GOexpress-package: Visualise microarray and RNAseq data with gene ontology...
In GOexpress: Visualise microarray and RNAseq data using gene ontology annotations

Description Details Author(s) See Also Examples

Integrates gene expression data with gene ontology annotations to score and visualise genes and gene ontologies best clustering groups of experimental samples. Supports custom annotations, or alternatively provides an interface to the Ensembl annotations using the biomaRt package. The default scoring approach is based on the random forest framework, while a one-way ANOVA is available as an alteranative. GO term are scored and ranked according to the average rank (alternatively, average power) of all associated genes. P-values can be generated to assess the significance of GO term ranking. The ranked list of GO terms is returned, with tools allowing to visualise the statistics on a gene- and ontology-basis.

Package:	GOexpress
Type:	Package
Version:	1.7.1
Date:	2016-02-06
License:	GPL (>= 3)

This package requires only two input variables

An ExpressionSet containing assayData and phenoData. The former should be a gene-by-sample matrix providing gene expression values for each gene in each sample. The latter should be an AnnotatedDataFrame from the Biobase package providing phenotypic information and grouping factors with two or more levels.
The name of the grouping factor to investigate, which must be a valid column name in the phenoData slot of the above ExpressionSet.

Following analysis, visualisation methods include:

Histogram and quantiles representations of the scores of GO terms
Permutation-based P-values to assess the significance of GO term ranking
Filtering of results on various criteria (e.g. number of genes annotated to GO term)
Re-ordering of GO terms and gene result tables based on score or rank metric
Table of statistics for genes annotated to a given GO term
Hierarchical clustering of samples based on the expression level of genes annotated to a given GO term
Heatmap of samples and genes based on the expression level of genes annotated to a given GO term
Expression profile of a gene against one given factor (e.g. Time) while grouping samples on another given factor (e.g. Treatment)
Univariate analysis of the expression level of a gene in the different groups of each experimental factor.
Venn diagram of the counts of genes shared between a list of GO terms.

Maintainer: Kevin Rue-Albrecht <kevinrue67@gmail.com>

Main method for an example usage: GO_analyse.

Packages Biobase, randomForest, RColorBrewer, VennDiagram.

Methods biomaRt:getBM, ggplot2:ggplot, gplots:heatmap.2, gplots:bluered, gplots:greenred, grid:grid.newpage, grid:grid.layout, stringr:str_extract.

# Sample input data available with package:
data(AlvMac)

# Sample output data available with package:
data(AlvMac_results)

# Supported species and microarrays:
data(microarray2dataset)
data(prefix2dataset)

Loading required package: grid
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colMeans, colSums, colnames,
    dirname, do.call, duplicated, eval, evalq, get, grep, grepl,
    intersect, is.unsorted, lapply, lengths, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, rank, rbind,
    rowMeans, rowSums, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which, which.max, which.min

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