Browse code

numerous changes to the code and class definitions used for copy number estimation

git-svn-id: file:///home/git/hedgehog.fhcrc.org/bioconductor/trunk/madman/Rpacks/crlmm@43010 bc3139a8-67e5-0310-9ffc-ced21a209358

Rob Scharp authored on 15/11/2009 10:46:23
Showing23 changed files

... ...
@@ -312,3 +312,11 @@ is decoded and scanned
312 312
 2009-11-14 B Carvalho - committed version 1.5.2
313 313
 
314 314
  * code cleanup - removed unneeded C code
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+
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+2009-11-15 R. Scharpf - committed version 1.5.3
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+
318
+ * numerous changes to the copy number estimation
319
+ - ABset and CrlmmSetList classes are gone. Using SnpCallSetPlus and CrlmmSet
320
+ - Added class SegmentSet that extends CrlmmSet directly.
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+
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+
... ...
@@ -1,15 +1,15 @@
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.
4
-Version: 1.5.1
5
-Date: 2009-10-25
4
+Version: 1.5.3
5
+Date: 2009-11-15
6 6
 Author: Rafael A Irizarry, Benilton S Carvalho <bcarvalh@jhsph.edu>, Robert Scharpf <rscharpf@jhsph.edu>, Matt Ritchie <mritchie@wehi.EDU.AU>
7 7
 Maintainer: Benilton S Carvalho <bcarvalh@jhsph.edu>, Robert Scharpf <rscharpf@jhsph.edu>, Matt Ritchie <mritchie@wehi.EDU.AU>
8
-Description: Faster implementation of CRLMM specific to SNP 5.0 and 6.0 arrays, as well as a copy number tool specific to 6.0.
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
10 10
 Depends: methods, Biobase (>= 2.5.5), R (>= 2.10.0)
11
-Imports: affyio, preprocessCore, utils, stats, genefilter, splines, mvtnorm, oligoClasses, ellipse, methods, SNPchip
12
-Suggests: hapmapsnp5, hapmapsnp6, genomewidesnp5Crlmm (>= 1.0.2),genomewidesnp6Crlmm (>= 1.0.2), snpMatrix, VanillaICE (>= 1.7.8), GGdata
11
+Imports: affyio, preprocessCore, utils, stats, genefilter, splines, mvtnorm, oligoClasses, ellipse, methods, SNPchip, oligoClasses, VanillaICE (>= 1.9.1)
12
+Suggests: hapmapsnp5, hapmapsnp6, genomewidesnp5Crlmm (>= 1.0.2),genomewidesnp6Crlmm (>= 1.0.2), snpMatrix, GGdata
13 13
 Collate: AllClasses.R
14 14
 	 AllGenerics.R
15 15
 	 methods-ABset.R
... ...
@@ -1,11 +1,7 @@
1
-## Class definition
2
-setClass("ABset", contains="eSet",
3
-	 prototype = prototype(
4
-	 new("VersionedBiobase",
5
-	     versions=c(classVersion("eSet"), SnpSet="1.0.0"))))
6
-setClass("crlmmSet", contains="eSet")
7
-setClass("CrlmmSetList", contains="list")
8
-setClass("CopyNumberSet", contains="eSet",
9
-	 prototype = prototype(
10
-	 new("VersionedBiobase",
11
-	     versions=c(classVersion("eSet"), SnpSet="1.0.0"))))
1
+setClass("CopyNumberSet", contains="SnpLevelSet")
2
+setClass("CrlmmSet", contains=c("SnpCallSetPlus", "CopyNumberSet"))
3
+setClass("SnpCallSetPlusFF", contains="SnpCallSetPlus")
4
+setClass("CrlmmSetFF", contains="CrlmmSet")
5
+setClass("SegmentSet", contains="CrlmmSet",
6
+	 representation(emissionPr="array",
7
+			segmentData="data.frame"))
... ...
@@ -3,20 +3,27 @@ setGeneric("B", function(object) standardGeneric("B"))
3 3
 setGeneric("A<-", function(object, value) standardGeneric("A<-"))
4 4
 setGeneric("addFeatureAnnotation", function(object, ...) standardGeneric("addFeatureAnnotation"))
5 5
 setGeneric("B<-", function(object, value) standardGeneric("B<-"))
6
-setGeneric("batch", function(object) standardGeneric("batch"))
7
-##setGeneric("calls", function(x) standardGeneric("calls"))
8 6
 setGeneric("confs", function(object) standardGeneric("confs"))
9
-setGeneric("CA", function(object, ...) standardGeneric("CA"))
10
-setGeneric("CB", function(object, ...) standardGeneric("CB"))
7
+setGeneric("CA", function(object) standardGeneric("CA"))
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+setGeneric("CB", function(object) standardGeneric("CB"))
11 9
 setGeneric("CA<-", function(object, value) standardGeneric("CA<-"))
12 10
 setGeneric("CB<-", function(object, value) standardGeneric("CB<-"))
13
-##setGeneric("chromosome", function(object) standardGeneric("chromosome"))
14
-setGeneric("cnIndex", function(object, ...) standardGeneric("cnIndex"))
15
-setGeneric("cnNames", function(object, ...) standardGeneric("cnNames"))
16
-##setGeneric("copyNumber", function(object) standardGeneric("copyNumber"))
17
-##setGeneric("position", function(object) standardGeneric("position"))
11
+setGeneric("emissionPr", function(object) standardGeneric("emissionPr"))
12
+setGeneric("emissionPr<-", function(object, value) standardGeneric("emissionPr<-"))
13
+setGeneric("getParam", function(object, name, batch) standardGeneric("getParam"))
14
+setGeneric("GT<-", function(object, value) standardGeneric("GT<-"))
15
+setGeneric("cnIndex", function(object) standardGeneric("cnIndex"))
16
+setGeneric("cnNames", function(object) standardGeneric("cnNames"))
17
+setGeneric("computeCopynumber", function(object, cnOptions) standardGeneric("computeCopynumber"))
18
+setGeneric("computeEmission", function(object, hmmOptions) standardGeneric("computeEmission"))
19
+setGeneric("computeHmm", function(object, hmmOptions) standardGeneric("computeHmm"))
20
+setGeneric("confs<-", function(object, value) standardGeneric("confs<-"))
21
+setGeneric("GT", function(object, ...) standardGeneric("GT"))
18 22
 setGeneric(".harmonizeDimnames", function(object) standardGeneric(".harmonizeDimnames"))
19
-setGeneric("snpIndex", function(object, ...) standardGeneric("snpIndex"))
20
-setGeneric("snpNames", function(object, ...) standardGeneric("snpNames"))
23
+setGeneric("isSnp", function(object) standardGeneric("isSnp"))
24
+setGeneric("pr", function(object, name, batch, value) standardGeneric("pr"))
25
+setGeneric("segmentData", function(object) standardGeneric("segmentData"))
26
+setGeneric("segmentData<-", function(object, value) standardGeneric("segmentData<-"))
27
+setGeneric("snpIndex", function(object) standardGeneric("snpIndex"))
28
+setGeneric("snpNames", function(object) standardGeneric("snpNames"))
21 29
 setGeneric("splitByChromosome", function(object, ...) standardGeneric("splitByChromosome"))
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-
23 30
deleted file mode 100644
... ...
@@ -1,18 +0,0 @@
1
-setValidity("ABset", function(object) {
2
-	##msg <- validMsg(NULL, Biobase:::isValidVersion(object, "CopyNumberSet"))
3
-	msg <- validMsg(NULL, assayDataValidMembers(assayData(object), c("A", "B")))
4
-	if (is.null(msg)) TRUE else msg
5
-})
6
-setMethod("A", "ABset", function(object) assayData(object)[["A"]])
7
-setMethod("B", "ABset", function(object) assayData(object)[["B"]])
8
-setReplaceMethod("A", signature(object="ABset", value="matrix"),
9
-		 function(object, value){
10
-			 assayDataElementReplace(object, "A", value)			
11
-		 })
12
-setReplaceMethod("B", signature(object="ABset", value="matrix"),
13
-		 function(object, value){
14
-			 assayDataElementReplace(object, "B", value)			
15
-		 })
16
-
17
-
18
-
... ...
@@ -3,49 +3,26 @@ setValidity("CopyNumberSet", function(object) {
3 3
 	if (is.null(msg)) TRUE else msg
4 4
 })
5 5
 ##may want to allow thresholding here (... arg)
6
-setMethod("CA", "CopyNumberSet", function(object, ...) assayData(object)[["CA"]]/100)
7
-setMethod("CB", "CopyNumberSet", function(object, ...) assayData(object)[["CB"]]/100)
8
-
9
-setReplaceMethod("CA", signature(object="CopyNumberSet", value="matrix"), function(object, value){
10
-	dns <- dimnames(value)
11
-	value <- matrix(as.integer(value*100), nrow(value), ncol(value))
12
-	dimnames(value) <- dns
13
-	assayDataElementReplace(object, "CA", value)
14
-})
15
-
16
-setReplaceMethod("CB", signature(object="CopyNumberSet", value="matrix"), function(object, value){
17
-	dns <- dimnames(value)	
18
-	value <- matrix(as.integer(value*100), nrow(value), ncol(value))
19
-	dimnames(value) <- dns	
20
-	assayDataElementReplace(object, "CB", value)
21
-})
22
-
6
+setMethod("CA", "CopyNumberSet", function(object) assayData(object)[["CA"]]/100)
7
+setMethod("CB", "CopyNumberSet", function(object) assayData(object)[["CB"]]/100)
23 8
 
9
+setReplaceMethod("CA", signature(object="CopyNumberSet", value="matrix"),
10
+		 function(object, value){
11
+			 assayDataElementReplace(object, "CA", value)		
12
+		 })
24 13
 
25
-
26
-setMethod("batch", "CopyNumberSet", function(object){
27
-	if("batch" %in% varLabels(object)){
28
-		result <- object$batch
29
-	} else {
30
-		stop("batch not in varLabels of CopyNumberSet")
31
-	}
32
-	return(result)
33
-})
14
+setReplaceMethod("CB", signature(object="CopyNumberSet", value="matrix"),
15
+		 function(object, value){
16
+			 assayDataElementReplace(object, "CB", value)
17
+		 })
34 18
 
35 19
 setMethod("copyNumber", "CopyNumberSet", function(object){
36
-	require(paste(annotation(object), "Crlmm", sep=""), character.only=TRUE) || stop(paste("Annotation package ", annotation(object), "Crlmm not available", sep=""))
37
-	##ensure that 2 + NA = 2 by replacing NA's with zero
38
-	##the above results in copy number 0, 1, or 2 depending on the genotype....safer just to drop
20
+	I <- isSnp(object)
39 21
 	CA <- CA(object)
40 22
 	CB <- CB(object)
41
-	##nas <- is.na(CA) & is.na(CB)
42
-	##CA[is.na(CA)] <- 0
43
-	##CB[is.na(CB)] <- 0
44 23
 	CN <- CA + CB
45 24
 	##For nonpolymorphic probes, CA is the total copy number
46
-	CN[cnIndex(object, annotation(object)), ] <- CA(object)[cnIndex(object, annotation(object)), ]
47
-	##if both CA and CB are NA, report NA
48
-	##CN[nas] <- NA
25
+	CN[!I, ] <- CA(object)[!I, ]
49 26
 	CN
50 27
 })
51 28
 
... ...
