1. crlmm
  2. Commit 5fcfed7d5cf3853537486e60459fb322c955d2a1
Browse code

roll back to crlmm version 1.5.24

git-svn-id: file:///home/git/hedgehog.fhcrc.org/bioconductor/trunk/madman/Rpacks/crlmm@45126 bc3139a8-67e5-0310-9ffc-ced21a209358

Rob Scharp authored on 10/03/2010 01:27:04
Showing 36 changed files
CHANGES
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@@ -433,3 +433,9 @@ then readIDAT() should work. Thanks to Pierre Cherel who reported this error.
433 433 
 2010-03-08 M. Ritchie committed version 1.5.31
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  * removed a few unnecessary lines of code from crlmm-illumina.R (zero not needed as argument for preprocessInfinium2() and storageMode should not be "lockedEnvironment" in RGtoXY())
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  * added "humanomni1quadv1b" to validCdfName() in utils.R
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+
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+2010-03-08 R.Scharpf committed version 1.5.32
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+
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+**	   This is a roll back to version 1.5.24
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+
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+
DESCRIPTION
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@@ -1,39 +1,17 @@
1 1 
 Package: crlmm
2 2 
 Type: Package
3 3 
 Title: Genotype Calling (CRLMM) and Copy Number Analysis tool for Affymetrix SNP 5.0 and 6.0 and Illumina arrays.
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-Version: 1.5.31
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-Date: 2010-03-08
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-Author: Rafael A Irizarry, Benilton S Carvalho <carvalho@bclab.org>, Robert Scharpf <rscharpf@jhsph.edu>, Matt Ritchie <mritchie@wehi.edu.au>
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-Maintainer: Benilton S Carvalho <carvalho@bclab.org>, Robert Scharpf <rscharpf@jhsph.edu>, Matt Ritchie <mritchie@wehi.EDU.AU>
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+Version: 1.5.32
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+Date: 2010-02-05
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+Author: Rafael A Irizarry, Benilton S Carvalho <bcarvalh@jhsph.edu>, Robert Scharpf <rscharpf@jhsph.edu>, Matt Ritchie <mritchie@wehi.edu.au>
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+Maintainer: Benilton S Carvalho <bcarvalh@jhsph.edu>, Robert Scharpf <rscharpf@jhsph.edu>, Matt Ritchie <mritchie@wehi.EDU.AU>
8 8 
 Description: Faster implementation of CRLMM specific to SNP 5.0 and 6.0 arrays, as well as a copy number tool specific to 5.0, 6.0, and Illumina platforms
9 9 
 License: Artistic-2.0
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-Depends: R (>= 2.11.0),
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-         methods,
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-         Biobase (>= 2.7.2),
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-         oligoClasses (>= 1.9.28)
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-Imports: affyio (>= 1.15.2),
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-         preprocessCore,
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-         utils,
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-         stats,
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-         genefilter,
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-         splines,
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-         mvtnorm,
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-         ellipse,
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-         SNPchip,ff
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-Suggests: hapmapsnp5,
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-          hapmapsnp6,
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-          genomewidesnp5Crlmm (>= 1.0.2),
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-          genomewidesnp6Crlmm (>= 1.0.2),
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-          snpMatrix,
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-          metaArray
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-Collate: AllClasses.R
30 
-	 AllGenerics.R
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-	 methods-AffymetrixAlleleSet.R
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-	 methods-IlluminaAlleleSet.R
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-	 methods-CrlmmContainer.R
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+Depends: methods, Biobase (>= 2.7.2), R (>= 2.11.0), oligoClasses (>= 1.9.21)
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+Imports: affyio (>= 1.15.2), preprocessCore, utils, stats, genefilter, splines, mvtnorm, ellipse, SNPchip
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+Suggests: hapmapsnp5, hapmapsnp6, genomewidesnp5Crlmm (>= 1.0.2),genomewidesnp6Crlmm (>= 1.0.2), snpMatrix
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+Collate: AllGenerics.R
34 14 
 	 methods-CNSet.R
35 
-	 methods-AlleleSet.R
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-	 methods-CallSet.R
37 15 
 	 methods-eSet.R
38 16 
          methods-SnpSuperSet.R
39 17 
          cnrma-functions.R
NAMESPACE
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@@ -1,4 +1,3 @@
1 
-## crlmm NAMESPACE
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 useDynLib("crlmm", .registration=TRUE)
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4 3 
 ## Biobase
... ... 
@@ -8,12 +7,11 @@ importClassesFrom(Biobase, AnnotatedDataFrame, AssayData, eSet, SnpSet,
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 importMethodsFrom(Biobase, annotation, "annotation<-",
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                   annotatedDataFrameFrom, assayData, "assayData<-",
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-		  snpCallProbability,
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                   combine, dims, experimentData, "experimentData<-",
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                   fData, featureData, "featureData<-", featureNames,
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                   fvarMetadata, fvarLabels, pData, phenoData,
15 13 
                   "phenoData<-", protocolData, "protocolData<-",
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-                  pubMedIds, rowMedians, sampleNames, snpCall, storageMode,
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+                  pubMedIds, rowMedians, sampleNames, storageMode,
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                   "storageMode<-", updateObject, varLabels)
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 importFrom(Biobase, assayDataElement, assayDataElementNames,
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@@ -21,75 +19,44 @@ importFrom(Biobase, assayDataElement, assayDataElementNames,
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            validMsg)
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 ## oligoClasses
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-##importClassesFrom(oligoClasses, SnpSuperSet, AlleleSet, CNSet)
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+importClassesFrom(oligoClasses, SnpSuperSet, AlleleSet)
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26 
-##S3 method ffdf and class ffdf
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-importFrom(ff, ffdf, ff, as.ff, as.ffdf)
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+importMethodsFrom(oligoClasses, allele, calls, "calls<-", confs,
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+		  "confs<-", cnConfidence, "cnConfidence<-",
26 
+		  isSnp, chromosome, position, CA, "CA<-", CB, "CB<-")
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29 28
29 
+importFrom(oligoClasses, chromosome2integer, celfileDate, list.celfiles)
30 30
31 
-##importMethodsFrom(oligoClasses, allele, calls, "calls<-", confs,
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-##		  "confs<-", cnConfidence, "cnConfidence<-", isSnp,
33 
-##		  chromosome, position, CA, "CA<-", CB, "CB<-", A, B)
31 
+importFrom(oligoClasses, copyNumber)
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35 
-importFrom(oligoClasses, chromosome2integer, celfileDate, list.celfiles,
36 
-           copyNumber)
37 
-
38 
-## graphics
39 33 
 importFrom(graphics, abline, axis, layout, legend, mtext, par, plot,
40 34 
            polygon, rect, segments, text, points, boxplot)
41 35
42 
-## grDevices
43 36 
 importFrom(grDevices, grey)
44 37
45 
-## affyio
46 38 
 importFrom(affyio, read.celfile.header, read.celfile)
47 39
48 
-## preprocessCore
49 
-importFrom(preprocessCore, normalize.quantiles.use.target,
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-           normalize.quantiles)
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+importFrom(preprocessCore, normalize.quantiles.use.target, normalize.quantiles)
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-## utils
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-importFrom(utils, data, packageDescription, setTxtProgressBar,
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-           txtProgressBar)
42 
+importFrom(utils, data, packageDescription, setTxtProgressBar, txtProgressBar)
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56 
-## stats
57 
-importFrom(stats, coef, cov, dnorm, kmeans, lm, mad, median, quantile,
58 
-           sd, update)
44 
+importFrom(stats, coef, cov, dnorm, kmeans, lm, mad, median, quantile, sd, update)
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60 
-## genefilter
61 46 
 importFrom(genefilter, rowSds)
62 47
63 
-## mvtnorm
64 48 
 importFrom(mvtnorm, dmvnorm)
65 49
66 
-## ellipse
67 50 
 importFrom(ellipse, ellipse)
68 51
69 
-
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-##exportClasses(FFSet)
71 
-exportMethods(annotatedDataFrameFrom,
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-	copyNumber, initialize,
73 
-              ##show, "$", "[[", "[",
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-	      genomeAnnotation,
75 
-	      lM,
76 
-	      CA,
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-	      CB,
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-	      A,
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-	      B,
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-	      snpCall,
81 
-	      confs,
82 
-	      chromosome,
83 
-	      position,
84 
-	      isSnp)
85 
-export(crlmmOptions, crlmm, crlmmCopynumber, ellipse, readIdatFiles, snprma, getParam, validCdfNames)
86 
-
87 
-
88 
-
89 
-#############
90 
-## TO REMOVE
91 
-#############
92 
-
93 
-##export everything that does not start with a .
94 
-exportPattern("^[^\\.]")
95 
-
52 
+exportMethods(A, B, copyNumber)
53 
+export(cnOptions, crlmm, crlmmIllumina, crlmmCopynumber, ellipse, readIdatFiles, snprma, getParam)
54 
+
55 
+##export(##viterbi.CNSet, ##move to VanillaICE
56 
+##	combineIntensities,
57 
+##	whichPlatform,
58 
+##	isValidCdfName,
59 
+##	crlmmWrapper,
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+##        withinGenotypeMoments,
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+##	locationAndScale, getParam.SnpSuperSet)
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+export(thresholdModelParams, computeCopynumber.CNSet, nuphiAllele, coefs, biasAdjNP)
NEWS
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@@ -1,17 +1,3 @@
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-        **************************************************
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-        *                                                *
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-        *              1.5 SERIES NEWS                   *
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-        *                                                *
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-        **************************************************
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-
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-USER VISIBLE CHANGES
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-
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-NEW FEATURES
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-
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-	o Support to large datasets via ff package. The user
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-	must load the ff package manually to benefit from
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-	this.
