maigesPack (version 1.36.0)

relNetworkB: Relevance Network analysis

Description

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

Usage

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

Arguments

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.

Value

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

Details

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.

References

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/)

See Also

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

Examples

## 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")