@@ -98,3 +75,5 @@ ellipse.CopyNumberSet <- function(x, copynumber, ...){
98 75
 
99 76
 
100 77
 
78
+
79
+
101 80
new file mode 100644
... ...
@@ -0,0 +1,298 @@
1
+setMethod("initialize", "CrlmmSet",
2
+          function(.Object,
3
+                   phenoData,
4
+		   featureData,
5
+		   annotation,
6
+		   experimentData,
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+		   protocolData,
8
+                   calls=new("matrix"),
9
+                   callsConfidence=new("matrix"),
10
+                   senseThetaA=new("matrix"),
11
+                   senseThetaB=new("matrix"),
12
+		   CA=new("matrix"),
13
+		   CB=new("matrix"), ... ){
14
+		  ad <- assayDataNew("lockedEnvironment",
15
+				     calls=calls,
16
+				     callsConfidence=callsConfidence,
17
+				     senseThetaA=senseThetaA,
18
+				     senseThetaB=senseThetaB,
19
+				     CA=CA,
20
+				     CB=CB)
21
+		  assayData(.Object) <- ad
22
+		  if (missing(phenoData)){
23
+			  phenoData(.Object) <- annotatedDataFrameFrom(calls, byrow=FALSE)
24
+		  } else phenoData(.Object) <- phenoData
25
+		  if (missing(featureData)){
26
+			  featureData(.Object) <- annotatedDataFrameFrom(calls, byrow=TRUE)
27
+		  } else featureData(.Object) <- featureData
28
+		  if(!missing(annotation)) annotation(.Object) <- annotation
29
+		  if(!missing(experimentData)) experimentData(.Object) <- experimentData
30
+		  if(!missing(protocolData)) protocolData(.Object) <- protocolData
31
+		  .Object	    
32
+          })
33
+
34
+setAs("SnpCallSetPlus", "CrlmmSet",
35
+      function(from, to){
36
+	      CA <- CB <- matrix(NA, nrow(from), ncol(from))
37
+	      dimnames(CA) <- dimnames(CB) <- list(featureNames(from), sampleNames(from))		  
38
+	      new("CrlmmSet",
39
+		  calls=calls(from),
40
+		  callsConfidence=callsConfidence(from),
41
+		  senseThetaA=A(from),
42
+		  senseThetaB=B(from),
43
+		  CA=CA,
44
+		  CB=CB,
45
+		  phenoData=phenoData(from),
46
+		  experimentData=experimentData(from),
47
+		  annotation=annotation(from),
48
+		  protocolData=protocolData(from),
49
+		  featureData=featureData(from))
50
+      })
51
+
52
+setValidity("CrlmmSet", function(object) {
53
+	assayDataValidMembers(assayData(object), c("CA", "CB", "calls", "callsConfidence", "senseThetaA", "senseThetaB"))
54
+})
55
+
56
+
57
+
58
+setMethod("computeCopynumber", "CrlmmSet", function(object, cnOptions){
59
+	computeCopynumber.CrlmmSet(object, cnOptions)
60
+})
61
+
62
+setMethod("computeCopynumber", "character", function(object, cnOptions){
63
+	crlmmFile <- object
64
+	isCrlmmSet <- length(grep("crlmmSet", crlmmFile[1])) > 0
65
+	for(i in seq(along=crlmmFile)){
66
+		cat("Processing ", crlmmFile[i], "...\n")
67
+		load(crlmmFile[i])
68
+		if(isCrlmmSet){
69
+			object <- get("crlmmSet")
70
+		} else {
71
+			object <- get("callSetPlus")
72
+		}
73
+		CHR <- unique(chromosome(object))
74
+		##if(length(CHR) > 1) stop("More than one chromosome in the object. This method requires one chromosome at a time.")		
75
+		if(all(CHR==24)){
76
+			message("skipping chromosome 24")
77
+			next()
78
+		}
79
+		cat("----------------------------------------------------------------------------\n")
80
+		cat("-        Estimating copy number for chromosome", CHR, "\n")
81
+		cat("----------------------------------------------------------------------------\n")
82
+		crlmmSet <- computeCopynumber(object, cnOptions)
83
+		save(crlmmSet, file=file.path(dirname(crlmmFile), paste("crlmmSet_", CHR, ".rda", sep="")))
84
+		if(!isCrlmmSet) if(cnOptions[["unlink"]]) unlink(crlmmFile[i])
85
+		rm(object, crlmmSet); gc();
86
+	}	
87
+})
88
+
89
+setMethod("pr", signature(object="CrlmmSet",
90
+			  name="character",
91
+			  batch="ANY",
92
+			  value="numeric"), 
93
+	  function(object, name, batch, value){
94
+		  label <- paste(name, batch, sep="_")
95
+		  colindex <- match(label, fvarLabels(object))
96
+		  if(length(colindex) == 1){
97
+			  fData(object)[, colindex] <- value
98
+		  } 
99
+		  if(is.na(colindex)){
100
+			  stop(paste(label, " not found in object"))
101
+		  }
102
+		  if(length(colindex) > 1){
103
+			  stop(paste(label, " not unique"))
104
+		  }
105
+		  object
106
+	  })
107
+
108
+setMethod("computeEmission", "CrlmmSet", function(object, hmmOptions){
109
+	computeEmission.CrlmmSet(object, hmmOptions)
110
+})
111
+
112
+setMethod("computeEmission", "character", function(object, hmmOptions){
113
+	filename <- object
114
+	chrom <- gsub(".rda", "", strsplit(filename, "_")[[1]][[2]])
115
+	if(hmmOptions[["verbose"]])
116
+		message("Compute emission probabilities for chromosome ", chrom)
117
+	if(file.exists(filename)){
118
+		load(filename)
119
+		crlmmSet <- get("crlmmSet")
120
+	} else {
121
+		stop("File ", filename, " does not exist.")
122
+	}
123
+	emission <- computeEmission(crlmmSet, hmmOptions)
124
+	message("Saving ", file.path(dirname(filename), paste("emission_", chrom, ".rda", sep="")))
125
+	if(hmmOptions[["save.it"]]){
126
+		save(emission,
127
+		     file=file.path(dirname(filename), paste("emission_", chrom, ".rda", sep="")))
128
+	}
129
+	return(emission)
130
+})
131
+
132
+setMethod("computeHmm", "CrlmmSet", function(object, hmmOptions){
133
+	computeHmm.CrlmmSet(object, hmmOptions)
134
+})
135
+
136
+##setMethod("computeHmm", "SnpCallSetPlus", function(object, hmmOptions){
137
+##	crlmmSet <- computeCopynumber(object, hmmOptions)
138
+##	computeHmm(crlmmSet, hmmOptions)
139
+##})
140
+
141
+## Genotype everything to get callSetPlus objects
142
+## Go from callSets to Segments sets, writing only the segment set to file
143
+## Safe, but very inefficient. Writes the quantile normalized data to file several times...
144
+setMethod("computeHmm", "character", function(object, hmmOptions){
145
+	outdir <- cnOptions[["outdir"]]
146
+	hmmOptions <- hmmOptions[["hmmOpts"]]
147
+	filenames <- object
148
+	for(i in seq(along=filenames)){
149
+		chrom <- gsub(".rda", "", strsplit(filenames[i], "_")[[1]][[2]])
150
+		if(hmmOptions[["verbose"]])
151
+			message("Fitting HMM to chromosome ", chrom)
152
+		if(file.exists(filenames[i])){
153
+			message("Loading ", filenames[i])
154
+			load(filenames[i])
155
+			crlmmSet <- get("crlmmSet")
156
+		} else {
157
+			stop("File ", filenames[i], " does not exist.")
158
+		}
159
+		hmmOptions$emission <- computeEmission(filenames[i], hmmOptions)
160
+		segmentSet <- computeHmm(crlmmSet, hmmOptions)
161
+		##MIN.MARKERS <- hmmOptions[["MIN.MARKERS"]]
162
+		##segmentSet <- segments[segments$nprobes >= MIN.MARKERS, ]
163
+		message("Saving ", file.path(outdir, paste("segmentSet_", chrom, ".rda", sep="")))
164
+		save(segmentSet,
165
+		     file=file.path(outdir, paste("segmentSet_", chrom, ".rda", sep="")))
166
+		unlink(file.path(outdir, paste("crlmmSet_", chrom, ".rda", sep="")))
167
+	}
168
+	fns <- list.files(outdir, pattern="segmentSet", full.names=TRUE)
169
+	return(fns)	
170
+})
171
+
172
+##initializeCrlmmSet <- function(annotation, sns, backingfile="./"){
173
+##	require(bigmemory)
174
+##	message("Initializing CrlmmSet file--be patient...")
