show_heatmap-methods: Display an interactive or static heatmap.

In ViSEAGO: ViSEAGO: a Bioconductor package for clustering biological functions using Gene Ontology and semantic similarity

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)

ViSEAGO documentation built on Nov. 8, 2020, 6:51 p.m.