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-
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         **************************************************
16 2 
         *                                                *
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         *              1.3 SERIES NEWS                   *
R/AllClasses.R
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deleted file mode 100644
... ... 
@@ -1,74 +0,0 @@
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-setOldClass("ffdf")
2 
-setOldClass("ff_matrix")
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-setClassUnion("matrix_or_ff", c("matrix", "ff_matrix"))
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-setClassUnion("list_or_ffdf", c("list", "ffdf"))
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-setClass("CrlmmContainer", contains="eSet",
6 
-	 representation(options="list",
7 
-			genomeAnnotation="ANY",
8 
-			"VIRTUAL"))
9 
-
10 
-setMethod("show", "CrlmmContainer", function(object){
11 
-	callNextMethod(object)
12 
-	cat("options: \n")
13 
-	print(names(crlmmOptions(object)))
14 
-	cat("\n")
15 
-	cat("genomeAnnotation:", nrow(genomeAnnotation(object)), " rows, ", ncol(genomeAnnotation(object)), " columns\n")
16 
-	print(genomeAnnotation(object)[1:5, ])
17 
-	cat("\n")
18 
-})
19 
-setClass("AlleleSet", contains="CrlmmContainer")
20 
-setClass("CallSet", contains="AlleleSet")
21 
-setClass("CNSet", contains="CallSet",
22 
-	 representation(lM="list_or_ffdf"))
23 
-
24 
-setClass("IlluminaRGSet", contains="CrlmmContainer")
25 
-setClass("IlluminaXYSet", contains="CrlmmContainer")
26 
-
27 
-setClass("AffymetrixAlleleSet", contains="AlleleSet")  ##AffymetrixAlleleSet
28 
-setClass("IlluminaAlleleSet", contains="AlleleSet")
29 
-##setClass("AffymetrixBigData", contains="AffymetrixAlleleSet")
30 
-##setClass("AffymetrixSmallData", contains="AffymetrixAlleleSet")
31 
-##setClass("IlluminaSmallData", contains="IlluminaAlleleSet")
32 
-##setClass("IlluminaBigData", contains="IlluminaAlleleSet")
33 
-##setMethod("initialize", "AffymetrixBigData", function(.Object, annotation){
34 
-##	.Object <- callNextMethod(.Object)
35 
-##	if(!missing(annotation)) annotation(.Object) <- annotation
36 
-##	.Object
37 
-##})
38 
-##setClass("AffymetrixCallSet", contains="CallSet")
39 
-##setClass("IlluminaCallSet", contains="CallSet")
40 
-setMethod("initialize", "AlleleSet", function(.Object, alleleA=new("matrix"), alleleB=new("matrix"), ...){
41 
-	.Object <- callNextMethod(.Object, alleleA=alleleA, alleleB=alleleB, ...)
42 
-	storageMode(.Object) <- "environment"
43 
-	.Object
44 
-})
45 
-setMethod("initialize", "CallSet", function(.Object, call=new("matrix"), callProbability=new("matrix"), ...){
46 
-	.Object <- callNextMethod(.Object, call=call, callProbability=callProbability, ...)
47 
-	storageMode(.Object) <- "environment"
48 
-	.Object
49 
-})
50 
-setMethod("initialize", "CNSet", function(.Object, CA=new("matrix"), CB=new("matrix"), lM=new("list"), ...){
51 
-	.Object <- callNextMethod(.Object, CA=CA, CB=CB, lM=lM,...)
52 
-	storageMode(.Object) <- "environment"
53 
-	.Object
54 
-})
55 
-setValidity("AlleleSet", function(object) {
56 
-	assayDataValidMembers(assayData(object), c("alleleA", "alleleB"))
57 
-})
58 
-setValidity("IlluminaRGSet", function(object) {
59 
-	assayDataValidMembers(assayData(object), c("R", "G", "zero"))
60 
-})
61 
-setValidity("IlluminaXYSet", function(object) {
62 
-	assayDataValidMembers(assayData(object), c("X", "Y", "zero"))
63 
-})
64 
-
65 
-setValidity("CallSet", function(object) {
66 
-	assayDataValidMembers(assayData(object), c("alleleA", "alleleB", "call", "callProbability"))
67 
-})
68 
-setValidity("CNSet", function(object) {
69 
-	assayDataValidMembers(assayData(object), c("alleleA", "alleleB", "call", "callProbability", "CA", "CB"))
70 
-})
71 
-
72 
-
73 
-
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-
R/AllGenerics.R
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@@ -1,57 +1,14 @@
1 
-setGeneric("A<-", function(object, value) standardGeneric("A<-"))
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-setGeneric("B<-", function(object, value) standardGeneric("B<-"))
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+setGeneric("A", function(object) standardGeneric("A"))
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+setGeneric("B", function(object) standardGeneric("B"))
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+##setGeneric("A<-", function(object, value) standardGeneric("A<-"))
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+##setGeneric("B<-", function(object, value) standardGeneric("B<-"))
3 5
4 
-setGeneric("getParam", function(object, name, ...) standardGeneric("getParam"))
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+setGeneric("getParam", function(object, name, batch) standardGeneric("getParam"))
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 setGeneric("cnIndex", function(object) standardGeneric("cnIndex"))
6 8 
 setGeneric("cnNames", function(object) standardGeneric("cnNames"))
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-setGeneric("confs", function(object) standardGeneric("confs"))
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-setGeneric("computeCopynumber", function(object) standardGeneric("computeCopynumber"))
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-setGeneric("crlmm", function(object, ...) standardGeneric("crlmm"))
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-setGeneric("crlmmOptions", function(object) standardGeneric("crlmmOptions"))
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-setGeneric("crlmmOptions<-", function(object, value) standardGeneric("crlmmOptions<-"))
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-setGeneric("construct", function(object, filenames) standardGeneric("construct"))
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-
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-setGeneric("getOptions", function(object) standardGeneric("getOptions"))
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-
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-##setGeneric("getA", function(object) standardGeneric("getA"))
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-##setGeneric("getB", function(object) standardGeneric("getB"))
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-##setGeneric("getG", function(object) standardGeneric("getG"))
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-##setGeneric("getR", function(object) standardGeneric("getR"))
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-##setGeneric("getZero", function(object) standardGeneric("getZero"))
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-##setGeneric("getCalls", function(object) standardGeneric("getCalls"))
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-##setGeneric("getConfs", function(object) standardGeneric("getConfs"))
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-##setGeneric("getCA", function(object) standardGeneric("getCA"))
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-##setGeneric("getCB", function(object) standardGeneric("getCB"))
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-setGeneric("getPhenoData", function(object) standardGeneric("getPhenoData"))
26 
-setGeneric("getFeatureData", function(object) standardGeneric("getFeatureData"))
27 
-setGeneric("getProtocolData", function(object, filenames) standardGeneric("getProtocolData"))
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-setGeneric("getGenomeAnnotation", function(object, ...) standardGeneric("getGenomeAnnotation"))
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-setGeneric("getLinearModelParam", function(object, ...) standardGeneric("getLinearModelParam"))
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-
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-##setGeneric("initializeStorage", function(object) standardGeneric("initializeStorage"))
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-setGeneric("prediction", function(x, ...) standardGeneric("prediction"))
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-setGeneric("genomeAnnotation", function(object) standardGeneric("genomeAnnotation"))
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-setGeneric("genomeAnnotation<-", function(object,value) standardGeneric("genomeAnnotation<-"))
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-setGeneric("lM", function(object) standardGeneric("lM"))
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-setGeneric("lM<-", function(object, value) standardGeneric("lM<-"))
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-
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-##setGeneric("nFeatures", function(object) standardGeneric("nFeatures"))
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-
9 
+setGeneric("computeCopynumber", function(object, cnOptions) standardGeneric("computeCopynumber"))
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 setGeneric("pr", function(object, name, batch, value) standardGeneric("pr"))
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-setGeneric("rma", function(object) standardGeneric("rma"))
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-setGeneric("snprma", function(object, ...) standardGeneric("snprma"))
43 11 
 setGeneric("snpIndex", function(object) standardGeneric("snpIndex"))
44 12 
 setGeneric("snpNames", function(object) standardGeneric("snpNames"))
45 13 
 ##setGeneric("splitByChromosome", function(object, ...) standardGeneric("splitByChromosome"))
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47 
-setGeneric("R", function(object) standardGeneric("R"))
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-setGeneric("G", function(object) standardGeneric("G"))
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-setGeneric("Z", function(object) standardGeneric("Z"))
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-setGeneric("X", function(object) standardGeneric("X"))
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-setGeneric("Y", function(object) standardGeneric("Y"))
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-setMethod("R", "IlluminaRGSet", function(object) assayDataElement(object, "R"))
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-setMethod("G", "IlluminaRGSet", function(object) assayDataElement(object, "G"))
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-setMethod("Z", "IlluminaRGSet", function(object) assayDataElement(object, "zero"))
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-setMethod("X", "IlluminaXYSet", function(object) assayDataElement(object, "X"))
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-setMethod("Y", "IlluminaXYSet", function(object) assayDataElement(object, "Y"))
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-setMethod("Z", "IlluminaXYSet", function(object) assayDataElement(object, "zero"))
R/cnrma-functions.R
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@@ -153,483 +153,337 @@ predictGender <- function(res, cdfName="genomewidesnp6", SNRMin=5){
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 	return(gender)
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 }
155 155
156 
-
157 
-##initializeFFObjects <- function(filenames, cnOptions){
158 
-##	outdir <- cnOptions[["outdir"]]
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-##	cdfName <- cnOptions[["cdfName"]]
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-##	AFile <- cnOptions[["AFile"]]
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-##	BFile <- cnOptions[["BFile"]]
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-##	callsFile <- cnOptions[["callsFile"]]
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-##	confsFile <- cnOptions[["confsFile"]]
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-##	snprmaFile <- cnOptions[["snprmaFile"]]
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-##	cnrmaFile <- cnOptions[["cnrmaFile"]]
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-##	CAFile <- cnOptions[["CAFile"]]
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-##	CBFile <- cnOptions[["CBFile"]]
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-##	load.it <- cnOptions[["load.it"]]
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-##	fileExists <- list(A=file.exists(AFile),
170 
-##			   B=file.exists(BFile),
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-##			   calls=file.exists(callsFile),
172 
-##			   confs=file.exists(confsFile),
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-##			   CA=file.exists(CAFile),
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-##			   CB=file.exists(CBFile))
175 
-##	allExists <- all(unlist(fileExists))
176 
-##	##if files already exist, check that the files have the appropriate dimension
177 
-##	if(allExists){
178 
-##		load(AFile)
179 
-##		open(A)
180 
-##		sns <- dimnames(A)[[2]]
181 
-##		if(!identical(sns, basename(filenames)) | !load.it){
182 
-##		## if not of the same dimension, clean up
183 
-##			message("Sample names in previously saved objects differ from the filenames. Removing previously saved objects.")
