@@ -37,6 +37,7 @@ Imports:

     shinyWidgets,

     SingleCellExperiment,

     SummarizedExperiment,

+    tidygraph,

     TreeSummarizedExperiment,

     utils

 Suggests:

@@ -62,4 +62,5 @@ importFrom(purrr,reduce)

 importFrom(shiny,plotOutput)

 importFrom(shiny,renderPlot)

 importFrom(shinyWidgets,addSpinner)

+importFrom(tidygraph,activate)

 importFrom(utils,stack)

@@ -17,3 +17,4 @@ Changes in version 1.1.X

 Changes in version 1.2.X

 * Created TreePlot family

 * Added typical tree operations

+* Created GraphPlot family

@@ -23,7 +23,9 @@ graph_slots <- c(name="character", assay.type="character", layout="character",

     edge.type="character", show.label="logical", add.legend="logical",

     edge.colour.by="character", edge.size.by="character",

     node.colour.by="character", node.shape.by="character",

-    node.size.by="character")

+    node.size.by="character", visual_parameters="character",

+    size_parameters="character", shape_parameters="character",

+    colour_parameters="character")

 #' @rdname GraphPlot

 #' @export

@@ -1,10 +1,10 @@

 #' Column graph plot

 #'

-#' Hierarchical tree for the rows of a

-#' \code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-constructor]{TreeSummarizedExperiment}}

-#' object. The tree can be produced with \code{\link[mia:taxonomy-methods]{addTaxonomyTree}}

-#' and gets stored in the \code{\link[TreeSummarizedExperiment:rowLinks]{rowTree}}

-#' slot of the experiment object. The panel implements \code{\link[miaViz:plotTree]{plotRowTree}}

+#' Network organisation for the samples of a

+#' \code{\link[SummarizedExperiment:SummarizedExperiment-class]{SummarizedExperiment}}

+#' object. The igraph should be stored in the \code{metadata} slot by a name

+#' containing \code{"graph"}. This panel uses

+#' \code{\link[miaViz:plotColGraph]{plotColGraph}}

 #' to generate the plot.

 #'

 #' @section Slot overview:

@@ -17,10 +17,17 @@

 #' \code{...} as a named argument.

 #'

 #' @examples

-#' # Import TreeSE

 #' library(mia)

-#' data("Tengeler2020", package = "mia")

-#' tse <- Tengeler2020

+#' library(miaViz)

+#' data("GlobalPatterns", library = "mia")

+#' data("col_graph", library = "miaViz")

+#' 

+#' tse <- GlobalPatterns

+#' tse <- agglomerateByRank(tse,

+#'                          rank = "Genus",

+#'                          na.rm = TRUE)

+#'                          

+#' metadata(tse)$graph <- col_graph

 #' 

 #' # Store panel into object

 #' panel <- ColumnGraphPlot()

@@ -32,6 +39,10 @@

 #'   iSEE(tse, initial = c(panel))

 #' }

 #' 

+#' @seealso

+#' \linkS4class{GraphPlot}

+#' \linkS4class{RowGraphPlot}

+#' 

 #' @author Giulio Benedetti

 #' 

 #' @docType methods

@@ -71,10 +82,27 @@ setMethod(".generateOutput", "ColumnGraphPlot",

     args[["layout"]] <- deparse(slot(x, "layout"))

     args[["edge.type"]] <- deparse(slot(x, "edge.type"))

     args[["add.legend"]] <- deparse(slot(x, "add.legend"))

-

+    

+    if( "Colour" %in% slot(x, "visual_parameters") ){

+        args <- .assign_viz_param(args, x, "Edge", "colour")

+        args <- .assign_viz_param(args, x, "Node", "colour",

+            arg.name = "colour.by")

+    }

+    

+    if( "Shape" %in% slot(x, "visual_parameters") ){

+        args <- .assign_viz_param(args, x, "Node", "shape",

+            arg.name = "shape.by")

+    }

+    

+    if( "Size" %in% slot(x, "visual_parameters") ){

+        args <- .assign_viz_param(args, x, "Edge", "size",

+            arg.name = "edge.width.by")

+        args <- .assign_viz_param(args, x, "Node", "size", arg.name = "size.by")