175
+##	path <- system.file("extdata", package=paste(annotation, "Crlmm", sep=""))
176
+##	load(file.path(path, "snpProbes.rda"))
177
+##	load(file.path(path, "cnProbes.rda"))
178
+##	nr <- nrow(snpProbes)+nrow(cnProbes)
179
+##	pos <- c(snpProbes[, "position"], cnProbes[, "position"])
180
+##	chr <- c(snpProbes[, "chrom"], cnProbes[, "chrom"])
181
+##	index <- order(chr, pos)
182
+##	fns <- c(rownames(snpProbes), rownames(cnProbes))[index]
183
+####	fns <- fns[1:20]
184
+##	nr <- length(fns)
185
+##	nc <- length(sns)
186
+####	if(!file.exists(file.path(backingfile, "A.bin"))){
187
+##		AA <- filebacked.big.matrix(nr, nc, 
188
+##					    type="integer",
189
+##					    init=0,
190
+##					    backingpath=backingfile,
191
+##					    backingfile="A.bin",
192
+##					    descriptorfile="A.desc",
193
+##					    dimnames=list(fns, sns))
194
+####	} else {
195
+####		AA <- attach.big.matrix("A.desc", backingpath=backingfile)
196
+####	}
197
+####	if(!file.exists(file.path(backingfile, "B.bin"))){
198
+##		BB <- filebacked.big.matrix(nr, nc, 
199
+##					    type="integer",
200
+##					    init=0,
201
+##					    backingpath=backingfile,
202
+##					    backingfile="B.bin",
203
+##					    descriptorfile="B.desc",
204
+##					    dimnames=list(fns, sns))			   
205
+####	}  else {
206
+####		BB <- attach.big.matrix("B.desc", backingpath=backingfile)
207
+####	}
208
+####	if(!file.exists(file.path(backingfile, "GT.bin"))){
209
+##		gt <- filebacked.big.matrix(nr, nc, 
210
+##					    type="integer",
211
+##					    init=0,
212
+##					    backingpath=backingfile,
213
+##					    backingfile="GT.bin",
214
+##					    descriptorfile="GT.desc",
215
+##					    dimnames=list(fns, sns))
216
+##		confs <- filebacked.big.matrix(nr, nc, 
217
+##					       type="integer",
218
+##					       init=0,
219
+##					       backingpath=backingfile,
220
+##					       backingfile="confs.bin",
221
+##					       descriptorfile="confs.desc",
222
+##					       dimnames=list(fns, sns))	
223
+####	} else {
224
+####		gt <- attach.big.matrix("GT.desc", backingpath=backingfile)
225
+####	}
226
+####	if(!file.exists(file.path(backingfile, "CA.bin"))){
227
+##		ca <- filebacked.big.matrix(nr, nc, 
228
+##					    type="integer",
229
+##					    init=0,
230
+##					    backingpath=backingfile,
231
+##					    backingfile="CA.bin",
232
+##					    descriptorfile="CA.desc",
233
+##					    dimnames=list(fns, sns))
234
+####	}  else {
235
+####		ca <- attach.big.matrix("CA.desc", backingpath=backingfile)
236
+####	}
237
+####	if(!file.exists(file.path(backingfile, "CB.bin"))){
238
+##		cb <- filebacked.big.matrix(nr, nc, 
239
+##					    type="integer",
240
+##					    init=0,
241
+##					    backingpath=backingfile,
242
+##					    backingfile="CB.bin",
243
+##					    descriptorfile="CB.desc",
244
+##					    dimnames=list(fns, sns))
245
+####	} else {
246
+####		cb <- attach.big.matrix("CB.desc", backingpath=backingfile)
247
+####	}
248
+##	return(new("CrlmmSet", A=AA, B=BB, CA=ca, CB=cb, GT=gt, confs=confs))
249
+##}
250
+
251
+
252
+##setMethod("A", signature(object="CrlmmSet"),
253
+##          function(object) assayDataElement(object,"A"))
254
+##setMethod("B", signature(object="CrlmmSet"),
255
+##          function(object) assayDataElement(object,"A"))
256
+##setMethod("CA", signature(object="CrlmmSet"),
257
+##          function(object) assayDataElement(object,"A"))
258
+##setMethod("CB", signature(object="CrlmmSet"),
259
+##          function(object) assayDataElement(object,"A"))
260
+##setMethod("GT", signature(object="CrlmmSet"),
261
+##          function(object) assayDataElement(object,"GT"))
262
+
263
+##setReplaceMethod("CA", signature(object="CrlmmSetList", value="big.matrix"),
264
+##		 function(object, value){
265
+##			 assayDataElementReplace(object, "A", value)
266
+##		 })
267
+##setReplaceMethod("CB", signature(object="CrlmmSetList", value="big.matrix"),
268
+##		 function(object, value){
269
+##			 CB(object[[3]]) <- value
270
+##			 object
271
+##			 })
272
+##
273
+##setReplaceMethod("A", signature(object="CrlmmSet", value="big.matrix"),
274
+##		 function(object, value){
275
+##			 assayDataElementReplace(object, "A", value)
276
+##		 })
277
+
278
+##setReplaceMethod("GT", signature(object="CrlmmSet", value="big.matrix"),
279
+##		 function(object, value){
280
+##			 assayDataElementReplace(object, "GT", value)
281
+##		 })
282
+##setReplaceMethod("confs", signature(object="CrlmmSet", value="big.matrix"),
283
+##		 function(object, value){
284
+##			 assayDataElementReplace(object, "callProbability", value)
285
+##		 })
286
+##setReplaceMethod("confs", signature(object="CrlmmSet", value="matrix"),
287
+##		 function(object, value){
288
+##			 assayDataElementReplace(object, "callProbability", value)
289
+##		 })
290
+##setReplaceMethod("GT", signature(object="CrlmmSet", value="matrix"),
291
+##		 function(object, value){
292
+##			 assayDataElementReplace(object, "GT", value)
293
+##		 })
294
+##setReplaceMethod("B", signature(object="CrlmmSetList", value="big.matrix"),
295
+##		 function(object, value){
296
+##			 B(object[[1]]) <- value
297
+##			 object
298
+##		 })
0 299
new file mode 100644
... ...
@@ -0,0 +1,39 @@
1
+##setAs("SnpCallSetPlus", "CrlmmSetFF",
2
+##	  function(from, to){
3
+##		  CA <- CB <- matrix(NA, nrow(from), ncol(from))
4
+##		  dimnames(CA) <- dimnames(CB) <- list(featureNames(from), sampleNames(from))		  
5
+##		  new("CrlmmSetFF",
6
+##		      calls=calls(from),
7
+##		      callsConfidence=callsConfidence(from),
8
+##		      senseThetaA=A(from),
9
+##		      senseThetaB=B(from),
10
+##		      CA=CA,
11
+##		      CB=CB,
12
+##		      phenoData=phenoData(from),
13
+##		      experimentData=experimentData(from),
14
+##		      annotation=annotation(from),
15
+##		      protocolData=protocolData(from),
16
+##		      featureData=featureData(from))
17
+##	  })
18
+
19
+##setMethod("[", "CrlmmSetFF", function(x, i, j, ..., drop = FALSE) {
20
+	## does NOT subset any of the assayDataElements
21
+	## does subset the featureData, phenoData, protocolData
22
+
23
+	## accessors to the assayData work as follows
24
+	## object2 <- object[1:10, ]
25
+	##
26
+	## A(object2)[1:10, ]
27
+	##  - i.  A(object2) gets the file
28
+	##  - ii. A is subset by the dimNames information as follows
29
+	##        dimNames[[1]] %in% featureNames(object2)
30
+	##        dimNames[[2]] %in% sampleNames(object2)
31
+	##    iii. first 10 elements are retrieved
32
+##})
33
+
34
+##setMethod("A", "CrlmmSetFF", function(object) assayData(object)[["senseThetaA"]])
35
+##setMethod("B", "CrlmmSetFF", function(object) assayData(object)[["senseThetaB"]])
36
+##setMethod("CA", "CrlmmSetFF", function(object) assayData(object)[["CA"]]/100)
37
+##setMethod("CB", "CrlmmSetFF", function(object) assayData(object)[["CB"]]/100)
38
+
39
+
0 40
deleted file mode 100644
... ...
@@ -1,317 +0,0 @@
1
-setMethod("[", "CrlmmSetList", function(x, i, j, ..., drop = FALSE){
2
-            if (missing(drop)) drop <- FALSE
3
-            if (missing(i) && missing(j))
4
-              {
5
-                 if (length(list(...))!=0)
6
-                   stop("specify genes or samples to subset; use '",
7
-                        substitute(x), "$", names(list(...))[[1]],
8
-                        "' to access phenoData variables")
9
-                 return(x)
10
-               }
11
-            if (!missing(j)){
12
-              f1 <- function(x, j){
13
-                x <- x[, j]
14
-              }
15
-              x <- lapply(x, f1, j)
16
-            }
17
-            if(!missing(i)){
18
-              f2 <- function(x, i){
19
-                x <- x[i, ]
20
-              }
21
-              x <- lapply(x, f2, i)
22
-            }
23
-	as(x, "CrlmmSetList")	
24
-})
25
-
26
-setMethod("$", "CrlmmSetList", function(x, name) {
27
-	##if(!(name %in% .parameterNames()[output(x) != 0])){
28
-	if(length(x) != 3){
29
-		stop("'$' operature reserved for accessing parameter names in CopyNumberSet object.  CrlmmSetList must be of length 3")
30
-	}
31
-	j <- grep(name, fvarLabels(x[[3]]))	
32
-	if(length(j) < 1)
33
-		stop(name, " not in fvarLabels of CopyNumberSet object")
34
-	if(length(j) > 1){
35
-		warning("Multiple instances of ", name, " in fvarLabels.  Using the first instance")
36
-		j <- j[1]
37
-	}
38
-	param <- fData(x[[3]])[, j]
39
-	param
40
-})
41
-setMethod(".harmonizeDimnames", "CrlmmSetList", function(object){
42
-	i <- length(object)
43
-	while(i > 1){
44
-		object[[i-1]] <- harmonizeDimnamesTo(object[[i-1]], object[[i]])
45
-		i <- i-1
46
-	}
47
-	object
48
-})
49
-
50
-setMethod("A", "CrlmmSetList", function(object) A(object[[1]]))
51
-
52
-setMethod("addFeatureAnnotation", "CrlmmSetList", function(object, ...){
53
-	##if(missing(CHR)) stop("Must specificy chromosome")
54
-	cdfName <- annotation(object)
55
-	pkgname <- paste(cdfName, "Crlmm", sep="")	
56
-	path <- system.file("extdata", package=pkgname)
57
-	loader("cnProbes.rda", pkgname=pkgname, envir=.crlmmPkgEnv)
58
-	cnProbes <- get("cnProbes", envir=.crlmmPkgEnv)
59
-	loader("snpProbes.rda", pkgname=pkgname, envir=.crlmmPkgEnv)
60
-	snpProbes <- get("snpProbes", envir=.crlmmPkgEnv)	
61
-
62
-	##Feature Data
63
-	snps <- featureNames(object)[snpIndex(object)]
64
-	nps <- featureNames(object)[cnIndex(object)]
65
-	position.snp <- snpProbes[match(snps, rownames(snpProbes)), "position"]
66
-	names(position.snp) <- snps
67
-	position.np <- cnProbes[match(nps, rownames(cnProbes)), "position"]
68
-	names(position.np) <- nps
69
-
70
-	J <- grep("chr", colnames(snpProbes))
71
-	chr.snp <- snpProbes[match(snps, rownames(snpProbes)), J]
72
-	chr.np <- cnProbes[match(nps, rownames(cnProbes)), J]	
73
-	
74
-	position <- c(position.snp, position.np)
75
-	chrom <- c(chr.snp, chr.np)
76
-
77
-	##We may not have annotation for all of the snps
78
-	if(!all(featureNames(object) %in% names(position))){
79
-		message("Dropping loci for which physical position  is not available.")
80
-		object <- object[featureNames(object) %in% names(position), ]
81
-	}
82
-	ix <- match(featureNames(object), names(position))
83
-	position <- position[ix]
84
-	chrom <- chrom[ix]
85
-	##require(SNPchip)
86
-	chrom <- chromosome2integer(chrom)
87
-
88
-	stopifnot(identical(names(position), featureNames(object)))
89
-	if(sum(duplicated(names(position))) > 0){
90
-		warning("Removing rows with NA identifiers...")
91
-		##RS: fix this
92
-		I <- which(!is.na(names(position)))
93
-	}  else I <- seq(along=names(position))
94
-	fd <- data.frame(cbind(chrom[I],
95
-			       position[I]))
96
-	colnames(fd) <- c("chromosome", "position")
97
-	rownames(fd) <- featureNames(object)
98
-	fD <- new("AnnotatedDataFrame",
99
-		  data=fd,
100
-		  varMetadata=data.frame(labelDescription=colnames(fd)))
101
-	return(fD)
102
-})
103
-
104
-setMethod("annotation", "CrlmmSetList", function(object) annotation(object[[1]]))
105
-setMethod("B", "CrlmmSetList", function(object) B(object[[1]]))
106
-setMethod("batch", "CrlmmSetList", function(object) batch(object[[3]]))
107
-setMethod("CA", "CrlmmSetList", function(object, ...) CA(object[[3]], ...))
108
-setMethod("CB", "CrlmmSetList", function(object, ...) CB(object[[3]], ...))
