[adegenet-commits] r907 - in pkg: R inst/doc man

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Mon Jun 13 23:11:34 CEST 2011 

Author: jombart
Date: 2011-06-13 23:11:33 +0200 (Mon, 13 Jun 2011)
New Revision: 907

Modified:
   pkg/R/import.R
   pkg/inst/doc/adegenet-genomics.Rnw
   pkg/inst/doc/adegenet-genomics.pdf
   pkg/inst/doc/adegenet-genomics.tex
   pkg/man/glAux.Rd
Log:
Added multicore option to fasta2genlight
Genomic vignette moving forward.
Doc fixes.


Modified: pkg/R/import.R
===================================================================
--- pkg/R/import.R	2011-06-13 18:04:17 UTC (rev 906)
+++ pkg/R/import.R	2011-06-13 21:11:33 UTC (rev 907)
@@ -1087,9 +1087,13 @@
         nb.ind <- length(grep("^>", txt))
         IND.LAB <- c(IND.LAB, sub(">","",txt[grep("^>", txt)])) # find individuals' labels
         txt <- split(txt, rep(1:nb.ind, each=LINES.PER.IND)) # split per individuals
-        txt <- lapply(txt, function(e) strsplit(paste(e[-1], collapse=""), split="")) # each genome -> one vector
+        if(multicore){
+            txt <- mclapply(txt, function(e) strsplit(paste(e[-1], collapse=""), split=""),
+                            mc.cores=n.cores, mc.silent=TRUE, mc.cleanup=TRUE, mc.preschedule=FALSE) # each genome -> one vector
+        } else {
+            txt <- lapply(txt, function(e) strsplit(paste(e[-1], collapse=""), split="")) # each genome -> one vector
+        }
 
-
         ## POOL contains all alleles of each position
         temp <- as.list(apply(matrix(unlist(txt), byrow=TRUE, nrow=length(txt)),2,unique)) # alleles current genomes
         POOL <- mapply(function(x,y) unique(c(x,y)), POOL, temp, SIMPLIFY=FALSE) # update global pool
@@ -1137,9 +1141,13 @@
         ## read SNPs
         nb.ind <- length(grep("^>", txt))
         txt <- split(txt, rep(1:nb.ind, each=LINES.PER.IND)) # split per individuals
-        txt <- lapply(txt, function(e) strsplit(paste(e[-1], collapse=""), split="")[[1]][snp.posi]) # each genome -> one SNP vector
+        if(multicore){
+            txt <- mclapply(txt, function(e) strsplit(paste(e[-1], collapse=""), split="")[[1]][snp.posi],
+                                        mc.cores=n.cores, mc.silent=TRUE, mc.cleanup=TRUE, mc.preschedule=FALSE) # each genome -> one SNP vector
+        } else {
+            txt <- lapply(txt, function(e) strsplit(paste(e[-1], collapse=""), split="")[[1]][snp.posi]) # each genome -> one SNP vector
+        }
 
-
         ## convert to genlight
         ##res <- c(res, lapply(txt, function(e) new("SNPbin", as.integer(e==sec.all))))
         res <- c(res, lapply(txt, function(e) new("SNPbin", f1(e))))

Modified: pkg/inst/doc/adegenet-genomics.Rnw
===================================================================
--- pkg/inst/doc/adegenet-genomics.Rnw	2011-06-13 18:04:17 UTC (rev 906)
+++ pkg/inst/doc/adegenet-genomics.Rnw	2011-06-13 21:11:33 UTC (rev 907)
@@ -573,7 +573,7 @@
 genome; this is very easily done in R, using \texttt{density} with an appropriate bandewidth:
 <<fig=TRUE>>=
 temp <- density(position(obj), bw=10)
-plot(temp, type="n", xlab="Position in the alignment", main="Location of the SNPs")
+plot(temp, type="n", xlab="Position in the alignment", main="Location of the SNPs", xlim=c(0,1701))
 polygon(c(temp$x,rev(temp$x)), c(temp$y, rep(0,length(temp$x))), col=transp("blue",.3))
 points(position(obj), rep(0, nLoc(obj)), pch="|", col="blue")
 @
@@ -642,14 +642,43 @@
 %%%%%%%%%%%%%%%%
 \subsection{Simple operations}
 %%%%%%%%%%%%%%%%
+Some simple operations such as computing allele frequencies or diagnosing missing values can be
+problematic when the data matrix cannot be represented in memory.
+\textit{adegenet} implements a few basic procedures which perform such basic tasks on
+\texttt{genlight} objects processing one individual at a time, thereby minimizing memory
+requirements. The most computer-intensive of these procedures can also use compiled C code and/or
+multicore capabilities (when available) to speed up computations.
+\\
 
 
+All these procedures are named using the prefix \texttt{gl} (for \texttt{genlight}), and can therefore be listed by
+typing \texttt{gl} and pressing the TAB key twice.
+They are (see \texttt{?glMean}):
+\begin{itemize}
+\item \texttt{glSum}: computes the sum of second alleles for each SNP.
+\item \texttt{glNA}: computes the number of missing values in each locus.
+\item \texttt{glMean}: computes the mean of second alleles, i.e. second allele frequencies for
+  each SNP.
+\item \texttt{glVar}: computes the variance of the second allele frequency for each SNP.
+\item \texttt{glDotProd}: computes the dot products between all pairs of individuals, with
+  possible centring and scaling.
+\end{itemize}
+For instance, one can easily map missing data across loci as we have done for SNP positions in the
+US influenza dataset (see previous section) using \texttt{glNA} and \texttt{density}:
+<<>>=
+head(glNA(obj),20)
+temp <- density(glNA(obj), bw=10)
+plot(temp, type="n", xlab="Position in the alignment", main="Location of the missing values (NAs)", xlim=c(0,1701))
+polygon(c(temp$x,rev(temp$x)), c(temp$y, rep(0,length(temp$x))), col=transp("blue",.3))
+points(glNA(obj), rep(0, nLoc(obj)), pch="|", col="blue")
+@
 
+\noindent Here, the few missing values are all located at the beginning at the alignment, probably
+reflecting heterogeneity in DNA amplification during the sequencing process.
+In actually large datasets, such simple investigation can give crucial insights about the quality of
+the data and the existence of possible biases.
 
 
-%%%%%%%%%%%%%%%%
-\subsection{Principal Component Analysis (PCA)}
-%%%%%%%%%%%%%%%%
 
 
 
@@ -659,6 +688,7 @@
 
 
 
+
 %%%%%%%%%%%%%%%%
 \subsection{Discriminant Analysis of Principal Components (DAPC)}
 %%%%%%%%%%%%%%%%

Modified: pkg/inst/doc/adegenet-genomics.pdf
===================================================================
--- pkg/inst/doc/adegenet-genomics.pdf	2011-06-13 18:04:17 UTC (rev 906)
+++ pkg/inst/doc/adegenet-genomics.pdf	2011-06-13 21:11:33 UTC (rev 907)
@@ -88,18 +88,12 @@
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[TRUNCATED]

To get the complete diff run:
    svnlook diff /svnroot/adegenet -r 907

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