+    }

+    

     args <- sprintf("%s=%s", names(args), args)

     args <- paste(args, collapse = ", ")

-    fun_call <- sprintf("p <- plotColGraph(se, %s)", args)

+    fun_call <- sprintf("p <- miaViz::plotColGraph(se, %s)", args)

     fun_cmd <- paste(strwrap(fun_call, width = 80, exdent = 4), collapse = "\n")

     plot_out <- .textEval(fun_cmd, panel_env)

@@ -1,10 +1,10 @@

 #' Row graph plot

 #'

-#' Hierarchical tree for the rows of a

-#' \code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-constructor]{TreeSummarizedExperiment}}

-#' object. The tree can be produced with \code{\link[mia:taxonomy-methods]{addTaxonomyTree}}

-#' and gets stored in the \code{\link[TreeSummarizedExperiment:rowLinks]{rowTree}}

-#' slot of the experiment object. The panel implements \code{\link[miaViz:plotTree]{plotRowTree}}

+#' Network organisation for the features of a

+#' \code{\link[SummarizedExperiment:SummarizedExperiment-class]{SummarizedExperiment}}

+#' object. The igraph should be stored in the \code{metadata} slot by a name

+#' containing \code{"graph"}. This panel uses

+#' \code{\link[miaViz:plotColGraph]{plotRowGraph}}

 #' to generate the plot.

 #'

 #' @section Slot overview:

@@ -17,10 +17,17 @@

 #' as a named argument.

 #'

 #' @examples

-#' # Import TreeSE

 #' library(mia)

-#' data("Tengeler2020", package = "mia")

-#' tse <- Tengeler2020

+#' library(miaViz)

+#' data("GlobalPatterns", library = "mia")

+#' data("row_graph", library = "miaViz")

+#' 

+#' tse <- GlobalPatterns

+#' tse <- agglomerateByRank(tse,

+#'                          rank = "Genus",

+#'                          na.rm = TRUE)

+#'                          

+#' metadata(tse)$graph <- row_graph

 #' 

 #' # Store panel into object

 #' panel <- RowGraphPlot()

@@ -32,6 +39,10 @@

 #'   iSEE(tse, initial = c(panel))

 #' }

 #' 

+#' @seealso

+#' \linkS4class{GraphPlot}

+#' \linkS4class{ColumnGraphPlot}

+#' 

 #' @author Giulio Benedetti

 #' 

 #' @docType methods

@@ -71,11 +82,28 @@ setMethod(".generateOutput", "RowGraphPlot",

     args[["layout"]] <- deparse(slot(x, "layout"))

     args[["edge.type"]] <- deparse(slot(x, "edge.type"))

     args[["add.legend"]] <- deparse(slot(x, "add.legend"))

+    

+    if( "Colour" %in% slot(x, "visual_parameters") ){

+        args <- .assign_viz_param(args, x, "Edge", "colour")

+        args <- .assign_viz_param(args, x, "Node", "colour",

+            arg.name = "colour.by")

+    }

+    

+    if( "Shape" %in% slot(x, "visual_parameters") ){

+        args <- .assign_viz_param(args, x, "Node", "shape",

+            arg.name = "shape.by")

+    }

+    

+    if( "Size" %in% slot(x, "visual_parameters") ){

+        args <- .assign_viz_param(args, x, "Edge", "size",

+            arg.name = "edge.width.by")

+        args <- .assign_viz_param(args, x, "Node", "size", arg.name = "size.by")

+    }

     args <- sprintf("%s=%s", names(args), args)

     args <- paste(args, collapse = ", ")

-    fun_call <- sprintf("p <- plotRowGraph(se, %s)", args)

-

+    fun_call <- sprintf("p <- miaViz::plotRowGraph(se, %s)", args)

+    

     fun_cmd <- paste(strwrap(fun_call, width = 80, exdent = 4), collapse = "\n")

     plot_out <- .textEval(fun_cmd, panel_env)

     all_cmds[["fun"]] <- fun_cmd

@@ -1,11 +1,11 @@

 #' Graph plot

 #'

-#' The Graph plot is a virtual class that creates the network structure of

+#' The Graph plot is a virtual class that showcases the network organisation of

 #' either the features or samples of a

-#' \code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-constructor]{TreeSummarizedExperiment}}

+#' \code{\link[SummarizedExperiment:SummarizedExperiment-class]{SummarizedExperiment}}

 #' object. The \linkS4class{RowGraphPlot} and \linkS4class{ColumnGraphPlot}

 #' classes belong to this family and are specialised to visualise the feature

-#' or sample graphs stored in metadata, respectively.

