bcRep (version 1.3.2)

geneUsage.distance: Dissimilarity/distance indices for gene usage data

Description

This function calculates Bray-Curtis, Jaccard or cosine indices for gene usage data of different samples.

Usage

geneUsage.distance(geneUsage.tab=NULL, names=NULL, 
     method=c("bc","jaccard", "cosine"), cutoff=0)

Arguments

geneUsage.tab

gene usage table with genes as columns and samples as rows

names

Names of samples (default: Sample1...n)

method

Distance/dissimilarity index to be used for calculation. On of Bray-Curtis (bc), Jaccard (jaccard) or cosine (cosine)

cutoff

Cutoff for gene proportions (default: 0; see details)

Value

• Output is a matrix containing dissimilarity/distance indices between samples, based on gene usages.

Details

This function calculates dissmiliarity indices based on gene usage data of different samples (columns = genes, rows = samples). Bray-Curtis, Jaccard or cosine indices can be chosen.

For explanation of Bray-Curtis and Jaccard index see vegdist.

For explanation of cosine index see dist.

When using Jaccard index, a cutoff for gene proportions can be given. Proportions will be transformed into absence/presence data (<= cutoff;=""> cutoff) and afterwards Jaccard indices are calculated.

References

Bray, J. R. and J. T. Curtis. 1957. An ordination of upland forest communities of southern Wisconsin. Ecological Monographs 27:325-349.

Levandowsky, Michael; Winter, David (1971), "Distance between sets", Nature 234 (5): 34-35

Graham L. Giller (2012). "The Statistical Properties of Random Bitstreams and the Sampling Distribution of Cosine Similarity". Giller Investments Research Notes (20121024/1)

Jari Oksanen, F. Guillaume Blanchet, et al. (2015). vegan: Community Ecology Package. R package version 2.3-1. http://CRAN.R-project.org/package=vegan David Meyer and Christian Buchta (2015). proxy: Distance and Similarity Measures. R package version 0.4-15. http://CRAN.R-project.org/package=proxy

See Also

dist.PCoA, plotDistPCoA, sequences.distance

Examples

data(vgenes) # VH gene proportions of 10 samples (rows) and 30 VH genes (columns)
disttab<-geneUsage.distance(geneUsage.tab = vgenes, method = "bc")