cluster_GO


    A Gene Ontology (GO) identifier.
    

go_id


    The output of <code>GO_analyse()</code> or a subset of it obtained from
    <code>subset_scores()</code>.
    

result


    <code>ExpressionSet</code> of the <code>Biobase</code> package including a
    gene-by-sample expression matrix in the <code>AssayData</code> slot, and a
    phenotypic information data-frame in the <code>phenodata</code> slot. In the
    expression matrix, row names are Ensembl gene identifiers or probeset
    identifiers, and column names are sample identifiers. In the phentypic
    data-frame, row names are sample idenfifiers, column names are grouping
    factors and phenotypic traits usable for the one-way ANOVA. 
    

eSet


    The grouping factor in <code>phenodata</code> to label the samples by.
    


    A named list to subset <code>eSet</code>. Names must be column names existing
    in colnames(pData(eSet)). Values must be vectors of values existing in
    the corresponding column of pData(eSet).
    

subset


    The method used to calculate distance between samples. See the 
    <code>dist()</code> method from package <code>stats</code>.
    

method_dist


    The method used to cluster samples. See the 
    <code>hclust()</code> method from package <code>stats</code>.
    

method_hclust


    A numeric value defining the character expansion of text in the plot.
    


    A character string for the main title of the plot.
    

main


    A label for the x axis, defaults to "Distance".
    

xlab


    Scaling factor of the main title font size. Default is 1. We suggest to 
    use it in combination with the argument <code>main.Lsplit</code> for GO terms
    with long names.
    

cex.main


    Number of characters after which a new-line character will be inserted in
    the main title. If this would occur within a word, the new-line character
    will be inserted before this word. Default is NULL, leaving the title on a
    single line.
    

main.Lsplit


    Additional parameters passed on to <code>dist()</code>, <code>hclust()</code>
    and <code>plot()</code>.
    


Clusters the samples using only the expression levels of genes associated with
a given go_id.


 Expression 

 Clustering 

 gene 

 GOexpress 

The package contains methods to visualise the expression profile
of genes from a microarray or RNA-seq experiment, and offers a
supervised clustering approach to identify GO terms containing genes
with expression levels that best classify two or more predefined groups of
samples. Annotations for the genes present in the expression dataset may
be obtained from Ensembl through the biomaRt package, if not provided by
the user. The default random forest framework is used to evaluate the
capacity of each gene to cluster samples according to the
factor of interest. Finally, GO terms are scored by averaging the
rank (alternatively, score) of their respective gene sets to cluster
the samples. P-values may be computed to assess the significance of GO
term ranking. Visualisation function include gene expression profile,
gene ontology-based heatmaps, and hierarchical clustering of
experimental samples using gene expression data.

cluster_GO: Generates a hierarchical clustering of the samples

Description

Usage

Arguments

Value

See Also

Examples