compare_clusters-methods: Heatmap to compare partitions

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

Description

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

Usage

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

###################
# 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.