184 
-##			delete(A); gc()
185 
-##			unlink(AFile)
186 
-##			load(BFile); delete(B); unlink(BFile)
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-##			unlink(snprmaFile)
188 
-##			unlink(cnrmaFile)
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-##			if(file.exists(file.path(outdir, "cnParams.rda"))){
190 
-##				load(file.path(outdir, "cnParams.rda"))
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-##				delete(cnParams); gc()
192 
-##				unlink(file.path(outdir, "cnParams.rda"))
193 
-##			}
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-##			load(callsFile); delete(calls); unlink(callsFile)
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-##			load(confsFile); delete(confs); unlink(confsFile)
196 
-##			load(CAFile); delete(CA); unlink(CAFile)
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-##			load(CBFile); delete(CB); unlink(CBFile)
198 
-##			allExists <- FALSE
199 
-##		}
200 
-##	}
201 
-##	if(!allExists) 	{
202 
-##		message("Initializing ff objects for A, B, confs, calls, CA, and CB.")
203 
-##		dns <- .dimnames(filenames, cnOptions[["cdfName"]], cnOptions[["verbose"]])
204 
-##		fns <- dns[[1]]
205 
-##	}
206 
-##	if(!file.exists(AFile)) {A <- initializeBigMatrix(dns); save(A, file=AFile); close(A)}
207 
-##	if(!file.exists(BFile)) {B <- initializeBigMatrix(dns); save(B, file=BFile); close(B)}
208 
-##	if(!file.exists(confsFile)) {confs <- initializeBigMatrix(dns); save(confs, file=confsFile); close(confs)}
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-##	if(!file.exists(callsFile)) {calls <- initializeBigMatrix(dns); save(calls, file=callsFile); close(calls)}
210 
-##	if(!file.exists(CAFile)) {CA <- initializeBigMatrix(dns); save(CA, file=CAFile); close(CA)}
211 
-##	if(!file.exists(CBFile)) {CB <- initializeBigMatrix(dns); save(CB, file=CBFile); close(CB)}
212 
-##	featureDataFile <- file.path(outdir, "featureDataFF.rda")
213 
-##	if(!file.exists(featureDataFile)){
214 
-##		path <- system.file("extdata", package=paste(cnOptions[["cdfName"]], "Crlmm", sep=""))
215 
-##		load(file.path(path, "snpProbes.rda"))
216 
-##		snpProbes <- get("snpProbes")
217 
-##		load(file.path(path, "cnProbes.rda"))
218 
-##		cnProbes <- get("cnProbes")
219 
-##		message("Initializing featureDataFF.")
220 
-##		fvarlabels <- c("chromosome", "position",   "isSnp")
221 
-##		M <- matrix(NA, length(fns), 3, dimnames=list(fns, fvarlabels))
222 
-##		index <- match(rownames(snpProbes), rownames(M)) #only snp probes in M get assigned position
223 
-##		M[index, "position"] <- snpProbes[, grep("pos", colnames(snpProbes))]
224 
-##		M[index, "chromosome"] <- snpProbes[, grep("chr", colnames(snpProbes))]
225 
-##		M[index, "isSnp"] <- 1L
226 
-##		index <- match(rownames(cnProbes), rownames(M)) #only snp probes in M get assigned position
227 
-##		M[index, "position"] <- cnProbes[, grep("pos", colnames(cnProbes))]
228 
-##		M[index, "chromosome"] <- cnProbes[, grep("chr", colnames(cnProbes))]
229 
-##		M[index, "isSnp"] <- 0L
230 
-##		featureDataFF <- ff(M, dim=c(nrow(M), ncol(M)),
231 
-##				    vmode="integer", finalizer="close",
232 
-##				    overwrite=TRUE,
233 
-##				    dimnames=list(fns, fvarlabels))
234 
-##		save(featureDataFF, file=file.path(outdir, "featureDataFF.rda"))
235 
-##		close(featureDataFF)
236 
-##		rm(M, cnProbes, snpProbes, featureDataFF); gc()
237 
-##	}
238 
-##	## parameters file
239 
-##	parameterFile <- file.path(outdir, "cnParams.rda")
240 
-##	if(!file.exists(parameterFile)) {
241 
-##		message("Initializing parameters file")
242 
-##		batch <- cnOptions[["batch"]]
243 
-##		dns.batch <- list(fns, unique(batch))
244 
-##		cnParams <- initializeParamObject(dns.batch)
245 
-##		save(cnParams, file=file.path(outdir, "cnParams.rda"))
246 
-##		close(cnParams)
247 
-##	}
248 
-##}
249 
-
250 
-##preprocessAndGenotype <- function(filenames, cnOptions, ...){
251 
-##	set.seed(cnOptions[["seed"]])  ##for reproducibility
252 
-##	protocolFile <- cnOptions[["protocolFile"]]
253 
-##	cdfName <- cnOptions[["cdfName"]]
254 
-##	verbose <- cnOptions[["verbose"]]
255 
-##	if(file.exists(protocolFile)){
256 
-##		## check that file is the same dimension
257 
-##		load(protocolFile)
258 
-##		if(!identical(sampleNames(protocoldata), basename(filenames)))
259 
-##			unlink(protocolFile)
260 
-##	}
261 
-##	if(!file.exists(protocolFile)){
262 
-##		platform <- whichPlatform(paste(cdfName, "Crlmm", sep=""))
263 
-##		if(platform=="affymetrix"){
264 
-##			if(verbose) message("Creating protocol file with scan dates for the affy arrays")
265 
-##			scanDates <- data.frame(ScanDate=sapply(filenames, celfileDate))
266 
-##			rownames(scanDates) <- basename(rownames(scanDates))
267 
-##			protocoldata <- new("AnnotatedDataFrame",
268 
-##					    data=scanDates,
269 
-##					    varMetadata=data.frame(labelDescription=colnames(scanDates),
270 
-##					    row.names=colnames(scanDates)))
271 
-##			save(protocoldata, file=protocolFile)
272 
-##		}
273 
-##		## protocol file for illumina saved during the readIdatFile step
274 
-##	}
275 
-##	if(isPackageLoaded("ff")) initializeFFObjects(filenames, cnOptions)
276 
-##	crlmmWrapper(filenames, cnOptions, ...)
277 
-##	message("Checking for required files...")
278 
-##	message(cnOptions[["AFile"]], ": ", file.exists(cnOptions[["AFile"]]))
279 
-##	message(cnOptions[["BFile"]], ": ", file.exists(cnOptions[["BFile"]]))
280 
-##	message(cnOptions[["callsFile"]], ": ", file.exists(cnOptions[["callsFile"]]))
281 
-##	message(cnOptions[["confsFile"]], ": ", file.exists(cnOptions[["confsFile"]]))
282 
-##	message(cnOptions[["snprmaFile"]], ": ", file.exists(cnOptions[["snprmaFile"]]))
283 
-##	message(cnOptions[["protocolFile"]], ": ", file.exists(cnOptions[["protocolFile"]]))
284 
-##}
156 
+combineIntensities <- function(res, NP=NULL, callSet){
157 
+	rownames(res$B) <- rownames(res$A) <- res$gns
158 
+	colnames(res$B) <- colnames(res$A) <- res$sns
159 
+	if(!is.null(NP)){
160 
+		blank <- matrix(NA, nrow(NP), ncol(NP))
161 
+		dimnames(blank) <- dimnames(NP)
162 
+		A <- rbind(res$A, NP)
163 
+		B <- rbind(res$B, blank)
164 
+	} else {
165 
+		A <- res$A
166 
+		B <- res$B
167 
+	}
168 
+	dimnames(B) <- dimnames(A)
169 
+	index.snps <- match(res$gns, rownames(A))
170 
+	callsConfs <- calls <- matrix(NA, nrow(A), ncol(A), dimnames=dimnames(A))
285 171
286 
-##crlmmCopynumber <- function(cnOptions, ...){
287 
-##crlmmCopynumber <- function(object){
288 
-##	ops <- crlmmOptions(object)
289 
-##	verbose <- ops$verbose
290 
-##	calls <- snpCall(object)
291 
-##	confs <- confs(object)
292 
-##	fns <- featureNames(object)
293 
-##	SNRmin <- ops$SNRMin
294 
-##	batch <- object$batch
295 
-##	whichBatch <- ops$cnOpts$whichBatch
296 
-##	chromosome <- ops$cnOpts$chromosome
297 
-##	MIN.SAMPLES <- ops$cnOpts$MIN.SAMPLES
298 
-##	##k <- grep("chr", colnames(snpProbes))
299 
-##	for(CHR in chromosome){
300 
-##		##annotated snp and cn probes
301 
-##		##snps <- rownames(snpProbes)[snpProbes[, k] == CHR]
302 
-##		##cns <- rownames(cnProbes)[cnProbes[, k] == CHR]
303 
-##		##where are the annotated snps in the fns file
304 
-##		##index.snps <- match(snps, fns)
305 
-##		##index.cn <- match(cns, fns)
306 
-##		##row.index <- c(index.snps, index.cn)
307 
-##		cat("Chromosome ", CHR, "\n")
308 
-##		for(i in whichBatch){
309 
-##			PLATE <- unique(batch)[i]
310 
-##			message("Plate: ", PLATE)
311 
-##			sample.index <- which(batch==PLATE)
312 
-##			if(length(sample.index) < MIN.SAMPLES) {
313 
-##				warning("Plate ", PLATE, " has fewer than 10 samples.  Skipping this plate.")