109
-setMethod("calls", "CrlmmSetList", function(object) calls(object[[2]]))
110
-setMethod("chromosome", "CrlmmSetList", function(object){
111
-	chr <- NULL
112
-	for(i  in 1:length(object)){
113
-		if(length(fvarLabels(object[[i]])) > 0){
114
-			if("chromosome" %in% fvarLabels(object[[i]])){
115
-				chr <- chromosome(object[[i]])
116
-				break()
117
-			}
118
-		}
119
-	}
120
-	if(is.null(chr)) warning("fvarLabel 'chromosome' not in any element of the CrlmmSetList object")	
121
-	return(chr)
122
-	##chromosome(object[[3]])
123
-	})
124
-
125
-setMethod("position", "CrlmmSetList", function(object){
126
-	pos <- NULL
127
-	for(i  in 1:length(object)){
128
-		if(length(fvarLabels(object[[i]])) > 0){
129
-			if("position" %in% fvarLabels(object[[i]])){
130
-				pos <- position(object[[i]])
131
-				break()
132
-			}
133
-		} else next()
134
-	}
135
-	if(is.null(pos)) warning("fvarLabel 'position' not in any element of the CrlmmSetList object")
136
-	return(pos)
137
-	})
138
-
139
-setMethod("cnIndex", "CrlmmSetList", function(object, ...) {
140
-	match(cnNames(object[[1]], annotation(object)), featureNames(object))
141
-})
142
-setMethod("combine", signature=signature(x="CrlmmSetList", y="CrlmmSetList"),
143
-          function(x, y, ...){
144
-		  x.abset <- x[[1]]
145
-		  y.abset <- y[[1]]
146
-		  x.snpset <- x[[2]]
147
-		  y.snpset <- y[[2]]
148
-		  abset <- combine(x.abset, y.abset)
149
-		  ##we have hijacked the featureData slot to store parameters.  Biobase will not allow combining our 'feature' data.
150
-		  warning("the featureData is not easily combined...  removing the featureData")
151
-		  ##fd1 <- featureData(x.snpset)
152
-		  ##fd2 <- featureData(y.snpset)
153
-		  featureData(x.snpset) <- annotatedDataFrameFrom(calls(x.snpset), byrow=TRUE)
154
-		  featureData(y.snpset) <- annotatedDataFrameFrom(calls(y.snpset), byrow=TRUE)
155
-		  snpset <- combine(x.snpset, y.snpset)
156
-		  merged <- list(abset, snpset)
157
-		  merged <- as(merged, "CrlmmSetList")
158
-		  merged
159
-	  })
160
-setMethod("confs", "CrlmmSetList", function(object) confs(object[[2]]))
161
-setMethod("copyNumber", "CrlmmSetList", function(object) copyNumber(object[[3]]))
162
-setMethod("dims", "CrlmmSetList", function(object) sapply(object, dim))
163
-setMethod("featureNames", "CrlmmSetList", function(object) featureNames(object[[1]]))
164
-setMethod("ncol", signature(x="CrlmmSetList"), function(x) ncol(x[[1]]))
165
-setMethod("nrow", signature(x="CrlmmSetList"), function(x) nrow(x[[1]]))
166
-setMethod("plot", signature(x="CrlmmSetList"),
167
-	  function(x, y, ...){
168
-		  A <- log2(A(x))
169
-		  B <- log2(B(x))
170
-		  plot(A, B, ...)
171
-	  })
172
-setMethod("points", signature(x="CrlmmSetList"),
173
-	  function(x, y, ...){
174
-		  A <- log2(A(x))
175
-		  B <- log2(B(x))
176
-		  points(A, B, ...)
177
-	  })
178
-setMethod("sampleNames", "CrlmmSetList", function(object) sampleNames(object[[1]]))
179
-setMethod("show", "CrlmmSetList", function(object){
180
-	cat("\n Elements in CrlmmSetList object: \n")
181
-	cat("\n")
182
-	for(i in 1:length(object)){
183
-		cat("class: ", class(object[[i]]), "\n")
184
-		cat("assayData elements: ", ls(assayData(object[[i]])), "\n")
185
-		cat("Dimensions: ", dim(object[[i]]))		
186
-		cat("\n \n")
187
-	}
188
-})
189
-setMethod("snpIndex", "CrlmmSetList", function(object, ...){
190
-	match(snpNames(object[[1]], annotation(object)), featureNames(object))
191
-})
192
-setMethod("splitByChromosome", "CrlmmSetList", function(object, cdfName, outdir){
193
-	path <- system.file("extdata", package=paste(cdfName, "Crlmm", sep=""))	
194
-	load(file.path(path, "snpProbes.rda"))
195
-	load(file.path(path, "cnProbes.rda"))
196
-	k <- grep("chr", colnames(snpProbes))
197
-	if(length(k) < 1) stop("chr or chromosome not in colnames(snpProbes)")
198
-	for(CHR in 1:24){
199
-		cat("Chromosome ", CHR, "\n")
200
-		snps <- rownames(snpProbes)[snpProbes[, k] == CHR]
201
-		cnps <- rownames(cnProbes)[cnProbes[, k] == CHR]
202
-		index <- c(match(snps, featureNames(object)),
203
-			   match(cnps, featureNames(object)))
204
-		index <- index[!is.na(index)]
205
-		crlmmSetList <- object[index, ]
206
-		save(crlmmSetList, file=file.path(outdir, paste("crlmmSetList_", CHR, ".rda", sep="")))
207
-	}
208
-})
209
-
210
-setMethod("update", "CrlmmSetList", function(object, ...){
211
-	if(length(crlmmSetList) == 3){
212
-		message("copy number object already present. Nothing to do.")
213
-		return()
214
-	}
215
-	CHR <- unique(chromosome(crlmmSetList[[1]]))
216
-	if(length(CHR) > 1) stop("More than one chromosome in the object. This method requires one chromosome at a time.")
217
-	if(CHR == 24){
218
-		message("A solution for chromosome 24 is not yet available.")
219
-		return()
220
-	}	
221
-	computeCopynumber(object, CHR=CHR, ...)
222
-})
223
-
224
-setReplaceMethod("CA", signature(object="CrlmmSetList", value="matrix"),
225
-		 function(object, value){
226
-			 CA(object[[3]]) <- value
227
-			 object
228
-		 })
229
-setReplaceMethod("CB", signature(object="CrlmmSetList", value="matrix"),
230
-		 function(object, value){
231
-			 CB(object[[3]]) <- value
232
-			 object
233
-			 })
234
-
235
-setReplaceMethod("A", signature(object="CrlmmSetList", value="matrix"),
236
-		 function(object, value){
237
-			 A(object[[1]]) <- value
238
-			 object
239
-		 })
240
-setReplaceMethod("B", signature(object="CrlmmSetList", value="matrix"),
241
-		 function(object, value){
242
-			 B(object[[1]]) <- value
243
-			 object
244
-		 })
245
-
246
-
247
-
248
-setMethod("boxplot", "CrlmmSetList", function(x, ...){
249
-##boxplot.CrlmmSetList <- function(x, ...){
250
-	if(length(x) != 3) stop("elements of list should be of class ABset, SnpSet, and CopyNumberSet, respectively.")
251
-	genotypes <- calls(x)-1
252
-	A1 <- A(x)
253
-	B1 <- B(x)
254
-	Alist <- split(A1, genotypes)
255
-	Alist <- as(rev(Alist), "data.frame")
256
-	Blist <- split(B1, genotypes)
257
-	ylim <- range(unlist(Alist))
258
-	boxplot(Alist, xaxt="n", ylab=expression(I[A]), 
259
-		cex.axis=0.6,
260
-		xlab="",
261
-		ylim=range(unlist(Alist), na.rm=TRUE),	
262
-		border="grey50", xaxs="i", at=0:2, xlim=c(-0.5, 2.5),
263
-		cex.main=0.9, xaxt="n",
264
-		yaxt="n",
265
-		col=cols)
266
-	axis(2, at=pretty(ylim), cex.axis=0.8)
267
-	axis(1, at=0:2, labels=rev(c("2A (AA genotype)", "1A (AB genotype)", "0A (BB genotype)")), cex.axis=0.7)
268
-	##extracts nuA for first batch
269
-	suppressWarnings(nuA <- x$nuA)
270
-	segments(-1, nuA, 
271
-		 0, nuA, lty=2, col="blue")
272
-	suppressWarnings(phiA <- x$phiA)
273
-	##phiA <- fData(x)[["phiA_A"]]
274
-	segments(0, nuA,
275
-		 2.5, nuA+2.5*phiA, lwd=2, col="blue")
276
-	axis(2, at=nuA, labels=expression(hat(nu[A])), cex.axis=0.9)
277
-	text(0, ylim[1], labels=paste("n =", length(Alist[[1]])), cex=0.8)
278
-	text(1, ylim[1], labels=paste("n =", length(Alist[[2]])), cex=0.8)
279
-	text(2, ylim[1], labels=paste("n =", length(Alist[[3]])), cex=0.8)
280
-##	segments(0.5, nuA+0.5*phiA,
281
-##		 1, pretty(ylim, n=5)[2], lty=2, col="blue")
282
-##	segments(1, pretty(ylim, n=5)[2],
283
-##		 1.2, pretty(ylim)[2], lty=2, col="blue")
284
-##	text(1.25, pretty(ylim)[2], pos=4, 
285
-##	     labels=expression(hat(nu[A]) + c[A]*hat(phi[A])))
286
-	legend("topleft", fill=rev(cols), legend=c("AA", "AB", "BB"))##, title="diallelic genotypes")	
287
-
288
-	ylim <- range(unlist(Blist))
289
-	boxplot(Blist, xaxt="n", ylab=expression(I[B]), 
290
-		##xlab="diallelic genotypes", 
291
-		cex.axis=0.6, 
292
-		ylim=range(unlist(Blist), na.rm=TRUE),
293
-		border="grey50", xaxs="i", 
294
-		at=0:2, xlim=c(-0.5, 2.5),
295
-		cex.main=0.9, yaxt="n", 
296
-		col=rev(cols))
297
-	axis(2, at=pretty(ylim), cex.axis=0.8)
298
-	axis(1, at=0:2, labels=c("0B (AA genotype)", "1B (AB genotype)", "2B (BB genotype)"), cex.axis=0.7)
299
-	##nuB <- fData(x)[["nuB_A"]]
300
-	suppressWarnings(nuB <- x$nuB)
301
-	segments(-1, nuB, 
302
-		 0, nuB, lty=2, col="blue")
303
-	##phiB <- fData(x[i,])[["phiB_A"]]
304
-	suppressWarnings(phiB <- x$phiB)
305
-	segments(0, nuB,
306
-		 2.5, nuB+2.5*phiB, lwd=2, col="blue")
307
-	axis(2, at=nuB, labels=expression(hat(nu[B])), cex.axis=0.9)
308
-	text(0, ylim[1], labels=paste("n =", length(Blist[[1]])), cex=0.8)
309
-	text(1, ylim[1], labels=paste("n =", length(Blist[[2]])), cex=0.8)
310
-	text(2, ylim[1], labels=paste("n =", length(Blist[[3]])), cex=0.8)
311
-##	segments(0.5, nuB+0.5*phiB,
312
-##		 1, pretty(ylim,n=5)[2], lty=2, col="blue")
313
-##	segments(1, pretty(ylim, n=5)[2],
314
-##		 1.2, pretty(ylim,n=5)[2], lty=2, col="blue")
315
-##	text(1.25, pretty(ylim,n=5)[2], pos=4, labels=expression(hat(nu[B]) + c[B]*hat(phi[B])))	
316
-	mtext(featureNames(x)[i], 3, outer=TRUE, line=1)	
317
-})
318 0
new file mode 100644
... ...
@@ -0,0 +1,109 @@
1
+##How to make the initialization platform-specific?
