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

In kevinrue/GOexpress-release: Visualise microarray and RNAseq data using gene ontology annotations

Description

Successively plots univariate effects of one or more factors, typically for a designed experiment as analyzed by aov().

Usage

plot_design(
    go_id, result, eSet,
    factors=colnames(pData(eSet)), main="", main.Lsplit=NULL, ...)

Arguments

go_id	A Gene Ontology (GO) identifier represented by at least one gene in the dataset.
result	The output of GO_analyse() or a subset of it obtained from subset_scores().
eSet	ExpressionSet of the Biobase package including a gene-by-sample expression matrix in the AssayData slot, and a phenotypic information data-frame in the phenodata 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.
factors	A set of column names from phenodata. 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.
main	Changes the main title of the plots.
main.Lsplit	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.
...	Additional arguments which will be passed on to the plot.design() function.

Value

The output of the plot.design() function.

Author(s)

Kevin Rue-Albrecht

See Also

Method plot.design.

Examples

# load the sample output data
data(AlvMac_results)

# Univariate plot
plot_design(go_id="GO:0034142", eSet=AlvMac, result=AlvMac_results)

kevinrue/GOexpress-release documentation built on May 20, 2019, 9:08 a.m.