@@ -1,13 +1,17 @@

 Package: GeneTonic

 Title: Enjoy Analyzing And Integrating The Results From Differential Expression 

     Analysis And Functional Enrichment Analysis

-Version: 1.3.1

-Date: 2020-10-21

+Version: 1.3.2

+Date: 2021-02-19

 Authors@R: 

     c(

         person(

             given = "Federico", family = "Marini", role = c("aut", "cre"), 

             email = "marinif@uni-mainz.de", comment = c(ORCID = "0000-0003-3252-7758")

+        ),

+		person(

+            given = "Annekathrin", family = "Ludt", role = c("aut"), 

+            email = "anneludt@uni-mainz.de", comment = c(ORCID = "0000-0002-2475-4945")

         )

     )

 Description: This package provides a Shiny application that aims to combine at 

@@ -24,6 +28,7 @@ Imports:

     backbone,

     bs4Dash,

     colorspace,

+	colourpicker,

     ComplexHeatmap,

     dendextend,

     DESeq2,

@@ -46,6 +46,7 @@ export(shake_enrichrResult)

 export(shake_fgseaResult)

 export(shake_gprofilerResult)

 export(shake_topGOtableResult)

+export(signature_volcano)

 export(styleColorBar_divergent)

 import(GO.db)

 import(SummarizedExperiment)

@@ -98,6 +99,7 @@ importFrom(bs4Dash,bs4ValueBoxOutput)

 importFrom(bs4Dash,renderbs4InfoBox)

 importFrom(bs4Dash,renderbs4ValueBox)

 importFrom(colorspace,rainbow_hcl)

+importFrom(colourpicker,colourInput)

 importFrom(dendextend,branches_attr_by_clusters)

 importFrom(dendextend,set)

 importFrom(dplyr,"%>%")

@@ -2,11 +2,16 @@

 ## New features

-* The main function `GeneTonic()` gains an extra parameter, `gtl` - this can be used to provided a named list object where a single parameter is passed (e.g. after loading in a single seralized object), while the functionality stays unaltered. 

+* The main function `GeneTonic()` gains an extra parameter, `gtl` - this can be used to provided a named list object where a single parameter is passed (e.g. after loading in a single serialized object), while the functionality stays unaltered. 

   The same `gtl` parameter is also exposed in other functions of the package - see the vignette for some examples, or check the documentation of each specific function.

 * A new function to perform fuzzy clustering (following the implementation of DAVID) is added - see `gs_fuzzyclustering()`. It returns a table with additional information on the cluster of genesets and the status of each set in the group.  

+* A new function, `signature_volcano()`, adds a signature volcano plot to the `Gene-Geneset` panel. This plot displays the genes of a chosen geneset in color, while the remaining genes of the data are shown as shaded dots in the background. 

+  The color and transparency of the displayed genes can be chosen by the user, as well as the option to display the gene names of all genes in the geneset.

+

+* `gs_summary_overview` can also generate bar plots instead of the default segment-dot (lollipop) plots

+

 # GeneTonic 1.2.0

 ## New features

@@ -14,6 +14,7 @@

 #' bs4ValueBoxOutput renderbs4InfoBox renderbs4ValueBox

 #' bs4TabPanel bs4TabCard

 #' @importFrom colorspace rainbow_hcl

+#' @importFrom colourpicker colourInput

 #' @importFrom ComplexHeatmap Heatmap HeatmapAnnotation draw

 #' @importFrom dendextend branches_attr_by_clusters set

 #' @importFrom DESeq2 vst counts estimateSizeFactors normalizationFactors sizeFactors

@@ -58,6 +58,7 @@

 #'   row.names = rownames(dds_macrophage)

 #' )

 #'

+#' 

 #' # res object

 #' data(res_de_macrophage, package = "GeneTonic")

 #' res_de <- res_macrophage_IFNg_vs_naive

@@ -706,7 +707,11 @@ GeneTonic <- function(dds,

                    label = "Number of genesets",

                    value = 15, min = 1, max = nrow(res_enrich)),

       selectInput("exp_condition", label = "Group/color by: ",

-                  choices = c(NULL, names(colData(dds))), selected = NULL, multiple = TRUE)