2
+setMethod("initialize", "SnpCallSetPlus",
3
+          function(.Object,
4
+                   phenoData, featureData,
5
+                   calls=new("matrix"),
6
+                   callsConfidence=new("matrix"),
7
+                   senseThetaA=new("matrix"),
8
+                   senseThetaB=new("matrix"),
9
+		   annotation,
10
+		   experimentData,
11
+		   protocolData, ... ){
12
+		  ad <- assayDataNew("lockedEnvironment",
13
+				     calls=calls,
14
+				     callsConfidence=callsConfidence,
15
+				     senseThetaA=senseThetaA,
16
+				     senseThetaB=senseThetaB)
17
+		  assayData(.Object) <- ad
18
+		  if (missing(phenoData)){
19
+			  phenoData(.Object) <- annotatedDataFrameFrom(calls, byrow=FALSE)
20
+		  } else{
21
+			  phenoData(.Object) <- phenoData
22
+		  }
23
+		  if (missing(featureData)){
24
+			  featureData(.Object) <- annotatedDataFrameFrom(calls, byrow=TRUE)
25
+		  } else{
26
+			  featureData(.Object) <- featureData
27
+		  }
28
+		  if(!missing(annotation)) annotation(.Object) <- annotation
29
+		  if(!missing(experimentData)) experimentData(.Object) <- experimentData
30
+		  if(!missing(protocolData)) protocolData(.Object) <- protocolData
31
+		  .Object
32
+          })
33
+getParam.SnpCallSetPlus <- function(object, name, batch){
34
+		  label <- paste(name, batch, sep="_")
35
+		  colindex <- grep(label, fvarLabels(object))
36
+		  if(length(colindex) == 1){
37
+			  param <- fData(object)[, colindex]
38
+		  }
39
+		  if(length(colindex) < 1){
40
+			  param <- NULL
41
+		  }
42
+		  if(is.na(colindex)){
43
+			  stop(paste(label, " not found in object"))
44
+		  }
45
+		  if(length(colindex) > 1){
46
+			  stop(paste(label, " not unique"))
47
+		  }
48
+		  return(param)
49
+	  }
50
+
51
+setMethod("getParam", signature(object="SnpCallSetPlus",
52
+				name="character",
53
+				batch="ANY"),
54
+	  function(object, name, batch){
55
+		  if(length(batch) > 1){
56
+			  warning("batch argument to getParam should have length 1.  Only using the first")
57
+			  batch <- batch[1]
58
+		  }
59
+		  getParam.SnpCallSetPlus(object, name, batch)
60
+})
61
+
62
+setMethod("splitByChromosome", "SnpCallSetPlus", function(object, cnOptions){
63
+	tmpdir <- cnOptions[["tmpdir"]]
64
+	outdir <- cnOptions[["outdir"]]	
65
+	save.it <- cnOptions[["save.it"]]
66
+	path <- system.file("extdata", package=paste(annotation(object), "Crlmm", sep=""))	
67
+	load(file.path(path, "snpProbes.rda"))
68
+	snpProbes <- get("snpProbes")
69
+	load(file.path(path, "cnProbes.rda"))
70
+	cnProbes <- get("cnProbes")	
71
+	k <- grep("chr", colnames(snpProbes))
72
+	if(length(k) < 1) stop("chr or chromosome not in colnames(snpProbes)")
73
+	for(CHR in 1:24){
74
+		cat("Chromosome ", CHR, "\n")
75
+		snps <- rownames(snpProbes)[snpProbes[, k] == CHR]
76
+		cnps <- rownames(cnProbes)[cnProbes[, k] == CHR]
77
+		index <- c(match(snps, featureNames(object)),
78
+			   match(cnps, featureNames(object)))
79
+		index <- index[!is.na(index)]
80
+		callSetPlus <- object[index, ]
81
+		if(CHR != 24){
82
+			crlmmSet <- computeCopynumber(callSetPlus, cnOptions)
83
+			
84
+		} else{
85
+			message("Copy number estimates not available for chromosome Y.  Saving only the 'callSetPlus' object for this chromosome")
86
+			save(callSetPlus, file=file.path(outdir, paste("callSetPlus_", CHR, ".rda", sep="")))
87
+		}
88
+		if(cnOptions[["hiddenMarkovModel"]] & CHR != 24){
89
+			segmentSet <- computeHmm(crlmmSet, cnOptions)
90
+			save(segmentSet, file=file.path(outdir, paste("segmentSet_", CHR, ".rda", sep="")))
91
+			saved.objects <- list.files(outdir, pattern="segmentSet", full.names=TRUE)
92
+		} else{ ## save crlmmSet to outdir
93
+			save(crlmmSet, file=file.path(outdir, paste("crlmmSet_", CHR, ".rda", sep="")))
94
+			saved.objects <- list.files(outdir, pattern="crlmmSet", full.names=TRUE)			
95
+		}		
96
+	}
97
+	saved.objects
98
+})
99
+setMethod("addFeatureAnnotation", "SnpCallSetPlus", function(object, ...){
100
+	addFeatureAnnotation.SnpCallSetPlus(object, ...)
101
+})
102
+setMethod("computeCopynumber", "SnpCallSetPlus",
103
+	  function(object, cnOptions){
104
+		  computeCopynumber.SnpCallSetPlus(object, cnOptions)
105
+	  })
106
+setMethod("chromosome", "SnpCallSetPlus", function(object) fData(object)$chromosome)
107
+setMethod("position", "SnpCallSetPlus", function(object) fData(object)$position)
108
+gtConfidence <- function(object) 1-exp(-callsConfidence(object)/1000)
109
+	
0 110
new file mode 100644
... ...
@@ -0,0 +1,3 @@
1
+setMethod("featureNames", "SnpCallSetPlusFF", function(object) sampleNames(featureData(object)))
2
+setMethod("A", "SnpCallSetPlusFF", function(object){})
3
+
0 4
new file mode 100644
... ...
@@ -0,0 +1,44 @@
1
+##setValidity("SnpQSet", function(object) {
2
+##	##msg <- validMsg(NULL, Biobase:::isValidVersion(object, "CopyNumberSet"))
3
+##	msg <- validMsg(NULL, assayDataValidMembers(assayData(object), c("A", "B")))
4
+##	if (is.null(msg)) TRUE else msg
5
+##})
6
+
7
+setMethod("initialize", "SnpQSet",
8
+          function(.Object,
9
+                   assayData = assayDataNew(senseThetaA=senseThetaA, senseThetaB=senseThetaB),
10
+                   senseThetaA=new("matrix"),
11
+                   senseThetaB=new("matrix"),
12
+                   phenoData=annotatedDataFrameFrom(assayData, byrow=FALSE),
13
+                   featureData = annotatedDataFrameFrom(assayData, byrow=TRUE),
14
+                   experimentData=new("MIAME"),
15
+                   annotation=new("character")){
16
+            .Object <- callNextMethod(.Object,
17
+				      assayData = assayDataNew(senseThetaA=senseThetaA, senseThetaB=senseThetaB),
18
+				      phenoData=phenoData,
19
+				      experimentData=experimentData,
20
+				      annotation=annotation)
21
+            .Object
22
+    })
23
+
24
+setValidity("SnpQSet",
25
+            function(object)
26
+            assayDataValidMembers(assayData(object),
27
+                                  c("senseThetaA",
28
+                                    "senseThetaB")
29
+            ))
30
+setMethod("A", "SnpQSet", function(object) senseThetaA(object))
31
+setMethod("B", "SnpQSet", function(object) senseThetaB(object))
32
+setReplaceMethod("A", signature(object="SnpQSet", value="matrix"),
33
+		 function(object, value){
34
+			 assayDataElementReplace(object, "senseThetaA", value)			
35
+		 })
36
+setReplaceMethod("B", signature(object="SnpQSet", value="matrix"),
37
+		 function(object, value){
38
+			 assayDataElementReplace(object, "senseThetaB", value)			
39
+		 })
40
+setMethod("isSnp", "SnpQSet", function(object) {
41
+	isSnp.SnpQSet(object)
42
+})
43
+
44
+
... ...
@@ -1,5 +1,5 @@
1 1
 ## Methods for crlmm
2
-
3
-
4 2
 setMethod("calls", "SnpSet", function(object) assayData(object)$call)
3
+setReplaceMethod("calls", signature(object="SnpSet", value="matrix"), function(object, value) assayDataElementReplace(object, "call", value))
5 4
 setMethod("confs", "SnpSet", function(object) assayData(object)$callProbability)
5
+setReplaceMethod("confs", signature(object="SnpSet", value="matrix"), function(object, value) assayDataElementReplace(object, "callProbability", value))
... ...
@@ -1,22 +1,39 @@
1
-setMethod("cnIndex", "eSet", function(object, cdfName) match(cnNames(object, cdfName), featureNames(object)))
2
-setMethod("cnNames", "eSet", function(object, cdfName) {
3
-	path <- system.file("extdata", package=paste(cdfName, "Crlmm", sep=""))
1
+setMethod("cnIndex", "eSet", function(object){
2
+	index <- match(cnNames(object), featureNames(object), nomatch=0)
3
+	index[index != 0]
4
+  })
5
+
6
+setMethod("cnNames", "eSet", function(object) {
7
+	path <- system.file("extdata", package=paste(annotation(object), "Crlmm", sep=""))
4 8
 	load(file.path(path, "cnProbes.rda"))
9
+	cnProbes <- get("cnProbes")
5 10
 	cnps <- rownames(cnProbes)
6 11
 	cnps <- cnps[cnps %in% featureNames(object)]
7
-	featureNames(object)[match(cnps, featureNames(object))]	
8
-	##featureNames(object)[grep("CN_", featureNames(object))])
12
+	index <- match(cnps, featureNames(object), nomatch=0)
13
+	index <- index[index != 0]	
14
+	featureNames(object)[index]	
9 15
   })
10
-setMethod("snpIndex", "eSet", function(object, cdfName) match(snpNames(object, cdfName), featureNames(object)))
11
-setMethod("snpNames", "eSet", function(object, cdfName){
12
-	path <- system.file("extdata", package=paste(cdfName, "Crlmm", sep=""))
16
+
17
+
18
+setMethod("snpIndex", "eSet", function(object){
19
+	index <- match(snpNames(object), featureNames(object), nomatch=0)
20
+	index[index != 0]
21
+})
22
+
23
+setMethod("snpNames", "eSet", function(object){
24
+	path <- system.file("extdata", package=paste(annotation(object), "Crlmm", sep=""))
13 25
 	load(file.path(path, "snpProbes.rda"))
26
+	snpProbes <- get("snpProbes")
14 27
 	snps <- rownames(snpProbes)
15 28
 	snps <- snps[snps %in% featureNames(object)]
16
-	featureNames(object)[match(snps, featureNames(object))]
17
-  })
29
+	index <- match(snps, featureNames(object), nomatch=0)
30
+	index <- index[index != 0]
31
+	featureNames(object)[index]
32
+})
33
+
18 34
 setMethod("chromosome", "eSet", function(object) fData(object)$chromosome)
19 35
 setMethod("position", "eSet", function(object) fData(object)$position)
36
+
20 37
 ##setMethod("combine", signature=signature(x="eSet", y="eSet"),
21 38
 ##	  function(x, y, ...){
22 39
 ##		  ##Check that both x and y are valid objects
... ...
