Merge pull request #22 from LUMC/develop

Develop

CHANGELOG.md

@@ -4,6 +4,19 @@ Changelog
 <!--
 Newest changes should be on top.
 -->
+version 1.5.1
+---------------------------
++ Remove heatmap plot in enrichment
++ Fix empty table not shown
++ Update hover info
++ Apply icon name change in updated package (fontawesome)
++ Update markdowns to use non-interactive ggplot2 plots
++ Reorder chunks in markdown
++ Remove voom plot from raw data
++ Rewrite plots to be based on ggplot2 -> ggplotly
++ Change filtering for enrichment
++ Bug fix for tSNE: Missing break in loop
+
 version 1.4.4
 ---------------------------
 + Add file names and md5 to markdown

DESCRIPTION

@@ -1,36 +1,36 @@
 Package: dgeAnalysis
 Type: Package
 Title: dgeAnalysis
-Version: 1.4.4
+Version: 1.5.1
 Author@R:
   person("Tom", "Kuipers", email = "t.b.kuipers@lumc.nl", role = c("aut", "cre"))
 Description:
     R shiny tool to perform differential gene expression and view the results interactively.
-Depends: R (>= 3.6.1)
-RoxygenNote: 7.1.1
+Depends: R (>= 4.1)
+RoxygenNote: 7.2.1
 License: MIT + file LICENSE
 Encoding: UTF-8
 LazyData: true
 Imports: 
-    shiny (>= 1.5.0),
-    shinydashboard (>= 0.7.1),
-    shinyWidgets (>= 0.5.3),
+    shiny (>= 1.7.2),
+    shinydashboard (>= 0.7.2),
+    shinyWidgets (>= 0.7.2),
     shinycssloaders (>= 1.0.0),
-    shinyjs (>= 2.0.0),
-    BiocManager (>= 1.30.10),
-    knitr (>= 1.30),
-    SummarizedExperiment (>= 1.18.2),
-    edgeR (>= 3.30.3),
-    limma (>= 3.44.3),
-    DESeq2 (>= 1.28.1),
-    tidyr (>= 1.1.2),
-    scales (>= 1.1.1),
-    broom (>= 0.7.1),
-    plotly (>= 4.9.2),
-    Rtsne (>= 0.15),
-    rmarkdown (>= 2.4),
-    gprofiler2 (>= 0.2.0),
-    igraph (>= 1.2.5)
+    shinyjs (>= 2.1.0),
+    BiocManager (>= 1.30.18),
+    knitr (>= 1.39),
+    SummarizedExperiment (>= 1.24.0),
+    edgeR (>= 3.36.0),
+    limma (>= 3.50.3),
+    DESeq2 (>= 1.34.0),
+    tidyr (>= 1.3.2),
+    scales (>= 1.2.0),
+    broom (>= 1.0.0),
+    plotly (>= 4.10.0),
+    Rtsne (>= 0.16),
+    rmarkdown (>= 2.14),
+    gprofiler2 (>= 0.2.1),
+    igraph (>= 1.3.4),
 biocViews: Annotation, Clustering, GeneSetEnrichment, GO, KEGG,
     MultipleComparison, Pathways, Reactome, Visualization,
     Sequencing, RNASeq, GeneExpression, Transcription,

NAMESPACE

@@ -2,44 +2,49 @@
 
 export(addAnnotationsFromTableToSE)
 export(addSamplesFromTableToSE)
-export(alignmentSummary)
-export(alignmentSummaryPlot)
-export(barcodePlot)
-export(biasPlot)
+export(alignment_summary)
+export(bar_plot)
+export(barcode)
+export(barcode_plot)
+export(bias_gc)
 export(cnetPlotly)
+export(cnet_data)
+export(complexity)
 export(complexityData)
-export(complexityPlot)
-export(countDistributionBoxPlot)
-export(countDistributionLinePlot)
+export(count_dist)
 export(createContrast)
 export(createDesign)
 export(createMatrix)
-export(deRatioPlot)
-export(enrichBarplot)
-export(enrichDE)
+export(de_ratio)
+export(dendro_data)
+export(dendro_plot)
+export(enrich_bar)
+export(enrich_barDE)
 export(extract_geneSets)
-export(gamConfidenceFit)
-export(geneStrandBar)
+export(fix_violin_hover)
+export(gene_strand)
 export(getCount)
 export(get_dendrogram_data)
 export(get_organismID)
-export(heatplotly)
+export(heat_de)
+export(heat_var)
+export(heatmap_plot)
 export(informationBox)
+export(line_plot)
 export(list2df)
 export(list2graph)
-export(ma_plot)
-export(multidimensionalScalingPlot)
-export(pValuePlot)
-export(pcaPlot)
-export(plotlyGraph)
-export(plotly_dendrogram)
+export(ma)
+export(mds_clust)
+export(network_plot)
+export(pca_data)
+export(pvalue)
 export(readCountsFromTable)
 export(relevelSamples)
+export(scatter_plot)
 export(stackDge)
 export(startApp)
-export(topDgeHeatmapPlot)
-export(tsnePlot)
-export(variableHeatmapPlot)
-export(variancePcaPlot)
-export(volcanoPlot)
-export(voomPlot)
+export(tsne_data)
+export(violin_dist)
+export(violin_plot)
+export(volcano)
+export(voom_data)