+                  choices = c(NULL, names(colData(dds))), selected = NULL, multiple = TRUE),

+      colourInput("col", "Select colour for volcano plot", "#1a81c2",

+                  returnName = TRUE,

+                  allowTransparent = TRUE),

+      checkboxInput("labels", label = "Display all labels", value = FALSE)

     ),

     # footer definition -------------------------------------------------------

@@ -918,6 +923,7 @@ GeneTonic <- function(dds,

       tagList(

         # verbatimTextOutput("netnode"),

         plotOutput("net_sigheatplot"),

+        plotOutput("sig_volcano"),

         uiOutput("ggs_geneset_info")

       )

     })

@@ -964,6 +970,38 @@ GeneTonic <- function(dds,

       }

     })

+    output$sig_volcano <- renderPlot({

+      g <- reactive_values$ggs_graph()

+      cur_sel <- input$ggsnetwork_selected

+      cur_node <- match(cur_sel, V(g)$name)

+      cur_nodetype <- V(g)$nodetype[cur_node]

+      validate(need(cur_nodetype == "GeneSet",

+                    message = "Please select a gene set from the Gene-Geneset Graph."

+      ))

+      cur_gsid <- res_enrich$gs_id[match(input$ggsnetwork_selected, res_enrich$gs_description)]

+      

+      if (input$labels) {

+        signature_volcano(

+          res_de,

+          res_enrich,

+          annotation_obj = annotation_obj,

+          geneset_id = cur_gsid,

+          FDR = input$de_fdr,

+          color = input$col,

+          volcano_labels = Inf

+        )

+      } else {

+        signature_volcano(

+          res_de,

+          res_enrich,

+          annotation_obj = annotation_obj,

+          geneset_id = cur_gsid,

+          FDR = input$de_fdr,

+          color = input$col

+       )

+      }

+    })

+    

     output$ggs_geneset_info <- renderUI({

       g <- reactive_values$ggs_graph()

       cur_sel <- input$ggsnetwork_selected

@@ -133,7 +133,6 @@ gs_heatmap <- function(se,

     thisset_name <- "Custom list"

   }

-  thisset_members_ids

   sig_to_keep <- (thisset_members_ids %in% rownames(se))#

   thisset_members_ids_available <- thisset_members_ids[sig_to_keep]

@@ -245,7 +245,7 @@ shake_davidResult <- function(david_output_file) {

 #' #          "Reactome_2016", 

 #' #          "WikiPathways_2019_Human")

 #' # degenes <- (deseqresult2df(res_macrophage_IFNg_vs_naive, FDR = 0.01)$SYMBOL)

-#' # if called directly withín R...

+#' # if called directly within R...

 #' # enrichr_output_macrophage <- enrichr(degenes, dbs)

 #' # or alternatively, if downloaded from the website in tabular format

 #' enrichr_output_file <- system.file("extdata", 

@@ -13,6 +13,8 @@

 #' p-value - have been specified).

 #' @param color_by Character, specifying the column of `res_enrich` to be used

 #' for coloring the plotted gene sets. Defaults sensibly to `z_score`.

+#' @param return_barchart Logical, whether to return a barchart (instead of the 

+#' default dot-segment plot); defaults to FALSE.

 #'

 #' @return A `ggplot` object

 #'

@@ -54,18 +56,23 @@

 #' res_enrich <- get_aggrscores(res_enrich, res_de, anno_df)

 #'

 #' gs_summary_overview(res_enrich)

-#'

+#' 

+#' # if desired, it can also be shown as a barplot

+#' gs_summary_overview(res_enrich, 30, return_barchart = TRUE)

 gs_summary_overview <- function(res_enrich,

                                 n_gs = 20,

                                 p_value_column = "gs_pvalue",

-                                color_by = "z_score"

+                                color_by = "z_score",

+                                return_barchart = FALSE

                                 # , size_by = "gs_de_count"

                                 ) {

-  if (!(color_by %in% colnames(res_enrich))) {

-    stop("Your res_enrich object does not contain the ",

-         color_by,

-         " column.\n",

-         "Compute this first or select another column to use for the color.")