314 
-##				next()
315 
-##			}
316 
-##			##cnOptions[["batch"]] <- cnOptions[["batch"]][snpI[["SNR"]]  >= SNRmin]
317 
-####			if(isPackageLoaded("ff")){
318 
-####				ca <- as.matrix(CA[row.index, sample.index])
319 
-####				cb <- as.matrix(CB[row.index, sample.index])
320 
-####			} else{
321 
-####				dns <- dimnames(A[row.index, sample.index])
322 
-####				cb <- ca <- matrix(NA, nr=length(row.index), nc=length(sample.index), dimnames=dns)
323 
-####			}
324 
-####			cnSet <- new("CNSet",
325 
-####				     alleleA=as.matrix(A[row.index, sample.index]),
326 
-####				     alleleB=as.matrix(B[row.index, sample.index]),
327 
-####				     call=as.matrix(calls[row.index, sample.index]),
328 
-####				     callProbability=as.matrix(confs[row.index, sample.index]),
329 
-####				     CA=ca,
330 
-####				     CB=cb,
331 
-####				     featureData=annotatedDataFrameFrom(as.matrix(A[row.index, sample.index]), byrow=TRUE),
332 
-####				     phenoData=pD[sample.index, ],
333 
-####				     protocolData=protocoldata[sample.index, ])
334 
-##			##Verify this is correct
335 
-####			annotation(cnSet) <- cnOptions[["cdfName"]]
336 
-####			featureNames(cnSet) <- fns[row.index]
337 
-##			##add chromosome, position, isSnp
338 
-####			cnSet <- annotate(cnSet)
339 
-####			if(any(cnSet$SNR > SNRmin)){
340 
-####				if(CHR == chromosome[1]) message(paste("Excluding samples with SNR < ", SNRmin))
341 
-####				cnSet <- cnSet[, cnSet$SNR >= SNRmin]
342 
-####			}
343 
-####			featureData(cnSet) <- lm.parameters(cnSet, cnOptions)
344 
-##			if(CHR > 23) next()
345 
-##			cnSet <- computeCopynumber(object[chromosome(object) == CHR, sample.index])
346 
-####			if(!isPackageLoaded("ff") & i == whichBatch[1]) cnParams <- initializeParamObject(list(featureNames(cnSet), unique(cnOptions[["batch"]])[whichBatch]))
347 
-####			if(!isPackageLoaded("ff")) {
348 
-####				row.index <- 1:nrow(cnSet)
349 
-####			} else {
350 
-####				##Warning message:
351 
-####				##In d[[1]] * d[[2]] : NAs produced by integer overflow
352 
-####				CA[row.index, sample.index] <- cnSet@assayData[["CA"]]
353 
-####				CB[row.index, sample.index] <- cnSet@assayData[["CB"]]
354 
-####			}
355 
-####			cnParams <- updateParams(cnParams, cnSet, row.index, batch=unique(batch)[i])
356 
-##			## keep only chromosome, position, and isSnp
357 
-####			featureData(cnSet) <- featureData(cnSet)[, 1:3]
358 
-####			if(!isPackageLoaded("ff")){
359 
-####				save(cnSet, file=paste(cnFile, "_", PLATE, "_", CHR, ".rda", sep=""))
360 
-####				save(cnParams, file=paste(outdir, "cnParams_", PLATE, "_", CHR, ".rda", sep=""))
361 
-####			}
362 
-##		} ## end of batch loop
363 
-##	} ## end of chromosome loop
364 
-####	if(isPackageLoaded("ff")) {
365 
-####		close(cnParams)
366 
-####		close(A); close(B)
367 
-####		close(CA); close(CB)
368 
-####		save(CA, file=CAFile)
369 
-####		save(CB, file=CBFile)
370 
-####		close(calls); close(confs)
371 
-####		return()
372 
-####	}
373 
-##	return(cnSet)
374 
-##}
375 
-
376 
-
377 
-
172 
+	calls[index.snps, ] <- calls(callSet)
173 
+	callsConfs[index.snps, ] <- assayData(callSet)[["callProbability"]]
174 
+	fd <- data.frame(matrix(NA, nrow(calls), length(fvarLabels(callSet))))
175 
+	fd[index.snps, ] <- fData(callSet)
176 
+	rownames(fd) <- rownames(A)
177 
+	colnames(fd) <- fvarLabels(callSet)
178 
+	fD <- new("AnnotatedDataFrame",
179 
+		  data=data.frame(fd),
180 
+		  varMetadata=data.frame(labelDescription=colnames(fd), row.names=colnames(fd)))
181 
+	superSet <- new("CNSet",
182 
+			CA=matrix(NA, nrow(A), ncol(A), dimnames=dimnames(A)),
183 
+			CB=matrix(NA, nrow(A), ncol(A), dimnames=dimnames(A)),
184 
+			alleleA=A,
185 
+			alleleB=B,
186 
+			call=calls,
187 
+			callProbability=callsConfs,
188 
+			featureData=fD,
189 
+			phenoData=phenoData(callSet),
190 
+			experimentData=experimentData(callSet),
191 
+			protocolData=protocolData(callSet),
192 
+			annotation=annotation(callSet))
193 
+	return(superSet)
194 
+}
378 195
196 
+harmonizeDimnamesTo <- function(object1, object2){
197 
+	#object2 should be a subset of object 1
198 
+	object2 <- object2[featureNames(object2) %in% featureNames(object1), ]
199 
+	object1 <- object1[match(featureNames(object2), featureNames(object1)), ]
200 
+	object1 <- object1[, match(sampleNames(object2), sampleNames(object1))]
201 
+	stopifnot(all.equal(featureNames(object1), featureNames(object2)))
202 
+	stopifnot(all.equal(sampleNames(object1), sampleNames(object2)))
203 
+	return(object1)
204 
+}
379 205
206 
+crlmmCopynumber <- function(filenames, cnOptions, object, ...){
207 
+	if(!missing(object)){
208 
+		stopifnot(class(object) == "CNSet")
209 
+		createIntermediateObjects <- FALSE
210 
+	} else {
211 
+		createIntermediateObjects <- TRUE
212 
+		crlmmResults <- crlmmWrapper(filenames, cnOptions, ...)
213 
+		snprmaResult <- crlmmResults[["snprmaResult"]]
214 
+		cnrmaResult <- crlmmResults[["cnrmaResult"]]
215 
+		callSet <- crlmmResults[["callSet"]]
216 
+		rm(crlmmResults); gc()
217 
+		annotation(callSet) <- cnOptions[["cdfName"]]
218 
+		stopifnot(identical(featureNames(callSet), snprmaResult[["gns"]]))
219 
+		path <- system.file("extdata", package=paste(annotation(callSet), "Crlmm", sep=""))
220 
+		load(file.path(path, "snpProbes.rda"))
221 
+		snpProbes <- get("snpProbes")
222 
+		load(file.path(path, "cnProbes.rda"))
223 
+		cnProbes <- get("cnProbes")
224 
+		k <- grep("chr", colnames(snpProbes))
225 
+		if(length(k) < 1) stop("chr or chromosome not in colnames(snpProbes)")
226 
+	}
227 
+	set.seed(cnOptions[["seed"]])  ##for reproducibility
228 
+	chromosome <- cnOptions[["chromosome"]]
229 
+	SNRmin <- cnOptions[["SNRmin"]]
230 
+	for(CHR in chromosome){
231 
+		cat("Chromosome ", CHR, "\n")
232 
+		if(createIntermediateObjects){
233 
+			snps <- rownames(snpProbes)[snpProbes[, k] == CHR]
234 
+			cnps <- rownames(cnProbes)[cnProbes[, k] == CHR]
235 
+			index.snps <- match(snps, featureNames(callSet))
236 
+			index.nps <- match(cnps, rownames(cnrmaResult[["NP"]]))
237 
+			if(!is.null(cnrmaResult)){
238 
+				npI <- cnrmaResult$NP[index.nps, ]
239 
+			} else npI <- NULL
240 
+			snpI <- list(A=snprmaResult$A[index.snps, ],
241 
+				     B=snprmaResult$B[index.snps, ],
242 
+				     sns=snprmaResult$sns,
243 
+				     gns=snprmaResult$gns[index.snps],
244 
+				     SNR=snprmaResult$SNR,
245 
+				     SKW=snprmaResult$SKW,
246 
+				     mixtureParams=snprmaResult$mixtureParams,
247 
+				     cdfName=snprmaResult$cdfName)
248 
+			cnOptions[["batch"]] <- cnOptions[["batch"]][snpI[["SNR"]]  >= SNRmin]
249 
+			cnSet <- combineIntensities(res=snpI,
250 
+						    NP=npI,
251 
+						    callSet=callSet[index.snps, ])
252 
+			if(any(cnSet$SNR > SNRmin)){
253 
+				message(paste("Excluding samples with SNR < ", SNRmin))
254 
+				cnSet <- cnSet[, cnSet$SNR >= SNRmin]
255 
+			}
256 
+			rm(snpI, npI, snps, cnps, index.snps, index.nps); gc()
257 
+			pData(cnSet)$batch <- cnOptions[["batch"]]
258 
+			featureData(cnSet) <- lm.parameters(cnSet, cnOptions)
259 
+		} else {
260 
+			cnSet <- object
261 
+		}
262 
+		if(CHR != 24){
263 
+			cnSet <- computeCopynumber(cnSet, cnOptions)
264 
+		} else{
265 
+			message("Copy number estimates not available for chromosome Y.  Saving only the 'callSet' object for this chromosome")
266 
+			alleleSet <- cnSet
267 
+			save(alleleSet, file=file.path(cnOptions[["outdir"]], paste("alleleSet_", CHR, ".rda", sep="")))
268 
+			rm(cnSet, alleleSet); gc()
269 
+			next()
270 
+		}
271 
+		if(length(chromosome) == 1){
272 
+			if(cnOptions[["save.cnset"]]){
273 
+				save(cnSet, file=file.path(cnOptions[["outdir"]], paste("cnSet_", CHR, ".rda", sep="")))
274 
+			}
275 
+		}
276 
+		if(length(chromosome) > 1){
277 
+			save(cnSet, file=file.path(cnOptions[["outdir"]], paste("cnSet_", CHR, ".rda", sep="")))
278 
+			rm(cnSet); gc()
279 
+		} else {
280 
+			return(cnSet)
281 
+		}
282 
+	}
283 
+	saved.objects <- list.files(cnOptions[["outdir"]], pattern="cnSet", full.names=TRUE)
284 
+	return(saved.objects)
285 
+}
380 286
381 287
382 
-##loadIlluminaRG <- function(rgFile, crlmmFile, load.it, save.it,...){
383 
-####	if(missing(rgFile)){
384 
-####		##stop("must specify 'rgFile'.")
