relNetworkB: Relevance Network analysis
In maigesPack: Functions to handle cDNA microarray data, including several methods of data analysis

Description Usage Arguments Details Value Author(s) References See Also Examples

Function to construct Relevance Networks for one biological type (Butte's Relevance Network).

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relNetworkB(data=NULL, gLabelID="GeneName", sLabelID="Classification",
            geneGrp=NULL, path=NULL, samples=NULL,
            type="Rpearson", bRep=1000, ...)

`data`	object of class `maiges`.
`gLabelID`	character string giving the identification of gene label ID.
`sLabelID`	character string giving the identification of sample label ID.
`geneGrp`	character string (or numeric index) specifying the gene group to calculate the correlation values between them. If NULL (together with path) all genes are used.
`path`	character string (or numeric index) specifying the gene network to calculate the correlation values between them. If NULL (together with geneGrp) all genes are used.
`samples`	a character vector specifying the group to be compared.
`type`	type of correlation to be calculated. May be 'Rpearson' (default), 'pearson', 'kendall', 'spearman' or 'MI'.
`bRep`	integer specifying the number of bootstrap permutation to calculate the significance of correlation values.
`...`	additional parameters for functions `robustCorr` or `cor`.

This method uses the function cor to calculate the usual correlation values, robustCorr to calculate a robust correlation using an idea similar to the leave-one-out or MI to calculate mutual information values.

The result of this function is an object of class maigesRelNetB.

Gustavo H. Esteves <gesteves@vision.ime.usp.br>

Butte, A.J. and Kohane, I.S. Unsupervised Knowledge discovery in medical databases using relevance networks. In Proc. AMIA Symp., 711-715, 1999 (http://www.amia.org/pubs/symposia/D005550.HTM)

Butte, A.J.; Tamayo, P.; Slonim, D.; Golub, T.R. and Kohane, I.S. Discovering functional relationships between RNA expression and chemotherapeutic susceptibility using relevance networks, PNAS, 97, 12182-12186, 2000 (http://www.pnas.org/cgi/content/full/97/22/12182)

Butte, A.J. and Kohane, I.S. Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements. In Pacific Symposium on Biocomputing, 5, 415-426, 2000 (http://psb.stanford.edu/psb-online/proceedings/psb00/)

cor, robustCorr, MI maigesRelNetB, plot.maigesRelNetB, image.maigesRelNetB.

## Loading the dataset
data(gastro)

## Constructing the relevance network (Butte's method) for sample
## 'Tissue' equal to 'Neso' for the 1st gene group
gastro.net = relNetworkB(gastro.summ, sLabelID="Tissue", 
  samples="Neso", geneGrp=1, type="Rpearson")

## Constructing the relevance network (Butte's method) for sample
## 'Type' equal to 'Col' for the 1st gene group using the conventional
## pearson correlation
gastro.net = relNetworkB(gastro.summ, sLabelID="Type", 
  samples="Col", geneGrp=1, type="pearson")