+  if (!is.null(color_by)) {

+    if (!(color_by %in% colnames(res_enrich))) {

+      stop("Your res_enrich object does not contain the ",

+           color_by,

+           " column.\n",

+           "Compute this first or select another column to use for the color.")

+    }

   }

   re <- res_enrich

@@ -75,17 +82,44 @@ gs_summary_overview <- function(res_enrich,

   re_sorted <- re %>%

     arrange(.data$logp10) %>%

     mutate(gs_description = factor(.data$gs_description, .data$gs_description))

-  p <- ggplot(re_sorted, (aes_string(x = "gs_description", y = "logp10"))) +

-    geom_segment(aes_string(x = "gs_description", xend = "gs_description", y = 0, yend = "logp10"), color = "grey") +

-    geom_point(aes(col = .data[[color_by]]), size = 4) +

-    # geom_point(aes(col = .data[[color_by]], size = .data[[size_by]])) +

-    scale_color_gradient2(low = "#313695", mid = "#FFFFE5", high = "#A50026") +

-    coord_flip() +

-    labs(x = "Gene set description",

-         y = "-log10 p-value",

-         col = color_by) +

-    theme_minimal()

-

+  

+  if (return_barchart) {

+    p <- ggplot(re_sorted, (aes_string(x = "gs_description", y = "logp10"))) 

+    

+    if (is.null(color_by)) {

+      p <- p + geom_col()

+    } else {

+      p <- p + geom_col(aes(fill = .data[[color_by]])) + 

+        scale_fill_gradient2(low = "#313695", mid = "#FFFFE5", high = "#A50026")

+    }

+    

+    p <- p +

+      coord_flip() + 

+      labs(x = "Gene set description",

+           y = "-log10 p-value",

+           col = color_by) +

+      theme_minimal()

+  } else {

+    p <- ggplot(re_sorted, (aes_string(x = "gs_description", y = "logp10"))) +

+      geom_segment(aes_string(x = "gs_description", 

+                              xend = "gs_description", 

+                              y = 0, 

+                              yend = "logp10"), color = "grey")

+    

+    if (is.null(color_by)) {

+      p <- p + geom_point(size = 4)

+    } else {

+      p <- p + geom_point(aes(col = .data[[color_by]]), size = 4) +

+        scale_color_gradient2(low = "#313695", mid = "#FFFFE5", high = "#A50026")

+    }

+    

+    p <- p +

+      coord_flip() +

+      labs(x = "Gene set description",

+           y = "-log10 p-value",

+           col = color_by) +

+      theme_minimal()

+  }

   return(p)

 }

@@ -208,8 +242,8 @@ gs_summary_overview_pair <- function(res_enrich,

     geom_point(aes(fill = .data[[color_by]]), size = 4, pch = 21) +

     geom_point(aes_string(y = "logp10_2", col = paste0(color_by, "_2")),

                size = 4, alpha = alpha_set2) +

-    scale_color_gradient2(low = "#313695", mid = "#FFFFE5", high = "#A50026") +

-    scale_fill_gradient2(low = "#313695", mid = "#FFFFE5", high = "#A50026", guide = FALSE) +

+    scale_color_gradient2(low = "#313695", mid = "#FFFFE5", high = "#A50026", name = paste0(color_by, " set 2")) +

+    scale_fill_gradient2(low = "#313695", mid = "#FFFFE5", high = "#A50026", name = paste0(color_by, " set 1")) +

     coord_flip() +

     labs(x = "Gene set description",

          y = "-log10 p-value",

new file mode 100644

@@ -0,0 +1,206 @@

+#' Plot a volcano plot of a geneset

+#'

+#' Plot a volcano plot for the geneset of the provided data, with the remaining

+#' genes as shaded dots in the background of the plot.

+#'

+#' @param res_de A `DESeqResults` object.

