Annotations {FunCluster} | R Documentation

## Functional Profiling of Microarray RNA Expression Data

### Description

This routine belongs to the package FunCluster and performs an automated extraction and update of the Gene Ontology & KEGG annotations which are needed for FunCluster analysis.

### Usage

              annotations(date.annot = "")

### Arguments

`date.annot` | allows to specify the GO release to be used for annotations update. It has no effect on KEGG annotations.

### Details

For details concerning FunCluster please see FunCluster help or man page `help(FunCluster)`. The "Annotations" routine is allowing the automated extraction and update of the functional annotations from their respective web resources. Under common circumstances these routine will provide up-to-date annotations, stored into environmental variables and directly formatted for FunCluster use. Some errors may be seen when using this routine, related to the availability of GO annotations for the current month. In case of extraction errors, explained most usually by a delay in updating GO web servers, the date of the GO release to be used can be expressly indicated through the parameter `annot.date` (see example below). The transcript identification system used for FunCluster analysis is EntrezGene GeneID's. Please see more details on this choice within the JBCB paper.

Important note for Microsoft Windows users: in order to use this routine you will need additional software for handling TAR and GZIP archives. Such software is available for Windows under the GNU license.

For TAR packages you can go to:
http://gnuwin32.sourceforge.net/packages/tar.htm. Please do not forget to place the TAR executable and its dependencies (DLL's) somewhere into the PATH (like "C:/Windows" for example). For GZIP you can go to:
http://gnuwin32.sourceforge.net/packages/gzip.htm. The same observation as for the TAR executables and dependencies applies also here.

### Note

This package is related to a paper submitted to the Journal of Bioinformatics and Computational Biology: Henegar C, Cancello R, Rome S, Vidal H, Clement K, Zucker JD. Clustering biological annotations and gene expression data to identify putatively co-regulated biological processes.

### References

1. Henegar C, Cancello R, Rome S, Vidal H, Clement K, Zucker JD. Clustering biological annotations and gene expression data to identify putatively co-regulated biological processes. J Bioinform Comput Biol. 2006 Aug; 4(4) (in press).

2. Cancello R, Henegar C, Viguerie N, Taleb S, Poitou C, Rouault C, Coupaye M, Pelloux V, Hugol D, Bouillot JL, Bouloumie A, Barbatelli G, Cinti S, Svensson PA, Barsh GS, Zucker JD, Basdevant A, Langin D, Clement K. Reduction of macrophage infiltration and chemoattractant gene expression changes in white adipose tissue of morbidly obese subjects after surgery-induced weight loss. Diabetes 2005; 54(8):2277-86.

3. FunCluster website: http://corneliu.henegar.info/FunCluster.htm

### See Also

`FunCluster`.

### Examples

              ## Not run:
              ## the following example forces the use of a previous GO release
              (e.g. January 2006) for updating annotations;
              KEGG annotations are not affected by this parameter.
              annotations(date.annot = "200601")

    ## End(Not run)

[Package FunCluster version 1.01 Index]