+#' or sample igraphs stored in metadata, respectively.

 #'

 #' @section Slot overview:

 #' The following slots control the thresholds used in the visualisation:

@@ -36,7 +36,11 @@

 #'

 #' In addition, this class inherits all slots from its parent class

 #' \linkS4class{Panel}.

-#'

+#' 

+#' @seealso

+#' \linkS4class{RowGraphPlot}

+#' \linkS4class{ColumnGraphPlot}

+#' 

 #' @author Giulio Benedetti

 #' 

 #' @docType methods

@@ -48,8 +52,8 @@ setValidity2("GraphPlot", function(x) {

     msg <- character(0)

     msg <- .singleStringError(msg, x, fields=c("name", "assay.type", "layout",

-        "edge.type", "edge.colour.by", "edge.size.by", "colour.by", "shape.by",

-        "size.by"))

+        "edge.type", "edge.colour.by", "edge.size.by", "node.colour.by",

+        "node.shape.by", "node.size.by"))

     msg <- .validLogicalError(msg, x, fields=c("add.legend", "show.label"))

     if (length(msg)) {

@@ -70,9 +74,13 @@ setMethod("initialize", "GraphPlot", function(.Object, ...) {

     args <- .emptyDefault(args, "add.legend", TRUE)

     args <- .emptyDefault(args, "edge.colour.by", NA_character_)

     args <- .emptyDefault(args, "edge.size.by", NA_character_)

-    args <- .emptyDefault(args, "colour.by", NA_character_)

-    args <- .emptyDefault(args, "size.by", NA_character_)

-    args <- .emptyDefault(args, "shape.by", NA_character_)

+    args <- .emptyDefault(args, "node.colour.by", NA_character_)

+    args <- .emptyDefault(args, "node.size.by", NA_character_)

+    args <- .emptyDefault(args, "node.shape.by", NA_character_)

+    args <- .emptyDefault(args, "visual_parameters", NA_character_)

+    args <- .emptyDefault(args, "colour_parameters", NA_character_)

+    args <- .emptyDefault(args, "shape_parameters", NA_character_)

+    args <- .emptyDefault(args, "size_parameters", NA_character_)

     do.call(callNextMethod, c(list(.Object), args))

 })

@@ -102,12 +110,13 @@ setMethod(".createObservers", "GraphPlot",

     panel_name <- .getEncodedName(x)

     .createProtectedParameterObservers(panel_name, c("layout", "assay.type",

-        "name", "edge.type", "show.label", "add.legend", "RowSelectionSource"),

-        input=input, pObjects=pObjects, rObjects=rObjects)

+        "name", "edge.type", "show.label", "add.legend", "RowSelectionSource",

+        "visual_parameters", "colour_parameters", "size_parameters",

+        "shape_parameters"), input=input, pObjects=pObjects, rObjects=rObjects)

     .createUnprotectedParameterObservers(panel_name, c("edge.colour.by",

-        "edge.size.by", "size.by", "shape.by", "size.by"), input=input,

-        pObjects=pObjects, rObjects=rObjects)

+        "edge.size.by", "node.size.by", "node.colour.by", "node.shape.by",

+        "node.size.by"), input=input, pObjects=pObjects, rObjects=rObjects)

     invisible(NULL)

 })

@@ -172,9 +181,14 @@ setMethod(".definePanelTour", "GraphPlot", function(x) {

     callNextMethod())

 })

+#' @importFrom methods slot

+#' @importFrom S4Vectors metadata

+#' @importFrom tidygraph activate

 #' @importFrom SummarizedExperiment rowData colData

 .create_visual_box_for_graph <- function(x, se) {

     panel_name <- .getEncodedName(x)

+    

+    edge_data <- as.data.frame(activate(metadata(se)[[slot(x, "name")]], "edges"))

     gr_data <- switch(substr(panel_name, 1, 3),

         Row = rowData(se), Col = colData(se))