+#' @param res_enrich A `data.frame` object, storing the result of the functional

+#' enrichment analysis. See more in the main function, [GeneTonic()], to check the

+#' formatting requirements (a minimal set of columns should be present).

+#' @param annotation_obj A `data.frame` object with the feature annotation

+#' information, with at least two columns, `gene_id` and `gene_name`.

+#' @param gtl A `GeneTonic`-list object, containing in its slots the arguments

+#' specified above: `dds`, `res_de`, `res_enrich`, and `annotation_obj` - the names

+#' of the list _must_ be specified following the content they are expecting.

+#' @param geneset_id Character specifying the gene set identifier to be plotted.

+#' @param genelist A vector of character strings, specifying the identifiers

+#' contained in the `rownames` of the `res_de` input object.

+#' @param FDR Numeric value, specifying the significance level for thresholding

+#' adjusted p-values. Defaults to 0.05.

+#' @param color Character string to specify color of filtered points in the plot.

+#' Defaults to #1a81c2 (shade of blue).

+#' @param volcano_labels Integer, maximum number of labels for the gene sets to be

+#' plotted as labels on the volcano scatter plot. Defaults to 25.

+#' @param plot_title Character string, to specify the title of the plot,

+#' displayed over the volcano plot. If left to `NULL` as by default, it tries to use

+#' the information on the geneset identifier provided.

+#'

+#' @return A plot returned by the [ggplot()] function

+#' @export

+#'

+#' @examples

+#' library("macrophage")

+#' library("DESeq2")

+#' library("org.Hs.eg.db")

+#' library("AnnotationDbi")

+#'

+#' # dds object

+#' data("gse", package = "macrophage")

+#' dds_macrophage <- DESeqDataSet(gse, design = ~line + condition)

+#' rownames(dds_macrophage) <- substr(rownames(dds_macrophage), 1, 15)

+#' dds_macrophage <- estimateSizeFactors(dds_macrophage)

+#'

+#'

+#' # annotation object

+#' anno_df <- data.frame(

+#'   gene_id = rownames(dds_macrophage),

+#'   gene_name = mapIds(org.Hs.eg.db,

+#'                      keys = rownames(dds_macrophage),

+#'                      column = "SYMBOL",

+#'                      keytype = "ENSEMBL"),

+#'   stringsAsFactors = FALSE,

+#'   row.names = rownames(dds_macrophage)

+#' )

+#'

+#' # res object

+#' data(res_de_macrophage, package = "GeneTonic")

+#' res_de <- res_macrophage_IFNg_vs_naive

+#'

+#' # res_enrich object

+#' data(res_enrich_macrophage, package = "GeneTonic")

+#' res_enrich <- shake_topGOtableResult(topgoDE_macrophage_IFNg_vs_naive)

+#' res_enrich <- get_aggrscores(res_enrich, res_de, anno_df)

+#'

+#' signature_volcano(res_de,

+#'                   res_enrich,

+#'                   anno_df,

+#'                   geneset_id = res_enrich$gs_id[1]

+#'                   )

+#'

+#' # alternatively

+#'

+#' chemokine_list <- c("ENSG00000108702",

+#'                     "ENSG00000172156",

+#'                     "ENSG00000181374",

+#'                     "ENSG00000276409"

+#'                     )

+#'

+#' signature_volcano(res_de,

+#'                   res_enrich,

+#'                   anno_df,

+#'                   genelist = chemokine_list

+#'                   )

+#'

+signature_volcano <- function(res_de,

+                              res_enrich,

+                              annotation_obj = NULL,

+                              gtl = NULL,

+                              geneset_id = NULL,

+                              genelist = NULL,

+                              FDR = 0.05,

+                              color = "#1a81c2",

+                              volcano_labels = 25,

+                              plot_title = NULL

+) {

+  

+  if (!is.null(gtl)) {

+    checkup_gtl(gtl)

