Merge pull request #12 from LUMC/develop

Develop -> v1.3.1

DESCRIPTION

@@ -1,43 +1,44 @@
 Package: dgeAnalysis
 Type: Package
 Title: dgeAnalysis
-Version: 1.1.0
+Version: 1.3.1
 Author@R:
   person("Tom", "Kuipers", email = "t.b.kuipers@outlook.com", role = c("aut", "cre"))
 Description:
     R shiny tool to perform differential gene expression and view the results interactively.
 Depends: R (>= 3.6.1)
-RoxygenNote: 7.0.2
+RoxygenNote: 7.1.1
 License: MIT + file LICENSE
 Encoding: UTF-8
 LazyData: true
 Imports: 
-    shiny (>= 1.4.0),
+    shiny (>= 1.5.0),
     shinydashboard (>= 0.7.1),
-    shinyWidgets (>= 0.5.0),
-    shinycssloaders (>= 0.3),
-    shinyjs (>= 1.1),
+    shinyWidgets (>= 0.5.3),
+    shinycssloaders (>= 1.0.0),
+    shinyjs (>= 2.0.0),
     BiocManager (>= 1.30.10),
-    knitr (>= 1.27),
-    tidyr (>= 1.0.2),
-    scales (>= 1.1.0),
-    broom (>= 0.5.4),
-    plotly (>= 4.9.1),
-    igraph (>= 1.2.4.2),
-    reshape2 (>= 1.4.3),
-    SummarizedExperiment (>= 1.16.1),
-    edgeR (>= 3.28.0),
-    limma (>= 3.42.1),
-    DESeq2 (>= 1.26.0),
-    clusterProfiler (>= 3.14),
-    DOSE (>= 3.12.0),
-    graphite (>= 1.32.0),
-    ReactomePA (>= 1.30.0),
-    org.Hs.eg.db (>= 3.10),
-    org.Mm.eg.db (>= 3.10),
-    rmarkdown (>= 2.1)
+    knitr (>= 1.30),
+    tidyr (>= 1.1.2),
+    scales (>= 1.1.1),
+    broom (>= 0.7.1),
+    plotly (>= 4.9.2),
+    igraph (>= 1.2.5),
+    reshape2 (>= 1.4.4),
+    SummarizedExperiment (>= 1.18.2),
+    edgeR (>= 3.30.3),
+    limma (>= 3.44.3),
+    DESeq2 (>= 1.28.1),
+    clusterProfiler (>= 3.16.1),
+    DOSE (>= 3.14.0),
+    graphite (>= 1.34.0),
+    ReactomePA (>= 1.32.0),
+    org.Hs.eg.db (>= 3.11.4),
+    org.Mm.eg.db (>= 3.11.4),
+    rmarkdown (>= 2.4),
+    WGCNA (>= 1.69)
 biocViews: Annotation, Clustering, GeneSetEnrichment, GO, KEGG,
     MultipleComparison, Pathways, Reactome, Visualization,
-    Sequencing, RNASeq, ChIPSeq, GeneExpression, Transcription,
+    Sequencing, RNASeq, GeneExpression, Transcription,
     Normalization, DifferentialExpression, Bayesian, Regression,
-    PrincipalComponent
+    PrincipalComponent, WGCNA

