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.
|License:||GPL (>= 3)|
This package requires only two input variables
ExpressionSet containing assayData and phenoData.
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
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 <
Main method for an example usage:
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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 Welcome to Bioconductor Vignettes contain introductory material; view with 'browseVignettes()'. To cite Bioconductor, see 'citation("Biobase")', and for packages 'citation("pkgname")'.
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