+    dds <- gtl$dds

+    res_de <- gtl$res_de

+    res_enrich <- gtl$res_enrich

+    annotation_obj <- gtl$annotation_obj

+  }

+  

+  # Retrieve information about genes in geneset gs_id

+  if (!is.null(geneset_id)) {

+    if (geneset_id %in% res_enrich[["gs_id"]]) {

+      thisset_name <- res_enrich[geneset_id, "gs_description"]

+      thisset_members <-

+        unlist(strsplit(res_enrich[geneset_id, "gs_genes"], ","))

+      thisset_members_ids <-

+        annotation_obj$gene_id[match(thisset_members, annotation_obj$gene_name)]

+    }

+  } else {

+    # overwritable via a list

+    if (!all(genelist %in% rownames(res_de))) {

+      not_there <- genelist[!(genelist %in% rownames(res_de))]

+      warning(

+        "Some of the provided gene ids were not found in the SummarizedExperiment",

+        "\nNot found: ",

+        not_there

+      )

+    }

+    thisset_members_ids <- intersect(rownames(res_de), genelist)

+    thisset_name <- "Custom list"

+  }

+  

+  

+  # Prepare the data

+  complete_genes_ids <- rownames(res_de)

+  complete_genes <-

+    annotation_obj$gene_name[match(complete_genes_ids, annotation_obj$gene_id)]

+  

+  padj_complete <- res_de[complete_genes_ids, "padj"]

+  filter_info_complete <-sapply(padj_complete, function(x) x <= FDR)

+  padj_complete <- sapply(padj_complete, function(x) -log10(x))

+  

+  log2FoldChange_complete <- res_de[complete_genes_ids, "log2FoldChange"]

+  

+  gene_set_belong <- complete_genes_ids %in% thisset_members_ids

+  filter_info_complete <- filter_info_complete & gene_set_belong

+  

+  

+  thisset_complete_data <- data.frame(

+    complete_genes_ids,

+    padj_complete,

+    log2FoldChange_complete,

+    filter_info_complete,

+    gene_set_belong

+  )

+  

+  colnames(thisset_complete_data) <- c("genes",

+                                       "logTransformedpvalue",

+                                       "log2FoldChange",

+                                       "significant",

+                                       "belonging")

+  

+  

+  # Prepare plotting

+  volcano_df_complete <- thisset_complete_data

+  volcano_df_complete$genes_name <- complete_genes

+  max_x <- max(abs(range(thisset_complete_data["log2FoldChange"])))

+  limit_x <- max_x * c(-1, 1)

+  

+  

+  # Prepare plot title

+  if (is.null(plot_title)) {

+    title <- paste0("Signature Volcano Plot - ", thisset_name, " - ", geneset_id)

+  } else {

+    title <- plot_title

+  }

+  

+  

+  # Plot data

+  p <- ggplot(volcano_df_complete,

+              aes_string(x = "log2FoldChange", y = "logTransformedpvalue")) +

+    geom_point(aes_string(color = "significant",

+                          alpha = "belonging")) +

+    labs(x = "log2Fold Change",

+         y = "-log10 p-value",

+         color = "p-value <= FDR") +

+    scale_x_continuous(limits = limit_x) +

+    scale_color_manual(

+      labels = c("significant", "not significant"),

+      breaks = c("TRUE", "FALSE"),

+      values = c(color, "grey25")) +

+    scale_alpha_manual(breaks = c("TRUE", "FALSE"),

+                       values = c(1, 1 / 10)) +

+    theme_bw() +

+    theme(legend.title = element_text(size = 11, face = "bold"),

+          legend.text = element_text(size = 10))

+  

+  

+  # adding labels to the significant points of the geneset

+  p <- p + geom_text_repel(

+    data = subset(volcano_df_complete, filter_info_complete),

+    aes_string(label = "genes_name"),

+    size = 4,

+    max.overlaps = volcano_labels

+  )

+  

+  

+  # handling the title

+  p <- p + ggtitle(title)

+  p <- p + guides(alpha = FALSE)

+  return(p)

+}

@@ -8,11 +8,13 @@ element;intro

 #controlbar-toggle;Close back the controlbar.

 #ggsnetwork;You can interact with the network visualization, either by clicking on a desired node (you can zoom in with the mouse wheel of with the trackpad)...