NAMESPACE

@@ -1 +1,55 @@
-exportPattern("^[[:alpha:]]+")
+# Generated by roxygen2: do not edit by hand
+
+export(addAnnotationsFromTableToSE)
+export(addSamplesFromTableToSE)
+export(alignmentSummary)
+export(alignmentSummaryPlot)
+export(barcodePlot)
+export(biasPlot)
+export(cnetPlotly)
+export(complexityData)
+export(complexityPlot)
+export(countDistributionBoxPlot)
+export(countDistributionLinePlot)
+export(createContrast)
+export(createDesign)
+export(createMatrix)
+export(deRatioPlot)
+export(emap_plotly)
+export(enrichBarplot)
+export(extract_geneSets)
+export(gamConfidenceFit)
+export(geneStrandBar)
+export(getCount)
+export(get_dendrogram_data)
+export(get_geneList)
+export(get_organismID)
+export(heatplotly)
+export(informationBox)
+export(list2df)
+export(list2graph)
+export(ma_plot)
+export(multidimensionalScaling2dPlot)
+export(multidimensionalScaling3dPlot)
+export(overlap_ratio)
+export(pValuePlot)
+export(plot_module_trait_relation_heat)
+export(plot_modules)
+export(plot_power)
+export(plot_soft)
+export(plot_trait_heat)
+export(plotlyGraph)
+export(plotly_dendro_heat)
+export(plotly_dendrogram)
+export(readCountsFromTable)
+export(relevelSamples)
+export(samplePca2dPlot)
+export(samplePca3dPlot)
+export(stackDge)
+export(startApp)
+export(topDgeHeatmapPlot)
+export(update_n)
+export(variableHeatmapPlot)
+export(variancePcaPlot)
+export(volcanoPlot)
+export(voomPlot)

R/de.R

@@ -2,13 +2,14 @@
 ## ----- Read files -----
 
 
-## readCountsFromTable()
-##  Add all counts that are in samples in SummerizedExperiment
-## Parameters:
-##  data_counts = Dataframe, Containing all raw count data
-##  data_samples = Dataframe, Containing all sample data
-## Returns:
-##  se = SummerizedExperiment, With counts
+#' Add all counts that are in samples in SummerizedExperiment.
+#'
+#' @param data_counts Dataframe, Containing all raw count data
+#' @param data_samples Dataframe, Containing all sample data
+#'
+#' @return se, (SummerizedExperiment) With counts
+#' 
+#' @export
 
 readCountsFromTable <- function(data_counts, data_samples) {
   out <- as.matrix(data_counts[, colnames(data_counts) %in% rownames(data_samples)])
@@ -17,31 +18,32 @@ readCountsFromTable <- function(data_counts, data_samples) {
 }
 
 
-## addSamplesFromTableToSE()
-##  Add samples to the SummerizedExperiment
-## Parameters:
-##  se = SummerizedExperiment, With counts
-##  data_samples = Dataframe, Containing all sample data
-## Returns:
-##  se = SummerizedExperiment, With samples and counts
+#' Add samples to the SummerizedExperiment.
+#'
+#' @param se SummerizedExperiment, With counts
+#' @param data_samples Dataframe, Containing all sample data
+#'
+#' @return se, (SummerizedExperiment) With samples and counts
+#' 
+#' @export
 
 addSamplesFromTableToSE <- function(se, data_samples){
   data_samples <- droplevels(data_samples)
   samples <- intersect(colnames(se), rownames(data_samples))
   se <- se[,samples]
-  colData(se) <- DataFrame(data_samples[samples,])
-  names(colData(se)) <- colnames(data_samples)
+  colData(se) <- DataFrame(data_samples[samples,, drop = FALSE])
   se
 }
 
 
-## addAnnotationsFromTableToSE()
-##  Add annotation to the SummerizedExperiment
-## Parameters:
-##  se = SummerizedExperiment, With samples and counts
-##  data_annotation = Dataframe, Containing all annotation data
-## Returns:
-##  se = SummerizedExperiment, With samples, counts and annotation
+#' Add annotation to the SummerizedExperiment.
+#'
+#' @param se SummerizedExperiment, With counts
+#' @param data_annotation Dataframe, Containing all annotation data
+#'
+#' @return se, (SummerizedExperiment) With samples, counts and annotation
+#' 
+#' @export
 
 addAnnotationsFromTableToSE <- function(se, data_annotation){
   features <- intersect(rownames(se), rownames(data_annotation))
@@ -55,13 +57,14 @@ addAnnotationsFromTableToSE <- function(se, data_annotation){
 ## ----- Analysis utility -----
 
 
-## getCount()
-##  Count the read counts per feature to find number of reads that are aligned, not aligned, etc.
-## Parameters:
-##  x = String, Containing the value on which to count reads
-##  raw = Dataframe, Containing count data
-## Returns:
-##  Integer, With total counted reads
+#' Count the read counts per feature to find number of reads that are aligned, not aligned, etc.
+#'
+#' @param x Containing the value/label on which to count reads
+#' @param raw Dataframe, Containing count data
+#'
+#' @return Integer, With total counted reads
+#' 
+#' @export
 
 getCount <- function(x, raw){
   if (x["feature"] %in% rownames(raw)) {
@@ -73,12 +76,13 @@ getCount <- function(x, raw){
 }
 