R/de.R → R/de_functions.R

@@ -1,7 +1,4 @@
 
-## ----- Read files -----
-
-
 #' Add all counts that are in samples in SummerizedExperiment.
 #'
 #' @param data_counts Dataframe, Containing all raw count data
@@ -52,10 +49,6 @@ addAnnotationsFromTableToSE <- function(se, data_annotation) {
   se
 }
 
-## --------------------------------------------------------------------------
-
-## ----- Analysis utility -----
-
 
 #' Count the read counts per feature to find number of reads that are aligned, not aligned, etc.
 #'
@@ -76,23 +69,6 @@ getCount <- function(x, raw) {
 }
 
 
-#' 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))]
-  out <-  expand.grid(feature = c("aligned", specialFeatures),
-                sample = colnames(se))
-  out$count <- apply(out, 1, getCount, assays(se)$counts)
-  out
-}
-
-
 #' Creates dataframe with number of reads per gene, ordered on genes with the most reads assigned.
 #'
 #' @param se SummerizedExperiment, With samples, counts (and annotation)
@@ -111,8 +87,7 @@ complexityData <- function(se, max) {
     sorted <- sort(values, T)
     total <- sum(sorted)
     out[out$sample == x, "value"] <- cumsum(sorted)[1:max]
-    out[out$sample == x, "fraction"] <-
-      out[out$sample == x, "value"] / total
+    out[out$sample == x, "fraction"] <- out[out$sample == x, "value"] / total * 100
   }
   out
 }
@@ -134,42 +109,25 @@ stackDge <- function(dge) {
 }
 
 
-#' Calculates a confidence fit for various plots.
-#' Model used is GAM to calculate predictions.
+#' Fix hover info for violin plot, as it cant find CPM values
 #'
-#' @param deTab Dataframe, with all analysis results
-#' @param biasColumn String, Value on which to calculate confidence
+#' @param plot List object, List with plot object from ggplotly
 #'
-#' @return prediction, (Vector) With coordinates of prediction locations (line plot)
+#' @return plot, List object with fixed hover
 #'
 #' @export
 
-gamConfidenceFit <- function(deTab, biasColumn) {
-  method.args = list()
-  method.args$method <- "REML"
-
-  formula <- avgLog2FC ~ s(columnHere, bs = "cs")
-  formula <- paste(gsub("columnHere", parse(text = biasColumn), formula))
-  formula <- eval(parse(text = gsub(
-    "\\", "", paste(formula[2], formula[3], sep = " ~ "), fixed = TRUE
-  )))
-
-  base.args <- list(quote(formula), data = quote(deTab))
-  gamModel <- do.call(mgcv::gam, c(base.args, method.args))
-
-  prediction <- deTab[, c(biasColumn, "avgLog2FC")]
-  prediction <- cbind(prediction, predict(gamModel, se.fit = TRUE))
-  prediction <- prediction[order(prediction[[biasColumn]]),]
+fix_violin_hover <- function(plot) {
+  for (x in 1:length(plot[["x"]][["data"]])) {
+    layer <- plot[["x"]][["data"]][[x]]
+    logcpm <- round(layer[["x"]], 2)
+    temp <- sub("(<br />).*", "", layer[["text"]])
+    plot[["x"]][["data"]][[x]][["text"]] <- paste(temp, "\nLog2CPM:", logcpm)
+  }
 
-  setRange <- range(1, nrow(prediction))
-  result <- round(seq(setRange[1], setRange[2], length.out = 500))
-  prediction <- prediction[c(result), ]
+  plot
 }
 
-## --------------------------------------------------------------------------
-
-## ----- TREE PLOTS -----
-
 
 #' Get heigth information from tree object.
 #' Get labels/names from tree ends.
@@ -277,5 +235,3 @@ get_dendrogram_data <- function(tree,
   new <- new[order(new$x), ]
   return(new)
 }
-
-## --------------------------------------------------------------------------