 #nodeSelectggsnetwork;... or by selecting one here - first the gene sets are displayed, then the genes. Now select a gene set of interest.

-#ui_ggs_genesetbox;Whenever you select something, some additional content gets displayed in the boxes on the right side. If you selected a gene set, you should see some summary information on the geneset, referred to the inputs you provided, below a signature heatmap including all the genes annotated to the gene set.

+#ui_ggs_genesetbox;Whenever you select something, some additional content gets displayed in the boxes on the right side. If you selected a gene set, you should see some summary information on the geneset, referred to the inputs you provided, below a signature heatmap and a signature volcano plot including all the genes annotated to the gene set.

 #ggsnetwork;You can go back to the main network view, and select a gene now.

 #ui_ggs_genebox;See how some links to the selected gene get automatically generated as action buttons - to the NCBI and the GeneCards databases.

 #controlbar-toggle;Toggle again the control bar...

-#exp_condition + .selectize-control;... and select for example 'condition' from the dropdown select input.

+#exp_condition + .selectize-control;... and select for example 'condition' from the dropdown select input...

+#col; ... or you use the <b> Select color for volcano plot </b> option. With this you can change the color and transparency and the genes of the chosen geneset will be displayed accordingly.

+#labels; Also you can decide to check the <b> Display all labels </b> box. This will add the names of all genes in the geneset to the signature volcano plot - otherwise only a small number is displayed to keep a clearly represented plot. 

 #controlbar-toggle;Close back the control bar.

 #ui_ggs_genebox;You can see how the gene infobox also added a plot on the selected gene, split by the factor you specified in the select widget.

 #ggsnetwork;You can be interested in a number of genes and gene sets. <code>GeneTonic</code> supports functions for bookmarking all these entities and combine them together in an HTML report. Select any node now...

@@ -71,6 +71,7 @@ anno_df <- data.frame(

   row.names = rownames(dds_macrophage)

 )

+

 # res object

 data(res_de_macrophage, package = "GeneTonic")

 res_de <- res_macrophage_IFNg_vs_naive

@@ -8,7 +8,8 @@ gs_summary_overview(

   res_enrich,

   n_gs = 20,

   p_value_column = "gs_pvalue",

-  color_by = "z_score"

+  color_by = "z_score",

+  return_barchart = FALSE

 )

 }

 \arguments{

@@ -26,6 +27,9 @@ p-value - have been specified).}

 \item{color_by}{Character, specifying the column of \code{res_enrich} to be used

 for coloring the plotted gene sets. Defaults sensibly to \code{z_score}.}

+

+\item{return_barchart}{Logical, whether to return a barchart (instead of the

+default dot-segment plot); defaults to FALSE.}

 }

 \value{

 A \code{ggplot} object

@@ -69,6 +73,8 @@ res_enrich <- get_aggrscores(res_enrich, res_de, anno_df)

 gs_summary_overview(res_enrich)

+# if desired, it can also be shown as a barplot

+gs_summary_overview(res_enrich, 30, return_barchart = TRUE)

 }

 \seealso{

 \code{\link[=gs_summary_overview_pair]{gs_summary_overview_pair()}}, \code{\link[=gs_horizon]{gs_horizon()}}

@@ -29,7 +29,7 @@ Convert the output of Enrichr for straightforward use in \code{\link[=GeneTonic]

 #          "Reactome_2016", 

 #          "WikiPathways_2019_Human")

 # degenes <- (deseqresult2df(res_macrophage_IFNg_vs_naive, FDR = 0.01)$SYMBOL)

-# if called directly withín R...

+# if called directly within R...