@@ -142,4 +142,19 @@ loader <- function(theFile, envir, pkgname){
142 142
   load(theFile, envir=envir)
143 143
 }
144 144
 
145
+celfileDate <- function(filename) {
146
+	h <- affyio::read.celfile.header(filename, info="full")
147
+	date <- grep("/", strsplit(h$DatHeader, " ")[[1]], value=TRUE)
148
+	if(length(date) < 1){
149
+		##try something else
150
+		results <- h$ScanDate
151
+	} else{
152
+		date <- strsplit(date, split="/")[[1]]
153
+		CC <- ifelse(substr(date[3],1,1)=="9", "19", "20")
154
+		results <- as.character(as.Date(paste(paste(CC, date[3], sep=""), date[1],
155
+						      date[2], sep="-")))
156
+	}
157
+	results
158
+}
159
+
145 160
 
146 161
deleted file mode 100644
... ...
@@ -1,113 +0,0 @@
1
-\name{.computeCopynumber}
2
-\alias{.computeCopynumber}
3
-\title{Internal function for computing copy number}
4
-\description{
5
-
6
-  This function is not meant to be called directly by the user and is
7
-  not exported in the package namespace.  Arguments to this function can
8
-  be specified in the 'computeCopynumber' (no '.' preceding the name)
9
-  function.
10
-  
11
-}
12
-\usage{
13
-.computeCopynumber(chrom, A, B, calls, conf, NP, plate, MIN.OBS=1, 
14
-envir, P, DF.PRIOR = 50, CONF.THR = 0.99, bias.adj=FALSE,
15
-priorProb, gender=NULL, SNR, SNRmin, seed=123, cdfName="genomewidesnp6",
16
-verbose=TRUE, ...)
17
-}
18
-\arguments{
19
-  \item{chrom}{Chromosome (an integer).  Use 23 for X and 24 for Y.}
20
-  \item{A}{The A allele intensities from \code{snprma}}
21
-  \item{B}{The B allele intensities from \code{snprma}}
22
-  \item{calls}{The genotype calls from \code{crlmm}}
23
-  \item{conf}{The genotype confidence scores from \code{crlmm}}
24
-  \item{NP}{The quantile normalized intensities of the nonpolymorphic probes}
25
-  \item{plate}{The bach variable.  Should be the same length as the
26
-    number of columns in A}
27
-  \item{MIN.OBS}{Integer: The minimum number of observations in a genotype
28
-    cluster for which a SNP is deemed complete.}
29
-  \item{envir}{An environment to save intermediate objects}
30
-  \item{P}{Mainly for debugging a particular plate/batch.}
31
-  \item{DF.PRIOR}{The degrees of freedom for the prior.  Higher numbers
32
-    will shrink the variance and correlation more.}
33
-  \item{CONF.THR}{A threshold for the genotype confidence scores.
34
-    Genotypes with scores below the threshold are ignored when computing
35
-  SNP-specific  within-genotype estimates of location and scale.}
36
-  \item{bias.adj}{Logical: whether to adjust the location and scale
37
-    parameters to account for biases due to common copy number
38
-    variants.  This is a SNP-specific adjustment.  Parameters for
39
-    background and slope must have already been estimated and available
40
-    from the environment variable.}
41
-  \item{priorProb}{Numerical vector of length 4.  The prior probability
42
-    of each copy number state (0, 1, 2, 3, and 4). The default is a
43
-    uniform prior.  Ignored if bias.adj=FALSE}
44
-  \item{gender}{Gender of subjects. If not specified, we predict the
45
-    gender from the X chromosome.}
46
-  \item{SNR}{Signal to noise ratio from crlmm.}
47
-  \item{SNRmin}{The minimum value for the SNR -- we suggest 5. Samples
48
-    with SNR below SNRmin are excluded.}
49
-  \item{seed}{Seed used for random samples}
50
-  \item{cdfName}{Annotation package }
51
-  \item{verbose}{Logical: verbose output}
52
-  \item{\dots}{Currently ignored}
53
-}
54
-
55
-\details{
56
-  
57
-  This function transforms the intensities to a copy number scale.  We
58
-  assume that the median within-SNP intensity across samples is 2.  We
59
-  make no assumption about the chromosomal copy number. This function is
60
-  useful for detecting rare variants (e.g., variants that would not
61
-  affect the SNP-specific quantile-based estimators of location and
62
-  scale).  A correction for more common variants is coming, as well as
63
-  improved estimates of the uncertainty.
64
-  
65
-}
66
-
67
-\value{
68
-
69
-All objects created by this function are stored in the environment
70
-  passed to this function.  In addition, each of the elements are
71
-  specific to the chromosome(s) specified by the argument \code{chrom}.
72
-  For instance the element \code{A} is the matrix of quantile-normalized
73
-  intensities for the A-allele on chromosome(s) \code{chrom}.  The
74
-  element of this environment are as follows
75
-
76
-  \item{A}{Matrix of quantile-normalized intensities for the A-allele}
77
-  \item{B}{Matrix of quantile-normalized intensities for the A-allele}
78
-  \item{CA}{Copy number estimate for the A-allele (x 100)} 
79
-  \item{CB}{Copy number estimate for the B-allele (x 100)}
80
-  \item{calls}{CRLMM genotype calls (AA=1, AB=2, BB=3)}
81
-  \item{chrom}{Integer(s) indicating the chromosome(s)} 
82
-  \item{cnvs}{Names of the nonpolymorphic probes.  These are the
83
-  rownames of \code{NP} and \code{CT}.}
84
-  \item{conf}{CRLMM confidence scores for the genotypes: 'round(-1000*log2(1-p))'}
85
-  \item{corr}{Correlation of the A and B alleles for genotypes AB}
86
-  \item{corrA.BB}{Correlation of A and B alleles for genotypes BB}
87
-  \item{corrB.AA}{Correlation of A and B alleles for genotypes AA}
88
-  \item{CT}{Copy number estimates for nonpolymorphic probe.  See
89
-  \code{cnvs} for the rownames.}
90
-  \item{CT.sds}{Standard deviation estimates for \code{CT}}
91
-  \item{npflags}{Flags for the nonpolymorphic probes.}
92
-  \item{Ns}{The number of observations for each genotype/plate}
93
-  \item{nuA}{Background/cross-hyb for the A allele (plate- and locus-specific)}
94
-  \item{nuB}{Background/cross-hyb for the B allele (plate- and locus-specific)}
95
-  \item{nuT}{Background for the nonpolymorphic probes (plate- and locus-specific)}
96
-  \item{phiA}{Slope for the A allele (plate- and locus-specific)}
97
-  \item{phiB}{Slope for the B allele (plate- and locus-specific)}
98
-  \item{phiT}{Slope for the nonpolymorphic probes (plate- and locus-specific)}
99
-  \item{plate}{Factor indicating batch (same length as number of cel files)}
100
-  \item{sig2A}{Variance estimate for the A-allele signal (plate- and locus-specific)}
101
-  \item{sig2B}{Variance estimate for the B-allele signal (plate- and locus-specific)}
102
-  \item{sig2T}{Variance estimate for the nonpolymorphic signal (plate- and locus-specific)}
103
-  \item{snpflags}{Flags for polymorphic probes}
104
-  \item{snps}{Rownames for \code{A}, \code{B}, \code{CA}, \code{CB}, ...}
105
-  \item{sns}{ Sample names -- the column names for \code{A}, \code{B}, ...}
106
-  \item{steps}{Steps completed. For internal use.}
107
-  \item{tau2A}{Variance estimate for the B-allele background/cross-hyb (plate- and locus-specific)}
108
-  \item{tau2B}{Variance estimate for the B-allele background/cross-hyb (plate- and locus-specific)}
109
-}
110
-\references{Nothing yet.}
111
-\author{Rob Scharpf}
112
-\keyword{manip}
113
-
114 0
deleted file mode 100644
... ...
@@ -1,55 +0,0 @@
1
-\name{ABset-class}
2
-\Rdversion{1.1}
3
-\docType{class}
4
-\alias{ABset-class}
5
-\alias{A}
6
-\alias{B}
7
-\alias{A,ABset-method}
8
-\alias{B,ABset-method}
9
-\alias{A<-,ABset,matrix-method}
10
-\alias{B<-,ABset,matrix-method}
11
-\title{Class "ABset"}
12
-\description{Containter for quantile-normalized intensities}
13
-\section{Objects from the Class}{
14
-Objects can be created by calls of the form \code{new("ABset", assayData, phenoData, featureData, experimentData, annotation, protocolData, ...)}.
15
-}
16
-\section{Slots}{
17
-	 \describe{
18
-    \item{\code{assayData}:}{Object of class \code{"AssayData"} }
19
-    \item{\code{phenoData}:}{Object of class \code{"AnnotatedDataFrame"}  }
20
-    \item{\code{featureData}:}{Object of class \code{"AnnotatedDataFrame"} }
21
-    \item{\code{experimentData}:}{Object of class \code{"MIAME"} }
22
-    \item{\code{annotation}:}{Object of class \code{"character"}  }
23
-    \item{\code{protocolData}:}{Object of class \code{"AnnotatedDataFrame"}  }
24
-    \item{\code{.__classVersion__}:}{Object of class \code{"Versions"}  }
25
-  }
26
-}
27
-\section{Extends}{
28
-Class \code{\link[Biobase:class.eSet]{eSet}}, directly.
29
-Class \code{\link[Biobase:class.VersionedBiobase]{VersionedBiobase}}, by class "eSet", distance 2.
30
-Class \code{\link[Biobase:class.Versioned]{Versioned}}, by class "eSet", distance 3.
31
-}
32
-\section{Methods}{
33
-  \describe{
34
-    \item{A}{\code{signature(object="ABset")}: accessor for the
35
-      quantile-normalized intensities of allele A for polymorphic probes
36
-      and the quantile normalized intensities for the copy number
37
-      probes.}
38
-
39
-    \item{"A<-"}{\code{signature(object="ABset", value="matrix")}:
40
-      replacement method for the A allele intensities.}
41
-
42
-    \item{"B<-"}{\code{signature(object="ABset", value="matrix")}:
43
-    replacement method for the B allele intensities.}    
44
-    
45
-    \item{B}{\code{signature(object="ABset")}: accessor for the
46
-      quantile-normalized intensities of allele B for polymorphic probes.}    
47
-    \item{plot}{\code{signature(x = "ABset", y = "CopyNumberSet")}:
48
-... }}
49
-
50
-}
51
-\author{R. Scharpf}
52
-\examples{
53
-showClass("ABset")
54
-}
55
-\keyword{classes}
56 0
deleted file mode 100644
... ...
@@ -1,194 +0,0 @@
1
-\name{CrlmmSetList-class}
2
-\Rdversion{1.1}
3
-\docType{class}
4
-\alias{CrlmmSetList-class}
5
-\alias{[,CrlmmSetList-method}
6
-\alias{$,CrlmmSetList-method}
7
-\alias{addFeatureAnnotation}
8
-\alias{addFeatureAnnotation,CrlmmSetList-method}
9
-\alias{A<-}
10
-\alias{B<-}
11
-\alias{A,CrlmmSetList-method}
12
-\alias{A<-,CrlmmSetList,matrix-method}
13
-\alias{B,CrlmmSetList-method}
14
-\alias{B<-,CrlmmSetList,matrix-method}
15
-\alias{batch,CrlmmSetList-method}
16
-\alias{CA,CrlmmSetList-method}
17
-\alias{CB,CrlmmSetList-method}
18
-\alias{CA<-,CrlmmSetList,matrix-method}
19
-\alias{CB<-,CrlmmSetList,matrix-method}
20
-\alias{calls,CrlmmSetList-method}
21
-\alias{chromosome,CrlmmSetList-method}
22
-\alias{cnIndex,CrlmmSetList-method}
23
-\alias{combine,CrlmmSetList,CrlmmSetList-method}
24
-\alias{confs,CrlmmSetList-method}
25
-\alias{copyNumber,CrlmmSetList-method}
26
-\alias{nrow,CrlmmSetList-method}
27
-\alias{ncol,CrlmmSetList-method}
28
-\alias{plot,CrlmmSetList,ANY-method}
29
-\alias{points,CrlmmSetList-method}
30
-\alias{position,CrlmmSetList-method}
31
-\alias{sampleNames,CrlmmSetList-method}
32
-\alias{show,CrlmmSetList-method}
33
-\alias{snpIndex,CrlmmSetList-method}
34
-\alias{update,CrlmmSetList-method}
35
-\alias{update,character-method}
36
-
37
-
38
-\title{Class "CrlmmSetList"}
39
-\description{Container for quantile normalized intensities and genotype calls.}
40
-\section{Objects from the Class}{
41
-  Objects from the class are created by calls to the \code{crlmmWrapper}
42
-  function. 