385 
-####		rgFile <- file.path(dirname(crlmmFile), "rgFile.rda")
386 
-####		message("rgFile not specified.  Using ", rgFile)
387 
-####	}
388 
-##	if(!load.it){
389 
-##		RG <- readIdatFiles(...)
390 
-##		if(save.it) save(RG, file=rgFile)
391 
-##	}
392 
-##	if(load.it & !file.exists(rgFile)){
393 
-##		message("load.it is TRUE, but rgFile not present.  Attempting to read the idatFiles.")
394 
-##		RG <- readIdatFiles(...)
395 
-##		if(save.it) save(RG, file=rgFile)
396 
-##	}
397 
-##	if(load.it & file.exists(rgFile)){
398 
-##		message("Loading RG file")
399 
-##		load(rgFile)
400 
-##		RG <- get("RG")
401 
-##	}
402 
-##	return(RG)
403 
-##}
404 
-##
405 
-##loadIlluminaCallSet <- function(crlmmFile, snprmaFile, RG, load.it, save.it, cdfName){
406 
-##	if(!file.exists(crlmmFile) | !load.it){
407 
-##		callSet <- crlmmIllumina(RG=RG,
408 
-##					 cdfName=cdfName,
409 
-##					 sns=sampleNames(RG),
410 
-##					 returnParams=TRUE,
411 
-##					 save.it=TRUE,
412 
-##					 intensityFile=snprmaFile)
413 
-##		if(save.it) save(callSet, file=crlmmFile)
414 
-##	} else {
415 
-##		message("Loading ", crlmmFile, "...")
416 
-##		load(crlmmFile)
417 
-##		callSet <- get("callSet")
418 
-##	}
419 
-##	protocolData(callSet) <- protocolData(RG)
420 
-##	return(callSet)
421 
-##}
422 288
289 
+crlmmWrapper <- function(filenames, cnOptions, ...){
290 
+	cdfName <- cnOptions[["cdfName"]]
291 
+	load.it <- cnOptions[["load.it"]]
292 
+	save.it <- cnOptions[["save.it"]]
293 
+	splitByChr <- cnOptions[["splitByChr"]]
294 
+	crlmmFile <- cnOptions[["crlmmFile"]]
295 
+	intensityFile=cnOptions[["intensityFile"]]
296 
+	rgFile=cnOptions[["rgFile"]]
297 
+	##use.ff=cnOptions[["use.ff"]]
298 
+	outdir <- cnOptions[["outdir"]]
299 
+	if(missing(cdfName)) stop("cdfName is missing -- a valid cdfName is required.  See crlmm:::validCdfNames()")
300 
+	platform <- whichPlatform(cdfName)
301 
+	if(!(platform %in% c("affymetrix", "illumina"))){
302 
+		stop("Only 'affymetrix' and 'illumina' platforms are supported at this time.")
303 
+	} else {
304 
+		message("Checking whether annotation package for the ", platform, " platform is available")
305 
+		if(!isValidCdfName(cdfName)){
306 
+			cat("FALSE\n")
307 
+			stop(cdfName, " is not a valid entry.  See crlmm:::validCdfNames(platform)")
308 
+		} else cat("TRUE\n")
309 
+	}
310 
+	if(missing(intensityFile)) stop("must specify 'intensityFile'.")
311 
+	if(missing(crlmmFile)) stop("must specify 'crlmmFile'.")
312 
+	if(platform == "illumina"){
313 
+		if(missing(rgFile)){
314 
+			##stop("must specify 'rgFile'.")
315 
+			rgFile <- file.path(dirname(crlmmFile), "rgFile.rda")
316 
+			message("rgFile not specified.  Using ", rgFile)
317 
+		}
318 
+		if(!load.it){
319 
+			RG <- readIdatFiles(...)
320 
+			if(save.it) save(RG, file=rgFile)
321 
+		}
322 
+		if(load.it & !file.exists(rgFile)){
323 
+			message("load.it is TRUE, but rgFile not present.  Attempting to read the idatFiles.")
324 
+			RG <- readIdatFiles(...)
325 
+			if(save.it) save(RG, file=rgFile)
326 
+		}
327 
+		if(load.it & file.exists(rgFile)){
328 
+			message("Loading RG file")
329 
+			load(rgFile)
330 
+			RG <- get("RG")
331 
+		}
332 
+	}
333 
+	if(!(file.exists(dirname(crlmmFile)))) stop(dirname(crlmmFile), " does not exist.")
334 
+	if(!(file.exists(dirname(intensityFile)))) stop(dirname(intensityFile), " does not exist.")
335 
+	##---------------------------------------------------------------------------
336 
+	## FIX
337 
+	outfiles <- file.path(dirname(crlmmFile), paste("crlmmSetList_", 1:24, ".rda", sep=""))
338 
+	if(load.it & all(file.exists(outfiles))){
339 
+		load(outfiles[1])
340 
+		crlmmSetList <- get("crlmmSetList")
341 
+		if(!all(sampleNames(crlmmSetList) == basename(filenames))){
342 
+			stop("load.it is TRUE, but sampleNames(crlmmSetList != basename(filenames))")
343 
+		} else{
344 
+			return("load.it is TRUE and 'crlmmSetList_<CHR>.rda' objects found. Nothing to do...")
345 
+		}
346 
+	}
347 
+	if(load.it){
348 
+		if(!file.exists(crlmmFile)){
349 
+			message("load.it is TRUE, but ", crlmmFile, " does not exist.  Rerunning the genotype calling algorithm")
350 
+			load.it <- FALSE
351 
+		}
352 
+	}
353 
+	if(platform == "affymetrix"){
354 
+		if(!file.exists(crlmmFile) | !load.it){
355 
+			callSet <- crlmm(filenames=filenames,
356 
+					     cdfName=cdfName,
357 
+					     save.it=TRUE,
358 
+					     load.it=load.it,
359 
+					     intensityFile=intensityFile)
360 
+			message("Quantile normalizing the copy number probes...")
361 
+			cnrmaResult <- cnrma(filenames=filenames, cdfName=cdfName, outdir=outdir)
362 
+			if(save.it){
363 
+				message("Saving callSet and cnrmaResult to", crlmmFile)
364 
+				save(callSet, cnrmaResult, file=crlmmFile)
365 
+			}
366 
+		} else {
367 
+			message("Loading ", crlmmFile, "...")
368 
+			load(intensityFile)
369 
+			load(crlmmFile)
370 
+			callSet <- get("callSet")
371 
+			cnrmaResult <- get("cnrmaResult")
372 
+		}
373 
+		scanDates <- data.frame(ScanDate=sapply(filenames, celfileDate))
374 
+		protocolData(callSet) <- new("AnnotatedDataFrame",
375 
+					     data=scanDates,
376 
+					     varMetadata=data.frame(labelDescription=colnames(scanDates),
377 
+					     row.names=colnames(scanDates)))
378 
+	}
379 
+	if(platform == "illumina"){
380 
+		if(!file.exists(crlmmFile) | !load.it){
381 
+			callSet <- crlmmIllumina(RG=RG,
382 
+						 cdfName=cdfName,
383 
+						 sns=sampleNames(RG),
384 
+						 returnParams=TRUE,
385 
+						 save.it=TRUE,
386 
+						 intensityFile=intensityFile)
387 
+			if(save.it) save(callSet, file=crlmmFile)
388 
+		} else {
389 
+			message("Loading ", crlmmFile, "...")
