[adegenet-commits] r545 - pkg/man

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Mon Feb 1 17:09:55 CET 2010 

Author: jombart
Date: 2010-02-01 17:09:55 +0100 (Mon, 01 Feb 2010)
New Revision: 545

Modified:
   pkg/man/dapc.Rd
   pkg/man/dapcIllus.Rd
Log:
moving forward...


Modified: pkg/man/dapc.Rd
===================================================================
--- pkg/man/dapc.Rd	2010-02-01 15:52:52 UTC (rev 544)
+++ pkg/man/dapc.Rd	2010-02-01 16:09:55 UTC (rev 545)
@@ -159,8 +159,10 @@
 Discriminant analysis of principal components: a new method for the analysis of
 genetically structured populations. Submitted to \emph{PLoS genetics}.
 }
-\seealso{\code{\link{dapcIllus}}, a set of simulated data illustrating
-  the dapc, and \code{\link{eHGDP}} and \code{\link{H3N2}}, which also
+\seealso{\code{\link{find.clusters}}, to identify clusters with prior in
+  the data. \code{\link{dapcIllus}}, a set of simulated data illustrating
+  the DAPC, and \code{\link{eHGDP}} and \code{\link{H3N2}}, empirical
+  datasets also illustrating DAPC.
 }
 \author{ Thibaut Jombart \email{t.jombart at imperial.ac.uk} }
 \examples{

Modified: pkg/man/dapcIllus.Rd
===================================================================
--- pkg/man/dapcIllus.Rd	2010-02-01 15:52:52 UTC (rev 544)
+++ pkg/man/dapcIllus.Rd	2010-02-01 16:09:55 UTC (rev 545)
@@ -1,121 +1,70 @@
 \encoding{UTF-8}
-\name{spcaIllus}
-\alias{spcaIllus}
+\name{dapcIllus}
+\alias{dapcIllus}
 \docType{data}
-\title{Simulated data illustrating the sPCA}
+\title{Simulated data illustrating the dapc}
 \description{
-  Datasets illustrating the spatial Principal Component Analysis
-  (Jombart et al. submitted).
+  Datasets illustrating the Discriminant Analysis of Principal
+  Components (DAPC, Jombart et al. submitted).\cr
+
   These data were simulated using various models using Easypop (2.0.1).
-  Spatial coordinates were defined so that different spatial patterns
-  existed in the data. The \code{spca-illus} is a list containing the
-  following \linkS4class{genind} or \linkS4class{genpop} objects:\cr
-  - dat2A: 2 patches \cr
-  - dat2B: cline between two pop \cr
-  - dat2C: repulsion among individuals from the same gene pool \cr
-  - dat3: cline and repulsion \cr
-  - dat4: patches and local alternance \cr
+  The \code{dapcIllus} is a list containing the
+  following \linkS4class{genind} objects:\cr
+  - "a": island model with 6 populations \cr
+  - "b": hierarchical island model with 6 populations (3,2,1) \cr
+  - "c": one-dimensional stepping stone with 2x6 populations, and a boundary between the
+  two sets of 6 populations\cr
+  - "d": one-dimensional stepping stone with 24 populations\cr
 
   See "source" for a reference providing simulation details.
 }
-\usage{data(spcaIllus)}
+\usage{data(dapcIllus)}
 \format{
-  \code{spcaIllus} is list of 5 components being either genind or genpop objects.
+  \code{dapcIllus} is list of 4 components being all genind objects.
 }
 \source{
-   Jombart, T., Devillard, S., Dufour, A.-B. and Pontier, D.
-Revealing cryptic spatial patterns in genetic variability by a new
-multivariate method. \emph{Heredity}, \bold{101}, 92--103.
+  Jombart, T., Devillard, S. and Balloux, F.
+Discriminant analysis of principal components: a new method for the analysis of
+genetically structured populations. Submitted to \emph{PLoS genetics}.
+
 }
 \author{
   Thibaut Jombart \email{t.jombart at imperial.ac.uk}
 }
-\seealso{ \code{\link{spca}} }
+\seealso{ \code{\link{dapc}}, \code{\link{eHGDP}},  \code{\link{H3N2}}}
 \references{
-  Jombart T, Devillard S, Dufour A-B and Pontier D
-Revealing cryptic spatial patterns in genetic variability by a new
-multivariate method. Submitted to \emph{Heredity}.
- 
-  Balloux F (2001) Easypop (version 1.7): a computer program for oppulation
-  genetics simulations \emph{Journal of Heredity}, \bold{92}: 301-302
+   Jombart, T., Devillard, S. and Balloux, F.
+Discriminant analysis of principal components: a new method for the analysis of
+genetically structured populations. Submitted to \emph{PLoS genetics}.
 }
 \examples{
-if(require(spdep) & require(ade4)){
+if(require(MASS) & require(ade4)){
 
-data(spcaIllus)
-attach(spcaIllus)
-opar <- par(no.readonly=TRUE)
-## comparison PCA vs sPCA
+data(dapcIllus)
+attach(dapcIllus)
 