43
-}
44
-\section{Slots}{
45
-  \describe{
46
-    \item{\code{.Data}:}{Object of class \code{"list"} ~~ }
47
-  }    
48
-%	   \item{\code{ABset}:}{Object of class \code{"ABset"}.
49
-%	     Contains quantile normalized A and B intensities.  Quantile
50
-%	   normalized intensities for nonpolymorphic probes are stored
51
-%	   in the A slot.}
52
-%	 \item{\code{crlmmResult}:}{Object of class
53
-%	   \code{"SnpSet"}. Contains genotype calls and the
54
-%	   corresponding confidence estimates.}
55
-}
56
-
57
-\section{Details}{
58
-
59
-  Instances of \code{CrlmmSetList} are a list with two elements:
60
-
61
-  1.  an object of class \code{ABset}
62
-
63
-  2.  an object of class \code{SnpSet}
64
-
65
-  The \code{featureNames} and \code{sampleNames} of both objects are
66
-  required to be identical.
67
-
68
-  Quantile-normalized intensities for the copy number probes are stored
69
-  in the assay data element A of the ABset object.  Corresponding rows
70
-  for the B allele are recorded as NAs.  Genotype calls for copy number
71
-  probes in the SnpSet object are recorded as NAs.
72
-
73
-}
74
-  
75
-\section{Extends}{
76
-  Class \code{"\linkS4class{list}"}, from data part.
77
-  Class \code{"\linkS4class{vector}"}, by class "list", distance 2.
78
-  Class \code{\link[Biobase:assayData]{assayData}}, by class
79
-  "list", distance 2. 
80
-}
81
-\section{Methods}{
82
-  \describe{
83
-    \item{"["}{\code{signature(x = "CrlmmSetList")}: subsets both the
84
-      features and samples of each element in th elist}
85
-  
86
-    \item{"$"}{\code{signature(x = "CrlmmSetList")}: used to access
87
-    element from the \code{featureData} of the \code{CopyNumberSet}
88
-    element.  In particular, useful for extract the SNP- and
89
-    batch-specific parameters used to estimate copy number that are
90
-    currently stored in the \code{featureData} of \code{CopyNumberSet}
91
-    objects. }
92
-
93
-  \item{"addFeatureAnnotation"}{\code{signature(object =
94
-  "CrlmmSetList")}: Creates an object of class AnnotatedDataFrame from
95
-  the CrlmmSetList object.  The new annotation object contains
96
-  information on chromosome and physical position and has the same
97
-  ordering of rows as the CrlmmSetList object. }
98
-
99
-    \item{"A"}{\code{signature(object = "CrlmmSetList")}: extracts the
100
-      quantile normalized intensities for the A allele in the
101
-      \code{ABset} element.}
102
-
103
-    \item{"A<-"}{\code{signature(object = "CrlmmSetList", value =
104
-    "matrix")}: Replacement method for the A intensities.}    
105
-  
106
-    \item{"B"}{\code{signature(object = "CrlmmSetList")}: extracts the
107
-      quantile normalized intensities for the B allele in the
108
-      \code{ABset} element.}
109
-    
110
-    \item{"B<-"}{\code{signature(object = "CrlmmSetList", value =
111
-    "matrix")}: Replacement method for the B intensities.}        
112
-    
113
-    \item{"batch"}{\code{signature(object = "CrlmmSetList")}: extracts the
114
-      batch information used to estimate copy number.}    
115
-
116
-    \item{"CA"}{\code{signature(object = "CrlmmSetList")}: extracts the
117
-      copy number for allele A at polymorphic loci. For nonpolymorphic
118
-      probes, CA returns the total copy number. }
119
-  
120
-    \item{"CB"}{\code{signature(object = "CrlmmSetList")}: extracts the
121
-      copy number for allele B at polymorphic loci. For nonpolymorphic
122
-      probes, CB returns 'NA'.}
123
-
124
-    \item{"CA<-"}{\code{signature(object = "CrlmmSetList", value =
125
-	"matrix")}: Replacement method for the CA estimates.}
126
-
127
-    \item{"CB<-"}{\code{signature(object = "CrlmmSetList", value =
128
-    "matrix")}: Replacement method for the CB estimates.}                
129
-
130
-    \item{"calls"}{\code{signature(object = "CrlmmSetList")}: extracts
131
-      the genotype calls from the \code{SnpSet} element.}
132
-
133
-    \item{"cnIndex"}{\code{signature(object = "CrlmmSetList")}: returns
134
-      the row indices of the copy number probes.}
135
-
136
-    \item{"combine"}{\code{signature(x = "CrlmmSetList", y = "CrlmmSetList")}: combines
137
-      objects of the class.  }
138
-
139
-    \item{"confs"}{\code{signature(x = "CrlmmSetList")}: confidence
140
-    scores for crlmm genotype calls. }    
141
-    
142
-    \item{"nrow"}{\code{signature(x = "CrlmmSetList")}: Number of rows
143
-    (features) of each element in the list.  }
144
-    
145
-    \item{"ncol"}{\code{signature(x = "CrlmmSetList")}: Number of columns
146
-    (samples) of each element in the list.  }    
147
-	
148
-    \item{"plot"}{\code{signature(x = "CrlmmSetList")}: For A versus B
149
-      scatterplots.  }
150
-
151
-    \item{"points"}{\code{signature(x = "CrlmmSetList")}: For A versus B
152
-      scatterplots.  }
153
-
154
-    \item{"sampleNames"}{\code{signature(object = "CrlmmSetList")}:
155
-      Accessor for the column identifiers of the assay data elements.  }
156
-
157
-    \item{"show"}{\code{signature(object = "CrlmmSetList")}:
158
-      Shows the \code{ABset} and \code{SnpSet} elements of the list.  }
159
-
160
-    \item{"snpIndex"}{\code{signature(object = "CrlmmSetList")}: returns
161
-      the row indices of the polymorphic probes.}
162
-
163
-    \item{"update"}{\code{signature(object = "CrlmmSetList")}: This
164
-    method calls \code{computeCopynumber} to compute copy number for the
165
-    \code{crlmmSetList} object.  The object returned by this method is
166
-    itself an instance of class \code{CrlmmSetList}.  The third element
167
-    of the list is an instance of \code{CopyNumberSet} containing the
168
-    locus-level, allele-specific estimates of copynumber.  }
169
-
170
-  \item{"update"}{\code{signature(object = "character")}: This method
171
-    loads the CrlmmSetList file given as the argument to object --
172
-    the object is a character string or a vector of character strings
173
-    that provides the complete path to the CrlmmSetList file.
174
-    The CrlmmSetList object is loaded and updated with copy number
175
-    estimates -- an object of class CopyNumberSet becomes the third
176
-    element in the CrlmmSetList object.  After updating the CrlmmSetList
177
-    object, the object is saved to the same path.}
178
-}
179
-}
180
-
181
-\section{Warnings}{
182
-   \code{combine} will produce a warning as the \code{featureData} are
183
-   not easily combined and therefore removed.  This method needs
184
-   improvement.
185
-}
186
-\author{R. Scharpf}
187
-\seealso{
188
-  See also \code{"\link{crlmmWrapper}"},
189
-  \code{"\linkS4class{ABset}"}
190
-}
191
-\examples{
192
-showClass("CrlmmSetList")
193
-}
194
-\keyword{classes}
195 0
deleted file mode 100644
... ...
@@ -1,25 +0,0 @@
1
-\name{batch}
2
-\Rdversion{1.1}
3
-\alias{batch}
4
-\title{
5
-  Stores information on the batch (e.g., chemistry plate) used to
6
-  process samples.
7
-}
8
-\description{
9
-  Parameters for estimating copy number are locus- and batch-specific.
10
-}
11
-\usage{
12
-batch(object)
13
-}
14
-\arguments{
15
-  \item{object}{An object of class \code{CrlmmSetList} or \code{CopyNumberSet}.
16
-  }
17
-}
18
-\value{
19
-  Typically, a character string or factor.
20
-}
21
-\author{
22
-  Rob Scharpf
23
-}
24
-\keyword{manip}
25
-
26 0
deleted file mode 100644
... ...
@@ -1,70 +0,0 @@
1
-\name{computeCopynumber}
2
-\alias{computeCopynumber}
3
-\title{Computes copy number}
4
-\description{
5
-  A function that transforms the quantile-normalized fluorescence
6
-  intensities of the polymorphic and nonpolymorphic probes to a copy
7
-  number scale.  
8
-  
9
-}
10
-\usage{
11
-computeCopynumber(object, CHR, bias.adj=FALSE, batch, SNRmin=5, cdfName,
12
-...)
13
-}
14
-\arguments{
15
-  \item{object}{object of class \code{CrlmmSetList}.}
16
-  \item{CHR}{Chromosome (an integer).  Use 23 for X and 24 for Y.}
17
-  \item{bias.adj}{Logical.  When TRUE, an extra iteration is performed
18
-    (see details) .}
19
-  \item{batch}{Factor.  Must be the same length as the number of samples
20
-    in the object.}
21
-  \item{SNRmin}{The minimum value for the SNR -- we suggest 5. Samples
22
-    with SNR below SNRmin are dropped.}
23
-  \item{cdfName}{Annotation package }
24
-  \item{\dots}{arguments to \code{.computeCopynumber}.}
25
-}
26
-
27
-\details{
28
-
29
-  One may altenatively use the \code{update} method (a wrapper for
30
-  \code{computeCopynumber}) to add a \code{CopyNumberSet} object to the
31
-  \code{CrlmmSetList} object.
32
-
33
-  This function requires 10 or more samples to estimate model
34
-  parameters.  Preferably, 70+ samples would be processed together in a
35
-  batch.
36
-  
37
-  This function translates the quantile-normalized fluorescence
38
-  intensities to the scale of copy number.  We assume that for any given
39
-  locus the median copy number is two for each batch. When
40
-  \code{bias.adj=TRUE}, an extra iteration is performed whereby samples
41
-  with a high posterior probability of having a non-normal copy number
42
-  are excluded.  The resulting within-genotype estimators of location
43
-  and scale are more robust to a large number of samples having a copy
44
-  number variant.
45
-
46
-  For details, see the technical report:
47
-
48
-Scharpf RB, Ruczinski I, Carvalho B, Doan B, Chakravarti A, and Irizarry
49
-  R. A multilevel model to address batch effects in copy number
50
-  estimation using SNP arrays
51
-  (http://www.bepress.com/cgi/viewcontent.cgi?article=1193&context=jhubiostat).