390 
+			load(crlmmFile)
391 
+			callSet <- get("callSet")
392 
+		}
393 
+		protocolData(callSet) <- protocolData(RG)
394 
+	}
395 
+	if(platform=="affymetrix") {
396 
+		protocolData(callSet)[["ScanDate"]] <- as.character(celDates(filenames))
397 
+		sampleNames(protocolData(callSet)) <- sampleNames(callSet)
398 
+	}
399 
+	load(intensityFile)
400 
+	snprmaResult <- get("res")
401 
+	if(platform=="illumina"){
402 
+		if(exists("cnAB")){
403 
+			np.A <- as.integer(cnAB$A)
404 
+			np.B <- as.integer(cnAB$B)
405 
+			np <- ifelse(np.A > np.B, np.A, np.B)
406 
+			np <- matrix(np, nrow(cnAB$A), ncol(cnAB$A))
407 
+			rownames(np) <- cnAB$gns
408 
+			colnames(np) <- cnAB$sns
409 
+			cnAB$NP <- np
410 
+			##sampleNames(callSet) <- res$sns
411 
+			sampleNames(callSet) <- cnAB$sns
412 
+			cnrmaResult <- get("cnAB")
413 
+		} else cnrmaResult <- NULL
414 
+	}
415 
+	if(platform=="affymetrix"){
416 
+		if(exists("cnrmaResult")){
417 
+			cnrmaResult <- get("cnrmaResult")
418 
+		} else cnrmaResult <- NULL
419 
+	}
420 
+	crlmmResults <- list(snprmaResult=snprmaResult,
421 
+			     cnrmaResult=cnrmaResult,
422 
+			     callSet=callSet)
423 423
424 
-##loadAffyCallSet <- function(filenames, confsFile, callsFile, snprmaFile, load.it, save.it,  cdfName){
425 
-##
426 
-####		if(save.it){
427 
-####			message("Saving callSet to", callsFile)
428 
-####			##save(callSet, cnrmaResult, file=callsFile)
429 
-####			save(callSet, file=callsFile)
430 
-####		}
431 
-####	} else {
432 
-####		message("Loading ", callsFile, "...")
433 
-####		##load(snprmaFile)
434 
-####		load(callsFile)
435 
-####		callSet <- get("callSet")
436 
-####		##cnrmaResult <- get("cnrmaResult")
437 
-####	}
438 
-##
439 
-##}
440 
-##	if(platform=="affymetrix") {
441 
-##		protocolData(callSet)[["ScanDate"]] <- as.character(celDates(filenames))
442 
-##		sampleNames(protocolData(callSet)) <- sampleNames(callSet)
443 
-##	}
424 
+	if(!save.it){
425 
+		message("Cleaning up")
426 
+		unlink(intensityFile)
427 
+	}
428 
+	return(crlmmResults)
429 
+}
444 430
445 
-##loadAffyCnrma <- function(filenames, cnrmaFile, cdfName, outdir, load.it, save.it, use.bigmemory=FALSE){
446 
-##	if(!file.exists(cnrmaFile) | !load.it){
447 
-##		message("Quantile normalizing the copy number probes...")
448 
-##		cnrmaResult <- cnrma2(filenames=filenames, cdfName=cdfName, outdir=outdir, cnrmaFile=cnrmaFile)
449 
-##	} else cnrmaResult <- attach.big.matrix("NP.desc", outdir)
450 
-##	return(cnrmaResult)
451 
-##}
431 
+validCdfNames <- function(){
432 
+	c("genomewidesnp6",
433 
+	  "genomewidesnp5",
434 
+	  "human370v1c",
435 
+	  "human370quadv3c",
436 
+	  "human550v3b",
437 
+	  "human650v3a",
438 
+	  "human610quadv1b",
439 
+	  "human660quadv1a",
440 
+	  "human1mduov3b")
441 
+}
452 442
453 
-##loadIlluminaCnrma <- function(){
454 
-##	if(exists("cnAB")){
455 
-##		np.A <- as.integer(cnAB$A)
456 
-##		np.B <- as.integer(cnAB$B)
457 
-##		np <- ifelse(np.A > np.B, np.A, np.B)
458 
-##		np <- matrix(np, nrow(cnAB$A), ncol(cnAB$A))
459 
-##		rownames(np) <- cnAB$gns
460 
-##		colnames(np) <- cnAB$sns
461 
-##		cnAB$NP <- np
462 
-##		##sampleNames(callSet) <- res$sns
463 
-##		sampleNames(callSet) <- cnAB$sns
464 
-##		cnrmaResult <- get("cnAB")
465 
-##	} else cnrmaResult <- NULL
466 
-##	return(cnrmaResult)
467 
-##}
468 
-##
469 
-##crlmmWrapper <- function(filenames, cnOptions, ...){
470 
-##	crlmmBatchSize <- cnOptions[["crlmmBatchSize"]]
471 
-##	cdfName <- cnOptions[["cdfName"]]
472 
-##	load.it <- cnOptions[["load.it"]]
473 
-##	save.it <- cnOptions[["save.it"]]
474 
-##	callsFile <- cnOptions[["callsFile"]]
475 
-##	confsFile <- cnOptions[["confsFile"]]
476 
-##	AFile=cnOptions[["AFile"]]
477 
-##	BFile=cnOptions[["BFile"]]
478 
-##	snprmaFile=cnOptions[["snprmaFile"]]
479 
-##	cnrmaFile=cnOptions[["cnrmaFile"]]
480 
-##	rgFile=cnOptions[["rgFile"]]
481 
-##	protocolFile <- cnOptions[["protocolFile"]]
482 
-##	outdir <- cnOptions[["outdir"]]
483 
-##	if(missing(cdfName)) stop("cdfName is missing -- a valid cdfName is required.  See crlmm:::validCdfNames()")
484 
-##	platform <- whichPlatform(cdfName)
485 
-##	if(!(platform %in% c("affymetrix", "illumina"))){
486 
-##		stop("Only 'affymetrix' and 'illumina' platforms are supported at this time.")
487 
-##	} else {
488 
-##		if(!isValidCdfName(cdfName)){
489 
-##			stop(cdfName, " is not a valid entry.  See crlmm:::validCdfNames(platform)")
490 
-##		} else  message("Using the annotation package ", cdfName, " for this ", platform, " platform")
491 
-##	}
492 
-##	if(platform == "illumina") {
493 
-##		if(!file.exists(rgFile)){
494 
-##			if(load.it) message(rgFile, " does not exist and you chose to load.it.  Re-reading the R and G intensities from the IDAT files")
495 
-##			sampleSheet <- cnOptions$sampleSheet
496 
-##			ids <- cnOptions$ids
497 
-##			arrayInfoColNames <- cnOptions$arrayInfoColNames
498 
-##			highDensity <- cnOptions$highDensity
499 
-##			##this is either an NChannelSet object, or a list of pointers to the ff objects
500 
-##			RG <- readIdatFiles(sampleSheet=sampleSheet,
501 
-##					    arrayNames=basename(filenames),
502 
-##					    ids=ids,
503 
-##					    path=dirname(filenames),
504 
-##					    highDensity=highDensity,
505 
-##					    fileExt=cnOptions$fileExt[1:2],
506 
-##					    sep=cnOptions$fileExt[[3]],
507 
-##					    saveDate=FALSE,  ## I do this earlier
508 
-##					    verbose=cnOptions[["verbose"]],
509 
-##					    protocolFile=protocolFile)
510 
-##			if(save.it) save(RG, file=rgFile)
511 
-##			##RG <- loadIlluminaRG(rgFile, callsFile, load.it, save.it)
512 
-##		} else{
513 
-##			if(!isPackageLoaded("ff")) {load(rgFile); RG <- get("RG")}
514 
-##		}
515 
-##	}
516 
-##	if(!(file.exists(dirname(callsFile)))) stop(dirname(callsFile), " does not exist.")
517 
-##	if(!(file.exists(dirname(snprmaFile)))) stop(dirname(snprmaFile), " does not exist.")
518 
-##	if(platform == "affymetrix"){
519 
-##		crlmm(filenames=filenames,
520 
-##		      cdfName=cdfName,
521 
-##		      save.it=TRUE,
522 
-##		      load.it=load.it,
523 
-##		      snprmaFile=snprmaFile,
524 
-##		      callsFile=callsFile,
525 
-##		      confsFile=confsFile,
526 
-##		      AFile=AFile,
527 
-##		      BFile=BFile,
528 
-##		      crlmmBatchSize=crlmmBatchSize,
529 
-##		      SNRMin=cnOptions[["SNRMin"]])
530 
-##	}
531 
-##	gc()
532 
-##	if(platform == "illumina") {
533 
-##		callSet <- crlmmIllumina(RG=RG,
534 
-##					 cdfName=cdfName,
535 
-##					 sns=sampleNames(RG),
536 
-##					 returnParams=TRUE,
537 
-##					 save.it=TRUE,
538 
-##					 snprmaFile=snprmaFile,
539 
-##					 callsFile=callsFile,
540 
-##					 confsFile=confsFile,
541 
-##					 AFile=AFile,
542 
-##					 BFile=BFile)
543 
-##		##callSet <- loadIlluminaCallSet(callsFile, snprmaFile, RG, load.it, save.it, cdfName)
544 
-##	}
545 
-##	if(platform == "affymetrix"){
546 
-##		if(!file.exists(cnrmaFile) | !load.it){
547 
-##			message("Quantile normalizing the copy number probes...")
