R: Between- and within-class double principal coordinate...

bwca.dpcoa {ade4} | R Documentation

## Between- and within-class double principal coordinate analysis

### Description

These functions allow to study the variations in diversity among communities (as in dpcoa) taking into account a partition in classes

### Usage

    bwca.dpcoa(x, fac, cofac, scannf = TRUE, nf = 2, ...)
    ## S3 method for class 'dpcoa'
    bca(x, fac, scannf = TRUE, nf = 2, ...)
    ## S3 method for class 'dpcoa'
    wca(x, fac, scannf = TRUE, nf = 2, ...)
    ## S3 method for class 'betwit'
    randtest(xtest, nrepet = 999, ...)
    ## S3 method for class 'betwit'
    summary(object, ...)
    ## S3 method for class 'witdpcoa'
    print(x, ...)
    ## S3 method for class 'betdpcoa'
    print(x, ...)

### Arguments

`x` | an object of class `dpcoa`
`fac` | a factor partitioning the collections in classes
`scannf` | a logical value indicating whether the eigenvalues barplot should be displayed
`nf` | if scannf FALSE, a numeric value indicating the number of kept axes
`...` | further arguments passed to or from other methods
`cofac` | a cofactor partitioning the collections in classes used as a covariable
`nrepet` | the number of permutations
`xtest, object` | an object of class `betwit` created by a call to the function `bwca.dpcoa`

### Value

Objects of class `betdpcoa`, `witdpcoa` or `betwit`

### Author(s)

Stéphane Dray stephane.dray@univ-lyon1.fr

### References

Dray, S., Pavoine, S. and Aguirre de Carcer, D. (2015) Considering external information to improve the phylogenetic comparison of microbial communities: a new approach based on constrained Double Principal Coordinates Analysis (cDPCoA). Molecular Ecology Resources, 15, 242–249. doi:10.1111/1755-0998.12300

### See Also

`dpcoa`

### Examples

    ## Not run:

    ## First example of Dray et al (2015) paper

    con <- url("ftp://pbil.univ-lyon1.fr/pub/datasets/dray/MER2014/soilmicrob.rda")
    load(con)
    close(con)

    ## Partial CCA
    coa <- dudi.coa(soilmicrob$OTU, scannf = FALSE)
    wcoa <- wca(coa, soilmicrob$env$pH, scannf = FALSE)
    wbcoa <- bca(wcoa,soilmicrob$env$VegType, scannf = FALSE)

    ## Classical DPCoA
    dp <- dpcoa(soilmicrob$OTU, soilmicrob$dphy, RaoDecomp = FALSE, scannf = FALSE)

    ## Between DPCoA (focus on the effect of vegetation type)
    bdp <- bca(dp, fac = soilmicrob$env$VegType , scannf = FALSE)
    bdp$ratio ## 0.2148972
    randtest(bdp) ## p = 0.001

    ## Within DPCoA (remove the effect of pH)
    wdp <- wca(dp, fac = soilmicrob$env$pH, scannf = FALSE)
    wdp$ratio ## 0.5684348

    ## Between Within-DPCoA (remove the effect of pH and focus on vegetation type)
    wbdp <- bwca.dpcoa(dp, fac = soilmicrob$env$VegType, cofac =  soilmicrob$env$pH, scannf = FALSE)
    wbdp$ratio ## 0.05452813
    randtest(wbdp) ## p = 0.001

    ## End(Not run)

[Package ade4 version 1.7-16 Index]