show_heatmap {ViSEAGO} | R Documentation

## Display an interactive or static heatmap.

### Description

Display a heatmap in interactive or static mode.

### Usage

    show_heatmap(object, type, file = NULL, plotly_update = FALSE)

    ## S4 method for signature 'GO_clusters,character'
    show_heatmap(object, type, file = NULL, plotly_update = FALSE)

### Arguments

`object` | a `GO_clusters-class` object from `GOterms_heatmap` or `GOclusters_heatmap`.
`type` | could be "GOterms" to display GOterms clustering heatmap, or "GOclusters" to display GOclusters heatmap.
`file` | static image output file name (default to NULL).
`plotly_update` | update plotly html dependencies (default to FALSE).

### Details

This method displays an interactive heatmap (if `file`=NULL) from `GO_clusters-class` object for "GOterms" or "GOclusters" type.
A static png image could be printed by setting `file` argument.
Interactive heatmap cannot be displayed between two R versions. Then interactive view (build with previous R version) can be updated to new R version using `plotly_update` argument setting to TRUE.

### Value

display or print heatmap.

### See Also

Other enrich_GO_terms: `Upset()`, `enrich_GO_terms-class`, `overLapper()`, `show_table()`

Other GO_clusters: `GO_clusters-class`, `GOclusters_heatmap()`, `clusters_cor()`, `compare_clusters()`, `show_table()`

Other visualization: `GOclusters_heatmap()`, `GOcount()`, `GOterms_heatmap()`, `Upset()`, `available_organisms()`, `overLapper()`, `show_table()`

### Examples

    # load data example
    data(
        myGOs,
        package="ViSEAGO"
    )
    ## Not run:
    # compute GO terms Semantic Similarity distances
    myGOs<-ViSEAGO::compute_SS_distances(
        myGOs,
        distance="Wang"
    )

    # build MDS plot for a GO_SS-class distance object
    ViSEAGO::MDSplot(myGOs)

    # GOtermsHeatmap with default parameters
    Wang_clusters_wardD2<-ViSEAGO::GOterms_heatmap(
        myGOs,
        showIC=TRUE,
        showGOlabels=TRUE,
        GO.tree=list(
            tree=list(
                distance="Wang",
                aggreg.method="ward.D2",
                rotate=NULL
            ),
            cut=list(
                dynamic=list(
                    pamStage=TRUE,
                    pamRespectsDendro=TRUE,
                    deepSplit=2,
                    minClusterSize =2
                )
            )
        ),
        samples.tree=NULL
    )

    # Display GO terms heatmap
    ViSEAGO::show_heatmap(
        Wang_clusters_wardD2,
        "GOterms"
    )

    # Print GO terms heatmap
    ViSEAGO::show_heatmap(
        Wang_clusters_wardD2,
        "GOterms",
        "GOterms_heatmap.png"
    )

    # compute clusters of GO terms Semantic Similarity distances
    Wang_clusters_wardD2<-ViSEAGO::compute_SS_distances(
        Wang_clusters_wardD2,
        distance="BMA"
    )

    # GOclusters heatmap
    Wang_clusters_wardD2<-ViSEAGO::GOclusters_heatmap(
        Wang_clusters_wardD2,
        tree=list(
            distance="BMA",
            aggreg.method="ward.D2",
            rotate=NULL
        )
    )

    # Display GO clusters heatmap
    ViSEAGO::show_heatmap(
        Wang_clusters_wardD2,
        "GOclusters"
    )

    # Print GO clusters heatmap
    ViSEAGO::show_heatmap(
        Wang_clusters_wardD2,
        "GOclusters",
        "GOclusters_heatmap.png"
    )

    ## End(Not run)

[Package ViSEAGO version 1.4.0 Index]