@@ -198,49 +212,109 @@ setMethod(".definePanelTour", "GraphPlot", function(x) {

             and one of them can be selected.")))})

     .addSpecificTour(class(x)[1], "edge.size.by", function(panel_name) {

         data.frame(rbind(c(element = paste0("#", panel_name,

-            "_edge\\.width\\.by + .selectize-control"), intro = "Here, we can

+            "_edge\\.size\\.by + .selectize-control"), intro = "Here, we can

             choose whether or not to colour the tips by a variable from the

             <code>metadata</code>. When active, the available options are listed

             and one of them can be selected.")))})

-    .addSpecificTour(class(x)[1], "colour.by", function(panel_name) {

+    .addSpecificTour(class(x)[1], "node.colour.by", function(panel_name) {

         data.frame(rbind(c(element = paste0("#", panel_name,

-            "_colour\\.by + .selectize-control"), intro = "Here, we can choose

-            whether or not to colour the nodes by a variable from the

+            "_node\\.colour\\.by + .selectize-control"), intro = "Here, we can

+            choose whether or not to colour the nodes by a variable from the

             <code>metadata</code>. When active, the available options are listed

             and one of them can be selected.")))})

-    .addSpecificTour(class(x)[1], "shape.by", function(panel_name) {

+    .addSpecificTour(class(x)[1], "node.shape.by", function(panel_name) {

         data.frame(rbind(c(element = paste0("#", panel_name,

-            "_shape\\.by + .selectize-control"), intro = "Here, we can order

-            the tree alphabetically.")))})

-    .addSpecificTour(class(x)[1], "size.by", function(panel_name) {

+            "_node\\.shape\\.by + .selectize-control"), intro = "Here, we can

+            order the tree alphabetically.")))})

+    .addSpecificTour(class(x)[1], "node.size.by", function(panel_name) {

         data.frame(rbind(c(element = paste0("#", panel_name,

-            "_size\\.by + .selectize-control"), intro = "Here, we can

+            "_node\\.size\\.by + .selectize-control"), intro = "Here, we can

             choose how to colour the  tips by.")))})

+    .addSpecificTour(class(x)[1], "visual_parameters", function(panel_name) {

+        data.frame(rbind(c(element = paste0("#", panel_name,

+            "_visual_parameters"), intro = "Here, we can 

+            choose to show the different visual parameters.")))})

+    .addSpecificTour(class(x)[1], "colour_parameters", function(panel_name) {

+        data.frame(rbind(c(element = paste0("#", panel_name,

+            "_colour_parameters"), intro = "Here, we can make 

+            the colour depend on the value of a

+            categorical column data field for each plot components

+            (line, tip, node).")))})

+    .addSpecificTour(class(x)[1], "shape_parameters", function(panel_name) {

+        data.frame(rbind(c(element = paste0("#", panel_name,

+            "_shape_parameters"), intro = "Here, we can make 

+            the shape depend on the value of a

+            categorical column data field for each plot components

+            (line, tip, node).")))})

+    .addSpecificTour(class(x)[1], "size_parameters", function(panel_name) {

+        data.frame(rbind(c(element = paste0("#", panel_name,

+            "_size_parameters"), intro = "Here, we can make 

+            the size depend on the value of a

+            categorical column data field for each plot components

+            (line, tip, node).")))})

     # Define what parameters the user can adjust

     collapseBox(paste0(panel_name, "_VisualBoxOpen"),

         title="Visual parameters", open=FALSE,

         # Graph layout

         .selectInput.iSEE(x, field="layout", label="Layout:",

-            choices=c("auto", "fan", "igraph", "dendrogram", "linear", "matrix",

+            choices=c("kk", "fan", "link", "arc", "parallel", "linear", "matrix",

                 "treemap", "circlepack", "partition", "hive", "cactustree",

                 "backbone", "centrality", "eigen", "fabric", "focus", "pmds",

                 "stress", "unrooted", "htree"), selected=slot(x, "layout")),

         .selectInput.iSEE(x, field="edge.type", label="Edge type:",

-            choices=c("link", "arc", "parallel", "fan", "loop", "diagonal",

-                "elbow", "bend", "hive", "span", "point", "tile", "density",

-                "force", "path", "minimal", "sf"), selected=slot(x, "edge.type")),

