show_heatmap-methods: Display an interactive or static heatmap.

In abrionne/ViSEAGO: ViSEAGO: Easier data mining of biological functions organized into clusters using Gene Ontology and semantic similarity

Description

Display a heatmap in interactive or static mode.

Usage

show_heatmap(object, type, file = NULL)

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

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).

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.

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)

abrionne/ViSEAGO documentation built on June 13, 2019, 2:27 p.m.