses), ]
+          # }
+          # })
+
+
           doses[[i]] <- drug.responses$Dose
           responses[[i]] <- drug.responses$Viability
           names(doses[[i]]) <- names(responses[[i]]) <- seq_len(length(doses[[i]]))
@@ -201,7 +219,7 @@ function(drug,
               legend.values[[i]] <- sprintf("%s = %s", legends.label, round(as.numeric(sensitivityProfiles(pSets[[i]])[exp_i, legends.label]), digits=2))
             }
           } else {
-            legend.values[[i]] <- ""
+            legend.values[i] <- ""
           }
         }else {
           for (exp in exp_i) {
@@ -224,7 +242,7 @@ function(drug,
               }
             } else {
               tt <- unlist(strsplit(rownames(sensitivityInfo(pSets[[i]]))[exp], split="_"))
-              if (tt[1] == "treatmentid") {
+              if (tt[1] == treatment_col) {
                 legend.values[[j]] <- tt[2]
               }else{
                 legend.values[[j]] <- rownames(sensitivityInfo(pSets[[i]]))[exp]
@@ -323,13 +341,7 @@ function(drug,
     legends<- c(legends, sprintf("%s%s", pSetNames[[i]], legend.values[[i]]))
     legends.col <-  c(legends.col, mycol[i])
   }
-  if (common.range.star) {
-    if (length(doses) > 1) {
-      for (i in seq_len(length(doses))) {
-        points(common.ranges[[i]], responses[[i]][names(common.ranges[[i]])], pch=8, col=mycol[i])
-      }
-    }
-  }
+
   legend(legend.loc, legend=legends, col=legends.col, bty="n", cex=cex, pch=c(15,15))
   return(invisible(NULL))
 }

diff --git a/R/methods-[.R b/R/methods-[.R
@@ -1,6 +1,4 @@
 # ==== PharmacoSet Class
-
-
 #'`[`
 #'
 #' @examples
-Original file line number
+Diff line change
@@ Expand Up / @@ -6,3 +6,4 @@ CONTRIBUTING.md @@
     ^docs$
     ^pkgdown$
     ^LICENSE\.md$
+    .github