 # enrichr_output_macrophage <- enrichr(degenes, dbs)

 # or alternatively, if downloaded from the website in tabular format

 enrichr_output_file <- system.file("extdata", 

new file mode 100644

@@ -0,0 +1,112 @@

+% Generated by roxygen2: do not edit by hand

+% Please edit documentation in R/signature_volcano.R

+\name{signature_volcano}

+\alias{signature_volcano}

+\title{Plot a volcano plot of a geneset}

+\usage{

+signature_volcano(

+  res_de,

+  res_enrich,

+  annotation_obj = NULL,

+  gtl = NULL,

+  geneset_id = NULL,

+  genelist = NULL,

+  FDR = 0.05,

+  color = "#1a81c2",

+  volcano_labels = 25,

+  plot_title = NULL

+)

+}

+\arguments{

+\item{res_de}{A \code{DESeqResults} object.}

+

+\item{res_enrich}{A \code{data.frame} object, storing the result of the functional

+enrichment analysis. See more in the main function, \code{\link[=GeneTonic]{GeneTonic()}}, to check the

+formatting requirements (a minimal set of columns should be present).}

+

+\item{annotation_obj}{A \code{data.frame} object with the feature annotation

+information, with at least two columns, \code{gene_id} and \code{gene_name}.}

+

+\item{gtl}{A \code{GeneTonic}-list object, containing in its slots the arguments

+specified above: \code{dds}, \code{res_de}, \code{res_enrich}, and \code{annotation_obj} - the names

+of the list \emph{must} be specified following the content they are expecting.}

+

+\item{geneset_id}{Character specifying the gene set identifier to be plotted.}

+

+\item{genelist}{A vector of character strings, specifying the identifiers

+contained in the \code{rownames} of the \code{res_de} input object.}

+

+\item{FDR}{Numeric value, specifying the significance level for thresholding

+adjusted p-values. Defaults to 0.05.}

+

+\item{color}{Character string to specify color of filtered points in the plot.

+Defaults to #1a81c2 (shade of blue).}

+

+\item{volcano_labels}{Integer, maximum number of labels for the gene sets to be

+plotted as labels on the volcano scatter plot. Defaults to 25.}

+

+\item{plot_title}{Character string, to specify the title of the plot,

+displayed over the volcano plot. If left to \code{NULL} as by default, it tries to use

+the information on the geneset identifier provided.}

+}

+\value{

+A plot returned by the \code{\link[=ggplot]{ggplot()}} function

+}

+\description{

+Plot a volcano plot for the geneset of the provided data, with the remaining

+genes as shaded dots in the background of the plot.

+}

+\examples{

+library("macrophage")

+library("DESeq2")

+library("org.Hs.eg.db")

+library("AnnotationDbi")

+

+# dds object

+data("gse", package = "macrophage")

+dds_macrophage <- DESeqDataSet(gse, design = ~line + condition)

+rownames(dds_macrophage) <- substr(rownames(dds_macrophage), 1, 15)

+dds_macrophage <- estimateSizeFactors(dds_macrophage)

+

+

+# annotation object

+anno_df <- data.frame(

+  gene_id = rownames(dds_macrophage),

+  gene_name = mapIds(org.Hs.eg.db,

+                     keys = rownames(dds_macrophage),

+                     column = "SYMBOL",

+                     keytype = "ENSEMBL"),

+  stringsAsFactors = FALSE,

+  row.names = rownames(dds_macrophage)

+)

+

+# res object

+data(res_de_macrophage, package = "GeneTonic")

+res_de <- res_macrophage_IFNg_vs_naive

+

+# res_enrich object

+data(res_enrich_macrophage, package = "GeneTonic")

+res_enrich <- shake_topGOtableResult(topgoDE_macrophage_IFNg_vs_naive)

+res_enrich <- get_aggrscores(res_enrich, res_de, anno_df)

+

+signature_volcano(res_de,

+                  res_enrich,

+                  anno_df,

+                  geneset_id = res_enrich$gs_id[1]

+                  )

+

+# alternatively

+

+chemokine_list <- c("ENSG00000108702",

+                    "ENSG00000172156",

+                    "ENSG00000181374",

+                    "ENSG00000276409"

+                    )

+

+signature_volcano(res_de,

+                  res_enrich,

+                  anno_df,

+                  genelist = chemokine_list

+                  )

+

+}

@@ -34,8 +34,15 @@ test_that("summary plots are generated", {

   res_enrich2$aggr_score <- res_enrich2$aggr_score[shuffled_ones]

   p1 <- gs_summary_overview(res_enrich_withscores)