+            choices=c("fan", "link", "arc", "parallel"),

+            selected=slot(x, "edge.type")),

         .checkboxInput.iSEE(x, field="add.legend", label="View legend",

             value=slot(x, "add.legend")),

-        .selectInput.iSEE(x, field="edge.colour.by", label="Color edges by",

-            choices=names(gr_data), selected=slot(x, "edge.colour.by")),

-        .selectInput.iSEE(x, field="edge.size.by", label="Widen edges by",

-            choices=names(gr_data), selected=slot(x, "edge.size.by")),

-        .selectInput.iSEE(x, field="colour.by", label="Color nodes by",

-            choices=names(gr_data), selected=slot(x, "colour.by")),

-        .selectInput.iSEE(x, field="shape.by", label="Shape nodes by",

-            choices=names(gr_data), selected=slot(x, "shape.by")),

-        .selectInput.iSEE(x, field="size.by", label="Size edges by",

-            choices=names(gr_data), selected=slot(x, "size.by")))

-

-}

\ No newline at end of file

+        .checkboxGroupInput.iSEE(x, field="visual_parameters", label=NULL,

+            inline=TRUE, selected=slot(x, "visual_parameters"),

+            choices=c("Colour", "Size", "Shape")),

+        

+        .conditionalOnCheckGroup(

+            paste0(panel_name, "_visual_parameters"), "Colour",

+            list(

+                .checkboxGroupInput.iSEE(x, field="colour_parameters",

+                    inline=TRUE, selected=slot(x, "colour_parameters"),

+                    choices=c("Edge", "Node"), label="Colour by:"),

+                .conditionalOnCheckGroup(

+                    paste0(panel_name, "_colour_parameters"), "Edge",

+                        .selectInput.iSEE(x, field="edge.colour.by",

+                            label="Colour lines by", choices=names(edge_data),

+                            selected=slot(x, "edge.colour.by"))),

+                .conditionalOnCheckGroup(

+                    paste0(panel_name, "_colour_parameters"), "Node",

+                        .selectInput.iSEE(x, field="node.colour.by",

+                            label="Colour nodes by", choices=names(gr_data),

+                            selected=slot(x, "node.colour.by"))))),

+        

+        .conditionalOnCheckGroup(

+            paste0(panel_name, "_visual_parameters"), "Size",

+            list(

+                .checkboxGroupInput.iSEE(x, field="size_parameters",

+                    inline=TRUE, selected=slot(x, "size_parameters"),

+                    choices=c("Edge", "Node"), label="Size by:"),

+                .conditionalOnCheckGroup(

+                    paste0(panel_name, "_size_parameters"), "Edge",

+                        .selectInput.iSEE(x, field="edge.size.by",

+                            label="Size lines by", choices=names(edge_data),

+                            selected=slot(x, "edge.size.by"))),

+                .conditionalOnCheckGroup(

+                    paste0(panel_name, "_size_parameters"), "Node",

+                        .selectInput.iSEE(x, field="node.size.by",

+                            label="Size nodes by", choices=names(gr_data),

+                            selected=slot(x, "node.size.by"))))),

+        

+        .conditionalOnCheckGroup(

+            paste0(panel_name, "_visual_parameters"), "Shape",

+            list(

+                .checkboxGroupInput.iSEE(x, field="shape_parameters",

+                    inline=TRUE, selected=slot(x, "shape_parameters"),

+                    choices=c("Node"), label="Shape by:"),

+                .conditionalOnCheckGroup(

+                    paste0(panel_name, "_shape_parameters"), "Node",

+                        .selectInput.iSEE(x, field="node.shape.by",

+                            label="Shape nodes by", choices=names(gr_data),

+                            selected=slot(x, "node.shape.by"))))))

+

+}

@@ -216,24 +216,26 @@ setMethod(".definePanelTour", "TreePlot", function(x) {

         data.frame(rbind(c(element = paste0("#", panel_name,

             "_add\\.legend"), intro = "Here, we can choose

             whether or not to show a legend.")))})