548 
-##			## updates A matrix and saves cnrmaFile
549 
-##			cnrma(filenames=filenames, cdfName=cdfName, outdir=outdir, verbose=cnOptions[["verbose"]], cnrmaFile=cnrmaFile, AFile=AFile, snprmaFile=snprmaFile)
550 
-##		}
551 
-##	}
552 
-####	if(!is.null(cnrmaResult)){
553 
-####		for(CHR in chromosome){
554 
-####			cat(CHR, " ")
555 
-####			cnps <- rownames(cnProbes)[cnProbes[, k] == CHR]
556 
-####			index.nps <- match(cnps, rownames(cnrmaResult[["NP"]]))
557 
-####			NP <- cnrmaResult$NP[index.nps, ]
558 
-####			save(NP, file=file.path(tmpdir, paste("NP_", CHR, ".rda", sep="")))
559 
-####			rm(NP); gc()
560 
-####		}
561 
-####	}
562 
-##	if(!save.it){
563 
-##		message("Cleaning up")
564 
-##		unlink(snprmaFile); unlink(cnrmaFile)
565 
-##	}
566 
-##}
443 
+isValidCdfName <- function(cdfName){
444 
+	chipList <- validCdfNames()
445 
+	result <- cdfName %in% chipList
446 
+	if(!(result)){
447 
+		warning("cdfName must be one of the following: ",
448 
+			chipList)
449 
+	}
450 
+	return(result)
451 
+}
567 452
453 
+whichPlatform <- function(cdfName){
454 
+	index <- grep("genomewidesnp", cdfName)
455 
+	if(length(index) > 0){
456 
+		platform <- "affymetrix"
457 
+	} else{
458 
+		index <- grep("human", cdfName)
459 
+		platform <- "illumina"
460 
+	}
461 
+	return(platform)
462 
+}
568 463
569 464
570 465 
 # steps: quantile normalize hapmap: create 1m_reference_cn.rda object
571 
-##cnrma <- function(filenames, cdfName, sns, seed=1, verbose=FALSE, outdir){
572 
-##	if(missing(cdfName)) stop("must specify cdfName")
573 
-##	pkgname <- getCrlmmAnnotationName(cdfName)
574 
-##	require(pkgname, character.only=TRUE) || stop("Package ", pkgname, " not available")
575 
-##	if (missing(sns)) sns <- basename(filenames)
576 
-##        loader("npProbesFid.rda", .crlmmPkgEnv, pkgname)
577 
-##	fid <- getVarInEnv("npProbesFid")
578 
-##	set.seed(seed)
579 
-##	idx2 <- sample(length(fid), 10^5) ##for skewness. no need to do everything
580 
-##	SKW <- vector("numeric", length(filenames))
581 
-##
582 
-##
583 
-##	NP <- matrix(NA, length(fid), length(filenames))
584 
-##	verbose <- TRUE
585 
-##	if(verbose){
586 
-##		message("Processing ", length(filenames), " files.")
587 
-##		if (getRversion() > '2.7.0') pb <- txtProgressBar(min=0, max=length(filenames), style=3)
588 
-##	}
589 
-##	if(cdfName=="genomewidesnp6"){
590 
-##		loader("1m_reference_cn.rda", .crlmmPkgEnv, pkgname)
591 
-##	}
592 
-##	if(cdfName=="genomewidesnp5"){
593 
-##		loader("5.0_reference_cn.rda", .crlmmPkgEnv, pkgname)
594 
-##	}
595 
-##	reference <- getVarInEnv("reference")
596 
-##	##if(!is.matrix(reference)) stop("target distribution for quantile normalization not available.")
597 
-##	for(i in seq(along=filenames)){
598 
-##		y <- as.matrix(read.celfile(filenames[i], intensity.means.only=TRUE)[["INTENSITY"]][["MEAN"]][fid])
599 
-##		x <- log2(y[idx2])
600 
-##		SKW[i] <- mean((x-mean(x))^3)/(sd(x)^3)
601 
-##		rm(x)
602 
-##		NP[, i] <- as.integer(normalize.quantiles.use.target(y, target=reference))
603 
-##		if (verbose)
604 
-##			if (getRversion() > '2.7.0') setTxtProgressBar(pb, i)
605 
-##			else cat(".")
606 
-##	}
607 
-##	dimnames(NP) <- list(names(fid), sns)
608 
-##	##dimnames(NP) <- list(map[, "man_fsetid"], sns)
609 
-##	res3 <- list(NP=NP, SKW=SKW)
610 
-##	cat("\n")
611 
-##	return(res3)
612 
-##}
613 
-
614 
-cnrma <- function(object, filenames){
615 
-	ops <- crlmmOptions(object)
616 
-	cdfName <- annotation(object)
617 
-	seed <- ops$seed
618 
-	verbose <- ops$verbose
619 
-	##cnrmaFile <- ops$cnrmaFile
620 
-	A <- A(object)
466 
+cnrma <- function(filenames, cdfName, sns, seed=1, verbose=FALSE, outdir){
621 467 
 	if(missing(cdfName)) stop("must specify cdfName")
622 468 
 	pkgname <- getCrlmmAnnotationName(cdfName)
623 469 
 	require(pkgname, character.only=TRUE) || stop("Package ", pkgname, " not available")
624 
-	sns <- basename(filenames)
470 
+	if (missing(sns)) sns <- basename(filenames)
625 471 
         loader("npProbesFid.rda", .crlmmPkgEnv, pkgname)
626 472 
 	fid <- getVarInEnv("npProbesFid")
627 473 
 	set.seed(seed)
628 474 
 	idx2 <- sample(length(fid), 10^5) ##for skewness. no need to do everything
629 475 
 	SKW <- vector("numeric", length(filenames))
630 
-	index <- match(names(fid), featureNames(object))
631 
-	stopifnot(identical(featureNames(object)[index], names(fid)))
632 
-	if(length(index) < 1) stop("None of the names for the nonpolymorphic probes in the annotation package match the names stored in the snprmaFile.")
476 
+##	if(bigmemory){
477 
+##		NP <- filebacked.big.matrix(length(pnsa), length(filenames),
478 
+##					    type="integer",
479 
+##					    init=as.integer(0),
480 
+##					    backingpath=outdir,
481 
+##					    backingfile="NP.bin",
482 
+##					    descriptorfile="NP.desc")
483 
+##	} else{
484 
+		NP <- matrix(NA, length(fid), length(filenames))
485 
+##	}
486 
+	verbose <- TRUE
633 487 
 	if(verbose){
634 488 
 		message("Processing ", length(filenames), " files.")
635 489 
 		if (getRversion() > '2.7.0') pb <- txtProgressBar(min=0, max=length(filenames), style=3)
... ... 
@@ -641,21 +495,22 @@ cnrma <- function(object, filenames){
641 495 
 		loader("5.0_reference_cn.rda", .crlmmPkgEnv, pkgname)
642 496 
 	}
643 497 
 	reference <- getVarInEnv("reference")
498 
+	##if(!is.matrix(reference)) stop("target distribution for quantile normalization not available.")
644 499 
 	for(i in seq(along=filenames)){
645 500 
 		y <- as.matrix(read.celfile(filenames[i], intensity.means.only=TRUE)[["INTENSITY"]][["MEAN"]][fid])
646 501 
 		x <- log2(y[idx2])
647 502 
 		SKW[i] <- mean((x-mean(x))^3)/(sd(x)^3)
648 
-		rm(x); gc()
649 
-		A[index, i] <- as.integer(normalize.quantiles.use.target(y, target=reference))
503 
+		rm(x)
504 
+		NP[, i] <- as.integer(normalize.quantiles.use.target(y, target=reference))
650 505 
 		if (verbose)
651 506 
 			if (getRversion() > '2.7.0') setTxtProgressBar(pb, i)
652 507 
 			else cat(".")
653 
-		rm(y); gc()
654 508 
 	}
655 
-	cat("\nDone\n")
656 
-	pData(object)$SKW_nonpolymorphic <- SKW
657 
-	object@assayData[["alleleA"]] <- A
658 
-	return(object)
509 
+	dimnames(NP) <- list(names(fid), sns)
510 
+	##dimnames(NP) <- list(map[, "man_fsetid"], sns)
511 
+	res3 <- list(NP=NP, SKW=SKW)
512 
+	cat("\n")
513 
+	return(res3)
659 514 
 }
660 515
661 516 
 getFlags <- function(object, PHI.THR){
... ... 
@@ -673,7 +528,7 @@ getFlags <- function(object, PHI.THR){
673 528 
 }
674 529
675 530
676 
-instantiateObjects <- function(object){
531 
+instantiateObjects <- function(object, cnOptions){
677 532 
 	Ns <- matrix(NA, nrow(object), 5)
678 533 
 	colnames(Ns) <- c("A", "B", "AA", "AB", "BB")
679 534 
 	vA <- vB <- muB <- muA <- Ns
... ... 
@@ -700,46 +555,130 @@ thresholdCopynumber <- function(object){
700 555 
 	return(object)
701 556 
 }
702 557
703 
-##linear model parameters
704 
-##lm.parameters <- function(object, cnOptions){
705 
-##	fD <- fData(object)
706 
-##	batch <- object$batch
707 
-##	uplate <- unique(batch)
708 
-##	parameterNames <- c(paste("tau2A", uplate, sep="_"),
709 
-##			    paste("tau2B", uplate, sep="_"),
710 
-##			    paste("sig2A", uplate, sep="_"),
711 
-##			    paste("sig2B", uplate, sep="_"),
712 
-##			    paste("nuA", uplate, sep="_"),
713 
-##			    paste("nuA.se", uplate, sep="_"),
714 
-##			    paste("nuB", uplate, sep="_"),
715 
-##			    paste("nuB.se", uplate, sep="_"),
716 
-##			    paste("phiA", uplate, sep="_"),
717 
-##			    paste("phiA.se", uplate, sep="_"),
718 
-##			    paste("phiB", uplate, sep="_"),
719 
-##			    paste("phiB.se", uplate, sep="_"),
720 
-##			    paste("phiAX", uplate, sep="_"),
721 
-##			    paste("phiBX", uplate, sep="_"),
722 
-##			    paste("corr", uplate, sep="_"),
723 
-##			    paste("corrA.BB", uplate, sep="_"),
724 
-##			    paste("corrB.AA", uplate, sep="_"))
725 
-##	pMatrix <- data.frame(matrix(numeric(0),
726 
-##				     nrow(object),
727 
-##				     length(parameterNames)),
728 
-##				     row.names=featureNames(object))
729 
-##	colnames(pMatrix) <- parameterNames
730 
-##	fD2 <- cbind(fD, pMatrix)
731 
-##	new("AnnotatedDataFrame", data=fD2,
732 
-##	    varMetadata=data.frame(labelDescription=colnames(fD2),
733 
-##	    row.names=colnames(fD2)))
558 
+##preprocessOptions <- function(crlmmFile="snpsetObject.rda",
559 
+##			      intensityFile="normalizedIntensities.rda",
560 
+##			      rgFile="rgFile.rda"){
561 
+##
734 562 
 ##}
735 563
564 
+cnOptions <- function(outdir="./",
565 
+		      cdfName,
566 
+		      crlmmFile,
567 
+		      intensityFile,
568 
+		      rgFile="rgFile.rda",
569 
+		      save.it=TRUE,
570 
+		      save.cnset=TRUE,
571 
+		      load.it=TRUE,
572 
+		      splitByChr=TRUE,
573 
+		      MIN.OBS=3,
574 
+		      MIN.SAMPLES=10,
575 
+		      batch=NULL,
576 
+		      DF.PRIOR=50,
577 
+		      bias.adj=FALSE,
578 
+		      prior.prob=rep(1/4, 4),
579 
+		      SNRmin=4,
580 
+		      chromosome=1:24,
581 
+		      seed=123,
582 
+		      verbose=TRUE,
583 
+		      GT.CONF.THR=0.99,
584 
+		      PHI.THR=2^6,##used in nonpolymorphic fxn for training
585 
+		      nHOM.THR=5, ##used in nonpolymorphic fxn for training
586 
+		      MIN.NU=2^3,
587 
+		      MIN.PHI=2^3,
588 
+		      THR.NU.PHI=TRUE,
589 
+		      thresholdCopynumber=TRUE,
590 
+		      unlink=TRUE,
591 
+		      ##hiddenMarkovModel=FALSE,
592 
+		      ##circularBinarySegmentation=FALSE,
593 
+##		      cbsOpts=NULL,
594 
+		      ##hmmOpts=NULL,
595 
+		      ...){
596 
+	if(missing(cdfName)) stop("must specify cdfName")
597 
+	if(!file.exists(outdir)){
598 
+		message(outdir, " does not exist.  Trying to create it.")
