Learn R Programming

GlobalAncova (version 3.40.0)

GlobalAncova gene set testing methods: Gene set testing of gene set databases using GlobalAncova

Description

Three functions adapted from package globaltest to test gene sets from databases for association of the gene expression profile with a response variable. Three function are provided for KEGG, for Gene Ontology and for the Broad Institute's gene sets.

Usage

GAKEGG (xx, ..., id, annotation, probe2entrez, multtest = c("holm", "BH", "BY"), sort = TRUE)
GAGO (xx, ..., id, annotation, probe2entrez, ontology = c("BP", "CC", "MF"), minsize=1, maxsize=Inf, multtest = c("holm", "focuslevel", "BH", "BY"), focuslevel = 10, sort = TRUE)
GABroad (xx, ..., id, annotation, probe2entrez, collection, category = c("c1", "c2", "c3", "c4", "c5"), multtest = c("holm", "BH", "BY"), sort = TRUE)

Arguments

xx
Matrix of gene expression data, where columns correspond to samples and rows to genes. Gene names have to be included as the row names of xx
...
Arguments describing the tests to be performed are passed on to GlobalAncova. Note that only the approximative version of GlobalAncova is used here and hence the parameter method is not available. Even though the number of permutations (perm) may be specified since very large gene sets (with more genes than max.group.size) are treated with the permutation test.
id
The identifier(s) of gene sets to be tested (character vector). If omitted, tests all gene sets in the database.
annotation
The name of the probe annotation package for the microarray that was used, or the name of the genome wide annotation package for the species (e.g. org.Hs.eg.db for human). If an organism package is given, the argument probe2entrez must be supplied.
probe2entrez
Use only if no probe annotation package is available. A mapping from probe identifiers to entrez gene ids. May be an environment, named list or named vector.
multtest
The method of multiple testing correction. Choose from: Benjamini and Hochberg FDR control (BH); Benjamini and Yekutieli FDR control (BY) or Holm familywise error control (holm). For GAGO also the focus level method is available. See focusLevel.
sort
If TRUE, sorts the results to increasing p-values.
ontology
The ontology or ontologies to be used. Default is to use all three ontologies.
minsize
The minimum number of probes that may be annotated to a gene set. Gene sets with fewer annotated probes are discarded.
maxsize
The maximum number of probes that may be annotated to a gene set. Gene sets with more annotated probes are discarded.
focuslevel
The focus level to be used for the focus level method. Either a vector of gene set ids, or a numerical level. In the latter case, findFocus is called with maxsize at the specified level to find a focus level.
collection
The Broad gene set collection, created by a call to getBroadSets.
category
The subcategory of the Broad collection to be tested. The default is to test all sets.

Value

p-values for each gene set.

Details

These are utility functions to make it easier to do gene set testing of gene sets available in gene set databases. The functions automatically retrieve the gene sets, preprocess and select them, perform global test, do multiple testing correction, and sort the results on the basis of their p-values. All functions require that annotate and the appropriate annotation packages are installed. GAKEGG additionally requires the KEGG.db package; GAGO requires the GO.db package; GABroad requires the user to download the XML file "msigdb_v2.5.xml" from \ http://www.broad.mit.edu/gsea/downloads.jsp, and to preprocess that file using the getBroadSets function.

References

Goeman, J.J. and Mansmann, U., Multiple testing on the directed acyclic graph of Gene Ontology. Bioinformatics 2008; 24(4): 537-44.

See Also

gtGO, gtKEGG, gtBroad, GlobalAncova, gt,

Examples

Run this code
  # see vignettes of packages GlobalAncova and globaltest and help of gtGO

Run the code above in your browser using DataLab