-    .addSpecificTour(class(x)[1], "edge_colour", function(panel_name) {

+    .addSpecificTour(class(x)[1], "add.tip.lab", function(panel_name) {

         data.frame(rbind(c(element = paste0("#", panel_name,

-            "_edge_colour"), intro = "Here, we can choose

-            whether or not to colour the lines by a variable from the

-            <code>metadata</code>. When active, the available options are listed

-            and one of them can be selected.")))})

-    .addSpecificTour(class(x)[1], "tip_colour", function(panel_name) {

+            "_add\\.tip\\.lab"), intro = "Here, we can choose

+            whether or not to show the tip labels.")))})

+    .addSpecificTour(class(x)[1], "add.node.lab", function(panel_name) {

         data.frame(rbind(c(element = paste0("#", panel_name,

-            "_tip_colour"), intro = "Here, we can choose

-            whether or not to colour the tips by a variable from the

-            <code>metadata</code>. When active, the available options are listed

-            and one of them can be selected.")))})

-    .addSpecificTour(class(x)[1], "node_colour", function(panel_name) {

+            "_add\\.node\\.lab"), intro = "Here, we can choose

+            whether or not to show the node numbers.")))})

+    .addSpecificTour(class(x)[1], "rotate.angle", function(panel_name) {

         data.frame(rbind(c(element = paste0("#", panel_name,

-            "_node_colour"), intro = "Here, we can choose

-            whether or not to colour the nodes by a variable from the

-            <code>metadata</code>. When active, the available options are listed

-            and one of them can be selected.")))})

+            "_rotate\\.angle"), intro = "Here, we can specify the angle by which

+            to rotate the tree.")))})

+    .addSpecificTour(class(x)[1], "open.angle", function(panel_name) {

+        data.frame(rbind(c(element = paste0("#", panel_name,

+            "_open\\.angle"), intro = "Here, we can specify the angle by which

+            to open the tree.")))})

+    .addSpecificTour(class(x)[1], "branch.length", function(panel_name) {

+        data.frame(rbind(c(element = paste0("#", panel_name,

+            "_branch\\.length"), intro = "Here, we can choose whether branch

+            length should be equalised.")))})

     .addSpecificTour(class(x)[1], "order.tree", function(panel_name) {

         data.frame(rbind(c(element = paste0("#", panel_name,

             "_order\\.tree"), intro = "Here, we can order

@@ -371,13 +373,16 @@ setMethod(".definePanelTour", "TreePlot", function(x) {

 }

 #' @importFrom methods slot

-.assign_viz_param <- function(args, x, element, aesthetic) {

-  

-    param_name <- paste(tolower(element), aesthetic, "by", sep = ".")

-    

+.assign_viz_param <- function(args, x, element, aesthetic, arg.name = NULL) {

+    # Build panel slot name

+    slot_name <- paste(tolower(element), aesthetic, "by", sep = ".")

+    # Use slot name if arg name is not given

+    if( is.null(arg.name) ){

+        arg.name <- slot_name

+    }

+    # Add slot value to args

     if( element %in% slot(x, paste(aesthetic, "parameters", sep = "_")) ){

-        args[[param_name]] <- deparse(slot(x, param_name))

+        args[[arg.name]] <- deparse(slot(x, slot_name))

     }

-  

     return(args)

 }

\ No newline at end of file

@@ -11,11 +11,11 @@ ColumnGraphPlot class, where any slot and its value can be passed to

 \code{...} as a named argument.

 }

 \description{

-Hierarchical tree for the rows of a

-\code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-constructor]{TreeSummarizedExperiment}}

-object. The tree can be produced with \code{\link[mia:taxonomy-methods]{addTaxonomyTree}}

-and gets stored in the \code{\link[TreeSummarizedExperiment:rowLinks]{rowTree}}

-slot of the experiment object. The panel implements \code{\link[miaViz:plotTree]{plotRowTree}}

+Network organisation for the samples of a

+\code{\link[SummarizedExperiment:SummarizedExperiment-class]{SummarizedExperiment}}

+object. The igraph should be stored in the \code{metadata} slot by a name

+containing \code{"graph"}. This panel uses

+\code{\link[miaViz:plotColGraph]{plotColGraph}}

 to generate the plot.