+  p1_bar <- gs_summary_overview(res_enrich_withscores, return_barchart = TRUE)

+  p1_nocol <- gs_summary_overview(res_enrich_withscores, color_by = NULL)

+  p1_bar_nocol <- gs_summary_overview(res_enrich_withscores, color_by = NULL, 

+                                      return_barchart = TRUE)

   expect_is(p1, "gg")

-

+  expect_is(p1_bar, "gg")

+  expect_is(p1_nocol, "gg")

+  expect_is(p1_bar_nocol, "gg")

+  

   p2 <- gs_summary_overview_pair(res_enrich_withscores, res_enrich2)

   expect_is(p2, "gg")

new file mode 100644

@@ -0,0 +1,62 @@

+context("Testing gene set signature volcano and related functionality")

+

+test_that("Geneset signature volcano is created", {

+  cur_gsid <- res_enrich_IFNg_vs_naive$gs_id[1]

+  p <- signature_volcano(res_de = res_macrophage_IFNg_vs_naive,

+                         res_enrich = res_enrich_IFNg_vs_naive,

+                         annotation_obj = anno_df,

+                         geneset_id = cur_gsid,

+                         FDR = 0.05,

+  )

+  expect_is(p, "gg")

+  p2 <- signature_volcano(res_de = res_macrophage_IFNg_vs_naive,

+                          res_enrich = res_enrich_IFNg_vs_naive,

+                          annotation_obj = anno_df,

+                          geneset_id = cur_gsid,

+                          color = "red"

+  )

+  expect_is(p2, "gg")

+  p3 <- signature_volcano(res_de = res_macrophage_IFNg_vs_naive,

+                   res_enrich = res_enrich_IFNg_vs_naive,

+                   annotation_obj = anno_df,

+                   geneset_id = cur_gsid,

+                   FDR = 0.05,

+                   plot_title = "Random Title"

+  )

+  expect_is(p3, "gg")

+  

+  gtl_macrophage <- list(dds = dds_macrophage,

+                         res_de = res_macrophage_IFNg_vs_naive,

+                         res_enrich = res_enrich_IFNg_vs_naive,

+                         annotation_obj = anno_df)

+  p4 <- signature_volcano(gtl = gtl_macrophage,

+                          geneset_id = cur_gsid,

+  )

+  expect_is(p4, "gg")

+  

+  p5 <- signature_volcano(res_de = res_macrophage_IFNg_vs_naive,

+                          res_enrich = res_enrich_IFNg_vs_naive,

+                          annotation_obj = anno_df,

+                          geneset_id = cur_gsid,

+                          FDR = 0.05,

+                          volcano_labels = 35

+  )

+  expect_is(p5, "gg")

+

+  # enforcing id not present in the object

+  mycustomlist <- c(

+    rownames(vst_macrophage)[1:10],

+    "ENSmadeUPid"

+  )

+

+  expect_warning(

+    p6 <- signature_volcano(

+      res_de = res_macrophage_IFNg_vs_naive,

+      res_enrich = res_enrich_IFNg_vs_naive,

+      annotation_obj = anno_df,

+      genelist = mycustomlist,

+    )

+  )

+

+  file.remove("Rplots.pdf")

+})

@@ -777,6 +777,18 @@ go_2_html("GO:0060337",

           res_enrich = res_enrich_macrophage)

 ```

+Plot a signature volcano plot for a gene set, with the genes of the geneset highlighted in color and the remaining genes shown shaded in the background: 

+

+```{r signaturevolcano}

+signature_volcano(res_de = res_macrophage_IFNg_vs_naive,

+                  res_enrich = res_enrich_macrophage,

+                  annotation_obj = anno_df,

+                  geneset_id = "GO:0060337",

+                  FDR = 0.05,

+                  color = "#1a81c2"

+)

+```

+

 Some functions are just to ensure that the input objects are conform with the format expected by `GeneTonic`:

 ```{r shakers, eval=FALSE}