Browse code

Finalize updates to copynumber and illumina_copynumber vignettes for v1.8.3 updates

git-svn-id: file:///home/git/hedgehog.fhcrc.org/bioconductor/trunk/madman/Rpacks/crlmm@52837 bc3139a8-67e5-0310-9ffc-ced21a209358

Rob Scharp authored on 16/02/2011 15:58:28
Showing4 changed files

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@@ -1,6 +1,6 @@
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 useDynLib("crlmm", .registration=TRUE)
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 ## this is temporary
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- exportPattern("^[^\\.]")
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+## exportPattern("^[^\\.]")
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 ##---------------------------------------------------------------------------
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 ## Biobase
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@@ -254,6 +254,7 @@ cn.F <- CA(cnSet, i=npx.index, j=F)
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 boxplot(data.frame(cbind(cn.M, cn.F)), pch=".", col="grey60", outline=FALSE)
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 @
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+
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 \begin{figure}[t!]
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  \centering
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  \includegraphics[width=0.8\textwidth]{copynumber-nonpolymorphicX}
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@@ -262,6 +263,7 @@ boxplot(data.frame(cbind(cn.M, cn.F)), pch=".", col="grey60", outline=FALSE)
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     across samples at a given marker on X is 1 for men and 2 for women.}
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 \end{figure}
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+Polymorphic markers on chromosome X:
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 \begin{figure}[t!]
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@@ -268,24 +268,89 @@ The following code chunk can be used to create an instance of
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 \Robject{CopyNumberSet} that contains the CA + CB at polymorphic
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 markers and 'CA' at nonpolymorphic markers.
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+Alternatively, total copy number can be obtained by
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+<<totalCopynumber.snps>>=
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+ct2 <- totalCopynumber(cnSet, i=snp.index, j=1:5)
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+stopifnot(all.equal(ct, ct2))
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+@
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+
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+Missing values can arise at polymorphic when the confidence score of
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+the genotype calls are below the threshold indicated by the threshold
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+\texttt{GT.CONF.THR} in \Robject{crlmmCopynumber}. See
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+\Robject{?crlmmCopynumber} for additional details.  In the following
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+codechunk, we compute the number of samples that had confidence scores
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+below \Sexpr{GT.CONF.THR} at loci for which ${\hat CA}$ and ${\hat CB}$
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+are missing.
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+
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+<<NAs.snps>>=
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+missing.copynumber <- which(rowSums(is.na(ct)) > 0)
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+invisible(open(snpCallProbability(cnSet)))
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+gt.confidence <- i2p(snpCallProbability(cnSet)[snp.index, ])
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+n.below.threshold <- rowSums(gt.confidence < 0.95)
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+unique(n.below.threshold[missing.copynumber])
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+@
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+\noindent For loci with missing copy number, the confidence scores
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+were all below the threshold.
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+
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+At nonpolymorphic loci, either the \Rfunction{CA} or
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+\Rfunction{totalCopynumber} functions can be used to obtain estimates
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+of total copy number.
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+
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+<<nonpolymorphicAutosomes>>=
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+marker.index <- which(!isSnp(cnSet) & chromosome(cnSet) < 23)
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+ct <- CA(cnSet, i=marker.index, j=1:5)
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+## all zeros
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+stopifnot(all(CB(cnSet, i=marker.index, j=1:5) == 0))
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+ct2 <- totalCopynumber(cnSet, i=marker.index, j=1:5)
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+stopifnot(all.equal(ct, ct2))
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+@
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+
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+
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+\begin{figure}[t!]
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+  Nonpolymorphic markers on chromosome X:
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+  \centering
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+<<nonpolymorphicX, fig=TRUE, width=8, height=4>>=
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+npx.index <- which(chromosome(cnSet)==23 & !isSnp(cnSet))
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+M <- sample(which(cnSet$gender==1), 5)
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+F <- sample(which(cnSet$gender==2), 5)
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+cn.M <- CA(cnSet, i=npx.index, j=M)
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+cn.F <- CA(cnSet, i=npx.index, j=F)
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+boxplot(data.frame(cbind(cn.M, cn.F)), pch=".", col="grey60", outline=FALSE)
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+@
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+\caption{Copy number estimates for nonpolymorphic loci on chromosome
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+  X (5 men, 5 women).  crlmm assumes that the median copy number
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+  across samples at a given marker on X is 1 for men and 2 for women.}
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+\end{figure}
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+
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-<<copynumberObject>>=
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-snp.index <- which(isSnp(cnSet))
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-cn <- totalCopynumber(cnSet, i=snp.index, j=1:10)
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-missing.snp <- which(rowSums(is.na(cn)) == 10) ##snps with no confidence
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-table(chromosome(cnSet)[missing.snp])
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-hist(i2p(snpCallProbability(cnSet)[missing.snp, 1:10]), breaks=100)
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-np.index <- which(!isSnp(cnSet))
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-ca <- CA(cnSet, i=np.index, j=1:10)
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-cb <- CB(cnSet, i=np.index, j=1:10) ## most are missing
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-cn <- totalCopynumber(cnSet, i=np.index, j=1:10)
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-missing.np <- which(rowSums(is.na(cn)) == 10)
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-table(chromosome(cnSet)[missing.np])
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-table(chromosome(cnSet)[np.index])
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+\begin{figure}[t!]
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+ \centering
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+<<polymorphicX, fig=TRUE, width=8, height=4>>=
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+## copy number estimates on X for SNPs are biased towards small values.
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+X.markers <- which(isSnp(cnSet) & chromosome(cnSet) == 23)
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+ca.M <- CA(cnSet, i=X.markers, j=M)
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+cb.M <- CB(cnSet, i=X.markers, j=M)
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+ca.F <- CA(cnSet, i=X.markers, j=F)
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+cb.F <- CB(cnSet, i=X.markers, j=F)
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+cn.M <- ca.M+cb.M
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+cn.F <- ca.F+cb.F
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+boxplot(data.frame(cbind(cn.M, cn.F)), pch=".", outline=FALSE, col="grey60")
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+cn2 <- totalCopynumber(cnSet, i=X.markers, j=c(M, F))
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+stopifnot(all.equal(cbind(cn.M, cn.F), cn2))
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+@
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+\caption{Copy number estimates for polymorphic markers on chromosome
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+  X. }
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+\end{figure}
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+Often it is of interest to smooth the total copy number estimates (the
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+sum of the allele-specific copy number) as a function of the physical
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+position.  The following code chunk can be used to create an instance
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+of \Robject{CopyNumberSet} that contains the CA + CB at polymorphic
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+markers and 'CA' at nonpolymorphic markers.
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+<<copynumberObject>>=
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 marker.index <- which(chromosome(cnSet) <= 22)## & isSnp(cnSet))
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 sample.index <- 1:5 ## first five samples
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 invisible(open(cnSet))
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@@ -332,7 +397,6 @@ for(j in 1:5){
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 }
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 @
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-
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 \section{Smoothing marker-level estimates of total copy number}
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 In this section, we show how the total copy number can be smoothed
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@@ -3,3 +3,4 @@ rsync -avuzb --exclude '*~' --exclude '.git*' -e ssh enigma2.jhsph.edu:~/madman/
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+