 }

 \section{Slot overview}{

@@ -25,10 +25,17 @@ This class inherits all slots from its parent class \linkS4class{GraphPlot}.

 }

 \examples{

-# Import TreeSE

 library(mia)

-data("Tengeler2020", package = "mia")

-tse <- Tengeler2020

+library(miaViz)

+data("GlobalPatterns", library = "mia")

+data("col_graph", library = "miaViz")

+

+tse <- GlobalPatterns

+tse <- agglomerateByRank(tse,

+                         rank = "Genus",

+                         na.rm = TRUE)

+                         

+metadata(tse)$graph <- col_graph

 # Store panel into object

 panel <- ColumnGraphPlot()

@@ -40,6 +47,10 @@ if (interactive()) {

   iSEE(tse, initial = c(panel))

 }

+}

+\seealso{

+\linkS4class{GraphPlot}

+\linkS4class{RowGraphPlot}

 }

 \author{

 Giulio Benedetti

@@ -6,12 +6,12 @@

 \alias{GraphPlot}

 \title{Graph plot}

 \description{

-The Graph plot is a virtual class that creates the network structure of

+The Graph plot is a virtual class that showcases the network organisation of

 either the features or samples of a

-\code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-constructor]{TreeSummarizedExperiment}}

+\code{\link[SummarizedExperiment:SummarizedExperiment-class]{SummarizedExperiment}}

 object. The \linkS4class{RowGraphPlot} and \linkS4class{ColumnGraphPlot}

 classes belong to this family and are specialised to visualise the feature

-or sample graphs stored in metadata, respectively.

+or sample igraphs stored in metadata, respectively.

 }

 \section{Slot overview}{

@@ -45,6 +45,10 @@ In addition, this class inherits all slots from its parent class

 \linkS4class{Panel}.

 }

+\seealso{

+\linkS4class{RowGraphPlot}

+\linkS4class{ColumnGraphPlot}

+}

 \author{

 Giulio Benedetti

 }

@@ -11,11 +11,11 @@ RowGraphPlot class, where any slot and its value can be passed to \code{...}

 as a named argument.

 }

 \description{

-Hierarchical tree for the rows of a

-\code{\link[TreeSummarizedExperiment:TreeSummarizedExperiment-constructor]{TreeSummarizedExperiment}}

-object. The tree can be produced with \code{\link[mia:taxonomy-methods]{addTaxonomyTree}}

-and gets stored in the \code{\link[TreeSummarizedExperiment:rowLinks]{rowTree}}

-slot of the experiment object. The panel implements \code{\link[miaViz:plotTree]{plotRowTree}}

+Network organisation for the features of a

+\code{\link[SummarizedExperiment:SummarizedExperiment-class]{SummarizedExperiment}}

+object. The igraph should be stored in the \code{metadata} slot by a name

+containing \code{"graph"}. This panel uses

+\code{\link[miaViz:plotColGraph]{plotRowGraph}}

 to generate the plot.

 }

 \section{Slot overview}{

@@ -25,10 +25,17 @@ This class inherits all slots from its parent class \linkS4class{GraphPlot}.

 }

 \examples{

-# Import TreeSE

 library(mia)

-data("Tengeler2020", package = "mia")

-tse <- Tengeler2020

+library(miaViz)

+data("GlobalPatterns", library = "mia")

+data("row_graph", library = "miaViz")

+

+tse <- GlobalPatterns

+tse <- agglomerateByRank(tse,

+                         rank = "Genus",

+                         na.rm = TRUE)

+                         

+metadata(tse)$graph <- row_graph

 # Store panel into object

 panel <- RowGraphPlot()

@@ -40,6 +47,10 @@ if (interactive()) {

   iSEE(tse, initial = c(panel))

 }

+}

+\seealso{

+\linkS4class{GraphPlot}

+\linkS4class{ColumnGraphPlot}

 }

 \author{

 Giulio Benedetti

@@ -155,6 +155,10 @@ Supported operations:

 - selecting edge type

 - customising aesthetics

+```{r tree_plot, echo=FALSE, out.width="100%"}

+SCREENSHOT("screenshots/RowGraphPlot.png", delay=20)

+```

+

 # Other panels {#sec-other}

 | Panel name         | Panel class    | Purpose                                     |

new file mode 100644

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