599 
+		dir.create(outdir, recursive=TRUE)
600 
+	}
601 
+	stopifnot(isValidCdfName(cdfName))
602 
+##	if(hiddenMarkovModel){
603 
+##		hmmOpts <- hmmOptions(...)
604 
+##	}
605 
+	if(missing(crlmmFile)){
606 
+		crlmmFile <- file.path(outdir, "snpsetObject.rda")
607 
+	}
608 
+	if(missing(intensityFile)){
609 
+		intensityFile <- file.path(outdir, "normalizedIntensities.rda")
610 
+	}
611 
+	if(is.null(batch))
612 
+		stop("must specify batch -- should be the same length as the number of files")
613 
+	list(outdir=outdir,
614 
+	     cdfName=cdfName,
615 
+	     crlmmFile=crlmmFile,
616 
+	     intensityFile=intensityFile,
617 
+	     rgFile=file.path(outdir, rgFile),
618 
+	     save.it=save.it,
619 
+	     save.cnset=save.cnset,
620 
+	     load.it=load.it,
621 
+	     splitByChr=splitByChr,
622 
+	     MIN.OBS=MIN.OBS,
623 
+	     MIN.SAMPLES=MIN.SAMPLES,
624 
+	     batch=batch,
625 
+	     DF.PRIOR=DF.PRIOR,
626 
+	     GT.CONF.THR=GT.CONF.THR,
627 
+	     prior.prob=prior.prob,
628 
+	     bias.adj=bias.adj,
629 
+	     SNRmin=SNRmin,
630 
+	     chromosome=chromosome,
631 
+	     seed=seed,
632 
+	     verbose=verbose,
633 
+	     PHI.THR=PHI.THR,
634 
+	     nHOM.THR=nHOM.THR,
635 
+	     MIN.NU=MIN.NU,
636 
+	     MIN.PHI=MIN.PHI,
637 
+	     THR.NU.PHI=THR.NU.PHI,
638 
+	     thresholdCopynumber=thresholdCopynumber,
639 
+	     unlink=unlink)
640 
+##	     hiddenMarkovModel=hiddenMarkovModel,
641 
+##	     circularBinarySegmentation=circularBinarySegmentation,
642 
+##	     cbsOpts=cbsOpts,
643 
+##	     hmmOpts=hmmOpts) ##remove SnpSuperSet object
644 
+}
645 
+
646 
+##linear model parameters
647 
+lm.parameters <- function(object, cnOptions){
648 
+	fD <- fData(object)
649 
+	batch <- object$batch
650 
+	uplate <- unique(batch)
651 
+	parameterNames <- c(paste("tau2A", uplate, sep="_"),
652 
+			    paste("tau2B", uplate, sep="_"),
653 
+			    paste("sig2A", uplate, sep="_"),
654 
+			    paste("sig2B", uplate, sep="_"),
655 
+			    paste("nuA", uplate, sep="_"),
656 
+			    paste("nuA.se", uplate, sep="_"),
657 
+			    paste("nuB", uplate, sep="_"),
658 
+			    paste("nuB.se", uplate, sep="_"),
659 
+			    paste("phiA", uplate, sep="_"),
660 
+			    paste("phiA.se", uplate, sep="_"),
661 
+			    paste("phiB", uplate, sep="_"),
662 
+			    paste("phiB.se", uplate, sep="_"),
663 
+			    paste("phiAX", uplate, sep="_"),
664 
+			    paste("phiBX", uplate, sep="_"),
665 
+			    paste("corr", uplate, sep="_"),
666 
+			    paste("corrA.BB", uplate, sep="_"),
667 
+			    paste("corrB.AA", uplate, sep="_"))
668 
+	pMatrix <- data.frame(matrix(numeric(0),
669 
+				     nrow(object),
670 
+				     length(parameterNames)),
671 
+				     row.names=featureNames(object))
672 
+	colnames(pMatrix) <- parameterNames
673 
+	fD2 <- cbind(fD, pMatrix)
674 
+	new("AnnotatedDataFrame", data=fD2,
675 
+	    varMetadata=data.frame(labelDescription=colnames(fD2),
676 
+	    row.names=colnames(fD2)))
677 
+}
678 
+
736 679 
 nonpolymorphic <- function(object, cnOptions, tmp.objects){
737 
-	chromosome <- cnOptions[["chromosome"]]
738 680 
 	batch <- unique(object$batch)
739 681 
 	CHR <- unique(chromosome(object))
740 
-	verbose <- cnOptions[["verbose"]]
741 
-	if(CHR != chromosome[1]) verbose <- FALSE
742 
-	if(batch != unique(cnOptions[["batch"]])[1]) verbose <- FALSE
743 682 
 	goodSnps <- function(object, PHI.THR, tmp.objects, nAA.THR, nBB.THR){
744 683 
 		Ns <- tmp.objects[["Ns"]]
745 684 
 		##Ns <- get("Ns", envir)
... ... 
@@ -865,9 +804,10 @@ nonpolymorphic <- function(object, cnOptions, tmp.objects){
865 804
866 805 
 		THR.NU.PHI <- cnOptions$THR.NU.PHI
867 806 
 		if(THR.NU.PHI){
807 
+			verbose <- cnOptions$verbose
868 808 
 			##Assign values to object
869 809 
 			object <- pr(object, "nuA", batch, nuA)
870 
-			object <- pr(object, "phiA", batch, phiA)
810 
+			object <- pr(object, "phiA", batch, phiA)
871 811 
 			if(verbose) message("Thresholding nu and phi")
872 812 
 			object <- thresholdModelParams(object, cnOptions)
873 813 
 		} else {
... ... 
@@ -885,6 +825,7 @@ nonpolymorphic <- function(object, cnOptions, tmp.objects){
885 825
886 826 
 		THR.NU.PHI <- cnOptions$THR.NU.PHI
887 827 
 		if(THR.NU.PHI){
828 
+			verbose <- cnOptions$verbose
888 829 
 			##Assign values to object
889 830 
 			object <- pr(object, "nuA", batch, nuA)
890 831 
 			object <- pr(object, "phiA", batch, phiA)
... ... 
@@ -905,27 +846,6 @@ nonpolymorphic <- function(object, cnOptions, tmp.objects){
905 846 
 	return(object)
906 847 
 }
907 848
908 
-nonpolymorphic.poe <- function(object, cnOptions, tmp.object){
909 
-	require(metaArray)
910 
-	nps <- log2(A(object)[!isSnp(object), ])
911 
-	nps <- (nps-rowMedians(nps))/rowMAD(nps)
912 
-	runAvg <- apply(nps, 2, myfilter, filter=rep(1/10, 10))
913 
-	rownames(runAvg) <- featureNames(object)[!isSnp(object)]
914 
-	rm.nas <- rowSums(is.na(runAvg)) == 0
915 
-	runAvg <- runAvg[rm.nas, ]
916 
-
917 
-	poe.scale <- poe.em(runAvg, cl=rep(0, ncol(nps)))$data
918 
-	pinegg <- piposg <- poe.scale
919 
-	piposg[piposg < 0] <- 0
920 
-	pinegg[pinegg > 0] <- 0
921 
-	pinegg <- pinegg*-1
922 
-	pm.em <- 1*pinegg + 2*(1-pinegg-piposg) + 3*piposg
923 
-	rownames(pm.em) <- rownames(runAvg)
924 
-	CA(object)[match(rownames(pm.em), featureNames(object)), ] <- pm.em
925 
-	##CA(object)[!isSnp(object), ] <- pm.em
926 
-	return(object)
927 
-}
928 
-
929 849 
 ##sufficient statistics on the intensity scale
930 850 
 withinGenotypeMoments <- function(object, cnOptions, tmp.objects){
931 851 
 	normal <- tmp.objects[["normal"]]
... ... 
@@ -1018,12 +938,12 @@ withinGenotypeMoments <- function(object, cnOptions, tmp.objects){
1018 938 
 	return(tmp.objects)
1019 939 
 }