compare_clusters-methods: Heatmap to compare partitions

Description Usage Arguments Details Value References See Also Examples

Description

Build an interactive heatmap of the common GO terms frequency between several partitions.

Usage

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compare_clusters(clusters)

## S4 method for signature 'list'
compare_clusters(clusters)

Arguments

clusters

a list of named GO_clusters-class objects, from GOterms_heatmap or GOclusters_heatmap methods.

Details

Build an interactive heatmap of common GO terms frequency between partitions from several GO_clusters-class objects.

Value

an interactive javascript heatmap.

References

Carson Sievert, Chris Parmer, Toby Hocking, Scott Chamberlain, Karthik Ram, Marianne Corvellec and Pedro Despouy (2017). plotly: Create Interactive Web Graphics via 'plotly.js'. R package version 4.6.0. https://CRAN.R-project.org/package=plotly

See Also

Other GO_clusters: GO_clusters-class, GOclusters_heatmap, clusters_cor, show_heatmap, show_table

Examples

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###################
# load example object
data(
    myGOs,
    package="ViSEAGO"
)

## Not run: 
###################
# compute Semantic Similarity (SS)
myGOs<-ViSEAGO::compute_SS_distances(
    myGOs,
    distance=c("Resnik","Lin","Rel","Jiang","Wang")
)

##################
# Resnik distance GO terms heatmap
Resnik_clusters_wardD2<-ViSEAGO::GOterms_heatmap(
    myGOs,
    showIC=TRUE,
    showGOlabels=TRUE,
    GO.tree=list(
        tree=list(
            distance="Resnik",
            aggreg.method="ward.D2"
        ),
        cut=list(
            dynamic=list(
                deepSplit=2,
                minClusterSize =2
            )
        )
    ),
    samples.tree=NULL
)

##################
# Lin distance GO terms heatmap
Lin_clusters_wardD2<-ViSEAGO::GOterms_heatmap(
    myGOs,
    showIC=TRUE,
    showGOlabels=TRUE,
    GO.tree=list(
        tree=list(
            distance="Lin",
            aggreg.method="ward.D2"
        ),
        cut=list(
            dynamic=list(
                deepSplit=2,
                minClusterSize =2
            )
        )
    ),
    samples.tree=NULL
)

##################
# Resnik distance GO terms heatmap
Rel_clusters_wardD2<-ViSEAGO::GOterms_heatmap(
    myGOs,
    showIC=TRUE,
    showGOlabels=TRUE,
    GO.tree=list(
        tree=list(
            distance="Rel",
            aggreg.method="ward.D2"
        ),
        cut=list(
            dynamic=list(
                deepSplit=2,
                minClusterSize =2
            )
        )
    ),
    samples.tree=NULL
)

##################
# Resnik distance GO terms heatmap
Jiang_clusters_wardD2<-ViSEAGO::GOterms_heatmap(
    myGOs,
    showIC=TRUE,
    showGOlabels=TRUE,
    GO.tree=list(
        tree=list(
            distance="Jiang",
            aggreg.method="ward.D2"
        ),
        cut=list(
            dynamic=list(
                deepSplit=2,
                minClusterSize =2
            )
        )
    ),
    samples.tree=NULL
)
##################
# Resnik distance GO terms heatmap
Wang_clusters_wardD2<-ViSEAGO::GOterms_heatmap(
    myGOs,
    showIC=TRUE,
    showGOlabels=TRUE,
    GO.tree=list(
        tree=list(
            distance="Wang",
            aggreg.method="ward.D2"
        ),
        cut=list(
            dynamic=list(
                deepSplit=2,
                minClusterSize =2
            )
        )
    ),
    samples.tree=NULL
)

## End(Not run)

###################
# clusters to compare
clusters<-list(
    Resnik="Resnik_clusters_wardD2",
    Lin="Lin_clusters_wardD2",
    Rel="Rel_clusters_wardD2",
    Jiang="Jiang_clusters_wardD2",
    Wang="Wang_clusters_wardD2"
)

## Not run: 
###################
# clusters content comparisons
clusters_comp<-ViSEAGO::compare_clusters(clusters)

## End(Not run)

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