52
-
53
-
54
-}
55
-
56
-\value{
57
-  
58
-  An object of class \code{CrlmmSetList}.
59
-
60
-}
61
-
62
-\seealso{
63
-  \code{\link{update}},  \code{\linkS4class{CrlmmSetList}}, \code{\linkS4class{CopyNumberSet}},   \code{.computeCopynumber}
64
-}
65
-\author{Rob Scharpf}
66
-\keyword{manip}
67
-\keyword{models}
68
-\keyword{regression}
69
-\keyword{robust}
70
-
71 0
deleted file mode 100644
... ...
@@ -1,73 +0,0 @@
1
-\name{crlmm}
2
-\alias{crlmm}
3
-
4
-\title{Genotype oligonucleotide arrays with CRLMM}
5
-\description{
6
-  This is a faster and more efficient implementation of the CRLMM
7
-  algorithm, especially designed for Affymetrix SNP 5 and 6 arrays (to
8
-  be soon extended to other platforms).
9
-}
10
-\usage{
11
-crlmm(filenames, row.names=TRUE, col.names=TRUE,
12
-      probs=c(1/3, 1/3, 1/3), DF=6, SNRMin=5,
13
-      gender=NULL, save.it=FALSE, load.it=FALSE,
14
-      intensityFile, mixtureSampleSize=10^5,
15
-      eps=0.1, verbose=TRUE, cdfName, sns, recallMin=10,
16
-      recallRegMin=1000, returnParams=FALSE, badSNP=0.7)
17
-}
18
-
19
-\arguments{
20
-  \item{filenames}{'character' vector with CEL files to be genotyped.}
21
-  \item{row.names}{'logical'. Use rownames - SNP names?}
22
-  \item{col.names}{'logical'. Use colnames - Sample names?}
23
-  \item{probs}{'numeric' vector with priors for AA, AB and BB.}
24
-  \item{DF}{'integer' with number of degrees of freedom to use with t-distribution.}
25
-  \item{SNRMin}{'numeric' scalar defining the minimum SNR used to filter
26
-  out samples.}
27
-  \item{gender}{'integer' vector, with same length as 'filenames',
28
-    defining sex. (1 - male; 2 - female)}
29
-  \item{save.it}{'logical'. Save preprocessed data?}
30
-  \item{load.it}{'logical'. Load preprocessed data to speed up analysis?}
31
-  \item{intensityFile}{'character' with filename to be saved/loaded -
32
-    preprocessed data.}
33
-  \item{mixtureSampleSize}{Number of SNP's to be used with the mixture model.}
34
-  \item{eps}{Minimum change for mixture model.}
35
-  \item{verbose}{'logical'.}
36
-  \item{cdfName}{'character' defining the CDF name to use
37
-    ('GenomeWideSnp5', 'GenomeWideSnp6')}
38
-  \item{sns}{'character' vector with sample names to be used.}
39
-  \item{recallMin}{Minimum number of samples for recalibration.}
40
-  \item{recallRegMin}{Minimum number of SNP's for regression.}
41
-  \item{returnParams}{'logical'. Return recalibrated parameters.}
42
-  \item{badSNP}{'numeric'. Threshold to flag as bad SNP (affects batchQC)}
43
-}
44
-\value{
45
-  A \code{SnpSet} object.
46
-  \item{calls}{Genotype calls (1 - AA, 2 - AB, 3 - BB)}
47
-  \item{confs}{Confidence scores 'round(-1000*log2(1-p))'}
48
-  \item{SNPQC}{SNP Quality Scores}
49
-  \item{batchQC}{Batch Quality Score}
50
-  \item{params}{Recalibrated parameters}
51
-}
52
-\references{
53
-  Carvalho B, Bengtsson H, Speed TP, Irizarry RA. Exploration,
54
-  normalization, and genotype calls of high-density oligonucleotide SNP
55
-  array data. Biostatistics. 2007 Apr;8(2):485-99. Epub 2006 Dec
56
-  22. PMID: 17189563.
57
-
58
-  Carvalho B, Louis TA, Irizarry RA. Describing Uncertainty in
59
-  Genome-wide Genotype Calling. (in prep)
60
-}
61
-\examples{
62
-## this can be slow
63
-if (require(genomewidesnp5Crlmm) & require(hapmapsnp5)){
64
-  path <- system.file("celFiles", package="hapmapsnp5")
65
-
66
-  ## the filenames with full path...
67
-  ## very useful when genotyping samples not in the working directory
68
-  cels <- list.celfiles(path, full.names=TRUE)
69
-  (crlmmOutput <- crlmm(cels))
70
-}
71
-}
72
-\keyword{classif}
73
-
74 0
deleted file mode 100644
... ...
@@ -1,71 +0,0 @@
1
-\name{crlmmWrapper}
2
-\Rdversion{1.1}
3
-\alias{crlmmWrapper}
4
-\title{ Wrapper to quantile normalize and genotype Affymetrix 6.0 cel files.
5
-}
6
-\description{
7
-  Quantile normalizes the cel files to a target reference distribution
8
-  (both polymorphic and nonpolymorphic loci).  Genotype calls and
9
-  confidence scores are assigned using the crlmm algorithm.
10
-}
11
-\usage{
12
-crlmmWrapper(filenames, cdfName, load.it=FALSE,
13
-save.it=FALSE, splitByChr=TRUE, crlmmFile, intensityFile, rgFile, ...)
14
-}
15
-\arguments{
16
-  \item{filenames}{
17
-    Complete path to cel files
18
-  }
19
-  \item{cdfName}{
20
-    Annotation package (currently, only 'genomewidesnp6' is supported).
21
-    See \code{crlmm:::validCdfNames()}.
22
-  }
23
-  \item{load.it}{ Logical.  If TRUE, the wrapper function will try to
24
-    load the 'intensityFile' and 'crlmmFile'. When FALSE, the quantile
25
-    normalization and genotype calling steps are recomputed regardless
26
-    of whether these objects exist.}
27
-  \item{save.it}{ Logical. Whether to save intermediate files.  When
28
-    TRUE, the SnpSet object containing genotype calls is saved to the
29
-    file indicated by 'crlmmFile'. This can be useful if an error occurs
30
-    in the crlmmWrapper function after the genotyping has been completed.
31
-  }
32
-  \item{splitByChr}{
33
-    Logical. Whether to split results by chromosome (default is TRUE).
34
-    Helpful for datasets containing 50+ samples.  Files are saved as
35
-    \code{paste(dirname(crlmmFile), "crlmmSetList_", CHR, ".rda", sep="")}.
36
-  }
37
-  \item{crlmmFile}{Character string.  Name of file (including the
38
-    complete path) containing the genotype calls.  }
39
-  \item{intensityFile}{Character string.  Name of file (with
40
-    complete path) containing the quantile-normalized intensities.  }  
41
-  \item{rgFile}{Character string.  Name of file (including the
42
-    complete path) containing the RG intensities (only applicable for
43
-    illumina platform).  }
44
-  \item{\dots}{
45
-    additional arguments to function \code{readIdatFiles} (illumina
46
-    platform only)
47
-  }
48
-}
49
-\value{
50
-  An object of class \code{CrlmmSetList}
51
-}
52
-\author{
53
-  R. Scharpf
54
-}
55
-\seealso{
56
-  \code{\linkS4class{CrlmmSetList}}
57
-  \code{\link{crlmm}}
58
-}
59
-\examples{
60
-\dontrun{
61
-library(crlmm)
62
-library(genomewidesnp6Crlmm)
63
-celFiles <- list.files("PATH_TO_CELS", full.name=TRUE)
64
-crlmmSetList <- crlmmWrapper(celFiles, intensityFile="intensities.rda")
65
-}
66
-}
67
-% Add one or more standard keywords, see file 'KEYWORDS' in the
68
-% R documentation directory.
69
-\keyword{robust}
70
-\keyword{methods}
71
-\keyword{list}
72 0
deleted file mode 100644
... ...
@@ -1,74 +0,0 @@
1
-\name{readIdatFiles}
2
-\alias{readIdatFiles}
3
-
4
-\title{Reads Idat Files from Infinium II Illumina BeadChips}
5
-
6
-\description{
7
-  Reads intensity information for each bead type from
8
-  .idat files of Infinium II genotyping BeadChips}
9
-
10
-\usage{
11
-readIdatFiles(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path="",
12
-              arrayInfoColNames=list(barcode="SentrixBarcode_A",
13
-                                     position="SentrixPosition_A"),
14
-              highDensity=FALSE, sep="_",
15
-              fileExt=list(green="Grn.idat", red="Red.idat"),
16
-              saveDate=FALSE)
17
-}
18
-
19
-\arguments{
20
-  \item{sampleSheet}{\code{data.frame} containing Illumina sample sheet
21
-    information (for required columns, refer to BeadStudio Genotyping
22
-    guide - Appendix A).}
23
-  \item{arrayNames}{character vector containing names of arrays to be
24
-    read in.  If \code{NULL}, all arrays that can be found in the
25
-    specified working directory will be read in.}
26
-  \item{ids}{vector containing ids of probes to be read in.  If
27
-    \code{NULL} all probes found on the first array are read in.}
28
-  \item{path}{character string specifying the location of files to be
29
-    read by the function}
30
-  \item{arrayInfoColNames}{(used when \code{sampleSheet} is specified)
31
-    list containing elements 'barcode' which indicates column names in
32
-    the \code{sampleSheet} which contains the arrayNumber/barcode number
33
-    and 'position' which indicates the strip number.  In older style
34
-    sample sheets, this information is combined (usually in a column
35
-    named 'SentrixPosition') and this should be specified as
36
-    \code{list(barcode=NULL, position="SentrixPosition")}}
37
-  \item{highDensity}{logical (used when \code{sampleSheet} is
38
-    specified). If \code{TRUE}, array extensions '\_A', '\_B' in
39
-    sampleSheet are replaced with 'R01C01', 'R01C02' etc.}
40
-  \item{sep}{character string specifying separator used in .idat file
41
-    names.}
42
-  \item{fileExt}{list containing elements 'Green' and 'Red' which
43
-    specify the .idat file extension for the Cy3 and Cy5 channels.}
44
-  \item{saveDate}{logical.  Should the dates from each .idat be saved
45
-    with sample information?}
46
-}
47
-
48
-\details{
49
-The summarised Cy3 (G) and Cy5 (R) intensity, number of beads that
50
-were used in each channel and standard errors (all on the orginal scale)
51
-are read in from the .idat files.
52
-
53
-Where available, a \code{sampleSheet} data.frame, in the same format
54
-as used by BeadStudio (columns 'Sample\_ID', 'SentrixBarcode\_A' and
55
-'SentrixPosition\_A' are required) which keeps track of sample
56
-information can be specified.
57
-
58
-Thanks to Keith Baggerly who provided the code to read in the binary .idat files.
59
-}
60
-
61
-\value{
62
-  NChannelSet with intensity data (\code{R}, \code{G}), number of beads
63
-  (\code{Rnb}, \code{Gnb}) and standard errors (\code{Rse}, \code{Gse})
64
-  for each bead type.
65
-}
66
-
67
-\author{Matt Ritchie}
68
-
69
-\examples{
70
-
71
-#RG = readIdatFiles()
72
-
73
-}
74
-\keyword{IO}