-# PCA
-pca2A <- dudi.pca(dat2A$tab,center=TRUE,scale=FALSE,scannf=FALSE)
-pca2B <- dudi.pca(dat2B$tab,center=TRUE,scale=FALSE,scannf=FALSE)
-pca2C <- dudi.pca(dat2C$tab,center=TRUE,scale=FALSE,scannf=FALSE)
-pca3 <- dudi.pca(dat3$tab,center=TRUE,scale=FALSE,scannf=FALSE,nf=2)
-pca4 <- dudi.pca(dat4$tab,center=TRUE,scale=FALSE,scannf=FALSE,nf=2)
+## PERFORM DAPCs
+dapc.a <- dapc(dapcIllus$a, n.pca=100, n.da=5)
+dapc.b <- dapc(dapcIllus$b, n.pca=100, n.da=5)
+dapc.c <- dapc(dapcIllus$c, n.pca=100, n.da=11)
+dapc.d <- dapc(dapcIllus$d, n.pca=100, n.da=11)
 
-# sPCA
-spca2A <- spca(dat2A,xy=dat2A$other$xy,ask=FALSE,type=1,plot=FALSE,scannf=FALSE,nfposi=1,nfnega=0)
 
-spca2B <- spca(dat2B,xy=dat2B$other$xy,ask=FALSE,type=1,plot=FALSE,scannf=FALSE,nfposi=1,nfnega=0)
+## LOOK AT ONE RESULT
+dapc.a
+summary(dapc.a)
 
-spca2C <- spca(dat2C,xy=dat2C$other$xy,ask=FALSE,type=1,plot=FALSE,scannf=FALSE,nfposi=0,nfnega=1)
+## FORM A LIST OF RESULTS FOR THE 4 DATASETS
+lres <- list(dapc.a, dapc.b, dapc.c, dapc.d)
 
-spca3 <- spca(dat3,xy=dat3$other$xy,ask=FALSE,type=1,plot=FALSE,scannf=FALSE,nfposi=1,nfnega=1)
 
-spca4 <- spca(dat4,xy=dat4$other$xy,ask=FALSE,type=1,plot=FALSE,scannf=FALSE,nfposi=1,nfnega=1)
-
-# an auxiliary function for graphics
-plotaux <- function(x,analysis,axis=1,lab=NULL,...){
-neig <- NULL
-if(inherits(analysis,"spca")) neig <- nb2neig(analysis$lw$neighbours)
-xrange <- range(x$other$xy[,1])
-xlim <- xrange + c(-diff(xrange)*.1 , diff(xrange)*.45)
-yrange <- range(x$other$xy[,2])
-ylim <- yrange + c(-diff(yrange)*.45 , diff(yrange)*.1)
-
-s.value(x$other$xy,analysis$li[,axis],include.ori=FALSE,addaxes=FALSE,cgrid=0,grid=FALSE,neig=neig,cleg=0,xlim=xlim,ylim=ylim,
-...)
-
-par(mar=rep(.1,4))
-if(is.null(lab)) lab = gsub("[P]","",x$pop)
-text(x$other$xy, lab=lab, col="blue", cex=1.2, font=2)
-add.scatter({barplot(analysis$eig,col="grey");box();title("Eigenvalues",line=-1)},posi="bottomright",ratio=.3)
-}
-
-# plots
-plotaux(dat2A,pca2A,sub="dat2A - PCA",pos="bottomleft",csub=2)
-plotaux(dat2A,spca2A,sub="dat2A - sPCA glob1",pos="bottomleft",csub=2)
-
-plotaux(dat2B,pca2B,sub="dat2B - PCA",pos="bottomleft",csub=2)
-plotaux(dat2B,spca2B,sub="dat2B - sPCA glob1",pos="bottomleft",csub=2)
-
-plotaux(dat2C,pca2C,sub="dat2C - PCA",pos="bottomleft",csub=2)
-plotaux(dat2C,spca2C,sub="dat2C - sPCA loc1",pos="bottomleft",csub=2,axis=2)
-
+## DRAW 4 SCATTERPLOTS
 par(mfrow=c(2,2))
-plotaux(dat3,pca3,sub="dat3 - PCA axis1",pos="bottomleft",csub=2)
-plotaux(dat3,spca3,sub="dat3 - sPCA glob1",pos="bottomleft",csub=2)
-plotaux(dat3,pca3,sub="dat3 - PCA axis2",pos="bottomleft",csub=2,axis=2)
-plotaux(dat3,spca3,sub="dat3 - sPCA loc1",pos="bottomleft",csub=2,axis=2)
+sapply(lres, scatter)
 
-plotaux(dat4,pca4,lab=dat4$other$sup.pop,sub="dat4 - PCA axis1",pos="bottomleft",csub=2)
-plotaux(dat4,spca4,lab=dat4$other$sup.pop,sub="dat4 - sPCA glob1",pos="bottomleft",csub=2)
-plotaux(dat4,pca4,lab=dat4$other$sup.pop,sub="dat4 - PCA axis2",pos="bottomleft",csub=2,axis=2)
-plotaux(dat4,spca4,lab=dat4$other$sup.pop,sub="dat4 - sPCA loc1",pos="bottomleft",csub=2,axis=2)
 
-# color plot
-par(opar)
-colorplot(spca3, cex=4, main="colorplot sPCA dat3")
-text(spca3$xy[,1], spca3$xy[,2], dat3$pop)
-
-colorplot(spca4, cex=4, main="colorplot sPCA dat4")
-text(spca4$xy[,1], spca4$xy[,2], dat4$other$sup.pop)
-
 # detach data
-detach(spcaIllus)
+detach(dapcIllus)
 }
 }
 \keyword{datasets}
-\keyword{spatial}
-

More information about the adegenet-commits mailing list