plot_design


    A Gene Ontology (GO) identifier represented by at least one gene
    in the dataset.
    

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


    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


    A set of column names from <code>phenodata</code>. Each of these values will be
    represented on the X-axis to investigate its effect on the average
    expression of a given genes for each level of that factor.
    

factors


    Changes the main title of the plots.
    

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 arguments which will be passed on to the <code>plot.design</code>()
    function.
    


Successively plots univariate effects of one or more
<code><a rd-options="base:factor" href="/link/factors?package=GOexpress&version=1.6.1&to=base%3Afactor" data-mini-rdoc="base:factor::factors">factors</a></code>, typically for a designed experiment
as analyzed by <code><a rd-options="stats:aov" href="/link/aov?package=GOexpress&version=1.6.1&to=stats%3Aaov" data-mini-rdoc="stats:aov::aov">aov</a></code>().


 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.

Kevin Rue-Albrecht

GOexpress

Visualise microarray and RNAseq data using gene ontology annotations

plot_design function


Successively plots univariate effects of one or more
<code><a rd-options='base:factor' href='factors'>factors</a></code>, typically for a designed experiment
as analyzed by <code><a rd-options='stats:aov' href='aov'>aov</a></code>().


plot_design: Plot Univariate Effects for genes associated with a Gene Ontology

Description

Usage

Arguments

Value

See Also

Examples