 
-## alignmentSummary()
-##  Creates dataframe with counts per mapping feature (aligned, not aligned, etc.)
-## Parameters:
-##  se = SummerizedExperiment, With samples, counts (and annotation)
-## Returns:
-##  out = Dataframe, With total counts per available mapping feature
+#' Creates dataframe with counts per mapping feature (aligned, not aligned, etc.).
+#'
+#' @param se SummerizedExperiment, With samples, counts (and annotation)
+#'
+#' @return out, (Dataframe) With total counts per available mapping feature
+#' 
+#' @export
 
 alignmentSummary <- function(se){
   specialFeatures <- rownames(se)[ grepl( "^__", rownames(se) ) ]
@@ -88,13 +92,14 @@ alignmentSummary <- function(se){
 }
 
 
-## complexityData()
-##  Creates dataframe with number of reads per gene, ordered on genes with the most reads assigned.
-## Parameters:
-##  se = SummerizedExperiment, With samples, counts (and annotation)
-##  max = Integer, The maximum rank that is used
-## Returns:
-##  out = Dataframe, With total read counts per gene
+#' Creates dataframe with number of reads per gene, ordered on genes with the most reads assigned.
+#'
+#' @param se SummerizedExperiment, With samples, counts (and annotation)
+#' @param max Integer, The maximum rank that is used
+#'
+#' @return out, (Dataframe) With total read counts per gene
+#' 
+#' @export
 
 complexityData <- function(se, max){
   features <- rownames(se)[ ! grepl( "^__", rownames(se) ) ]
@@ -111,12 +116,14 @@ complexityData <- function(se, max){
 }
 
 
-## stackDge()
-##  Stacks total DGE counts based on: mapping feature (aligned, not aligned, etc.), sample and LogCPM
-## Parameters:
-##  dge = DGE list object, containing samples and counts
-## Returns:
-##  count = Dataframe, With mapping feature, sample and LogCPM
+#' Stacks total DGE counts based on: mapping feature (aligned, not aligned, etc.), sample and LogCPM.
+#'
+#' @param dge DGE list object, containing samples and counts
+#' @param max Integer, The maximum rank that is used
+#'
+#' @return count, (Dataframe) With mapping feature, sample and LogCPM
+#' 
+#' @export
 
 stackDge <- function(dge){
   count <- stack(dge$counts)
@@ -125,14 +132,15 @@ stackDge <- function(dge){
 }
 
 
-## gamConfidenceFit()
-##  Calculates a confidence fit for various plots.
-##  Model used is GAM to calculate predictions
-## Parameters:
-##  deTab = Dataframe, with all analysis results
-##  biasColumn = String, Value on which to calculate confidence
-## Returns:
-##  prediction = Vector, With coordinates of prediction locations (line plot)
+#' Calculates a confidence fit for various plots.
+#' Model used is GAM to calculate predictions.
+#'
+#' @param deTab Dataframe, with all analysis results
+#' @param biasColumn String, Value on which to calculate confidence
+#'
+#' @return prediction, (Vector) With coordinates of prediction locations (line plot)
+#' 
+#' @export
 
 gamConfidenceFit <- function(deTab, biasColumn) {
   method.args = list()
@@ -144,7 +152,9 @@ gamConfidenceFit <- function(deTab, biasColumn) {
 
   base.args <- list(quote(formula), data = quote(deTab))
   gamModel <- do.call(mgcv::gam, c(base.args, method.args))
-  prediction <- augment(gamModel)
+
+  prediction <- deTab[, c(biasColumn, "avgLog2FC")]
+  prediction <- cbind(prediction, predict(gamModel, se.fit=TRUE))
   prediction <- prediction[order(prediction[[biasColumn]]), ]
 
   setRange <- range(1, nrow(prediction))