GOclusters_heatmap {ViSEAGO} | R Documentation

## Build a clustering heatmap on GO groups.

### Description

This method computes a clustering heatmap based on GO groups semantic similarity.

### Usage

    GOclusters_heatmap(
      object,
      tree = list(distance = "BMA", aggreg.method = "ward.D2", rotate = NULL)
    )

    ## S4 method for signature 'GO_clusters,list'
    GOclusters_heatmap(
      object,
      tree = list(distance = "BMA", aggreg.method = "ward.D2", rotate = NULL)
    )

### Arguments

`object` | a `GO_clusters-class` object from `compute_SS_distances`.
`tree` | a named list with: distance ("BMA" by default) distance computed from the semantic similarity for GO groups which could be "max", "avg", "rcmax",or "BMA". aggreg.method ("ward.D2" by default) aggregation method criteria from `hclust` (ward.D", "ward.D2", "single", "complete", "average", "mcquitty", "median", or "centroid") to build a `dendrogram`. rotate sort the branches of the tree based on a vector - eithor of labels order or the labels in their new order

### Details

This method computes a clustering heatmap based on GO groups semantic similarity (computed with `compute_SS_distances`).
The heatmap color intensity corresponds to the number of GO terms in each GO group.
GO group description is defined as the first common GO ancestor with the cluster identifiant in brackets.
The dendrogram branches are colored according to GO terms clusters.

### Value

a `GO_clusters-class` object.

### References

Matt Dowle and Arun Srinivasan (2017). data.table: Extension of 'data.frame'. R package version 1.10.4. https://CRAN.R-project.org/package=data.table.

Tal Galili (2015). dendextend: an R package for visualizing, adjusting, and comparing trees of hierarchical clustering. Bioinformatics. DOI:10.1093/bioinformatics/btv428.

Tal Galili (2017). heatmaply: Interactive Cluster Heat Maps Using 'plotly'. R package version 0.9.1. https://CRAN.R-project.org/package=heatmaply.

Erich Neuwirth (2014). RColorBrewer: ColorBrewer Palettes. R package version 1.1-2. https://CRAN.R-project.org/package=RColorBrewer.

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.

H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2009.

### See Also

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

Other semantic_similiarity: `GOterms_heatmap()`

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

### Examples

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

    # 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
    )

    # 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
        )
    )

    ## End(Not run)

[Package ViSEAGO version 1.4.0 Index]