MultiAssayExperiment objectmultiAssayExperiment class objectRangedRaggedAssay classThis vignette is the current working document for developing the MultiAssayExperiment class and methods. See a built html version.
See the API wiki by typing:
API()Here is an overview of the design:
empty <- MultiAssayExperiment()
empty## A "MultiAssayExperiment" object of 0 listed
## experiments with no user-defined names and respective classes.
## Containing an "Elist" class object of length 0:
## To access slots use:
## Elist() - to obtain the "Elist" of experiment instances
## pData() - for the phenotype "DataFrame"
## sampleMap() - for the sample availability "DataFrame"
## metadata() - for the metadata object of 'ANY' class
## See also: subsetByAssay(), subsetByFeature(), subsetBySample()slotNames(empty)## [1] "Elist" "pData" "sampleMap" "metadata" "drops"class(Elist(empty)) #Elist## [1] "Elist"
## attr(,"package")
## [1] "biocMultiAssay"class(pData(empty)) #DataFrame## [1] "DataFrame"
## attr(,"package")
## [1] "S4Vectors"class(sampleMap(empty)) #DataFrame## [1] "DataFrame"
## attr(,"package")
## [1] "S4Vectors"class(metadata(empty)) #NULL (class "ANY")## [1] "NULL"methods(class="MultiAssayExperiment")## [1] [ assay colnames Elist Elist<-
## [6] getHits isEmpty length metadata names
## [11] pData rownames sampleMap sampleMap<- show
## [16] subset
## see '?methods' for accessing help and source codemethods(class="RangedRaggedAssay")## [1] ! != [
## [4] [[ [[<- [<-
## [7] %in% < <=
## [10] == > >=
## [13] $ $<- aggregate
## [16] anyNA append as.character
## [19] as.complex as.data.frame as.env
## [22] as.integer as.list as.logical
## [25] as.numeric as.raw assay
## [28] by c classNameForDisplay
## [31] coerce colnames compare
## [34] do.call droplevels duplicated
## [37] elementLengths elementMetadata elementMetadata<-
## [40] elementType end end<-
## [43] endoapply eval expand.grid
## [46] extractROWS Filter getHits
## [49] getListElement head ifelse
## [52] is.na is.unsorted isEmpty
## [55] lapply length lengths
## [58] match mcols mcols<-
## [61] mendoapply metadata metadata<-
## [64] names names<- ncol
## [67] nrow NROW order
## [70] parallelSlotNames range rank
## [73] Reduce relist rename
## [76] rep rep.int replaceROWS
## [79] revElements rownames ROWNAMES
## [82] sapply score score<-
## [85] shiftApply show showAsCell
## [88] sort split start
## [91] start<- strand strand<-
## [94] subset table tail
## [97] tapply unique unlist
## [100] unsplit updateObject values
## [103] values<- width width<-
## [106] window with within
## [109] xtabs xtfrm
## see '?methods' for accessing help and source codegetMethod("colnames", "RangedRaggedAssay")## Method Definition:
##
## function (x, do.NULL = TRUE, prefix = "col")
## {
## .local <- function (x)
## base::names(x)
## .local(x)
## }
## <environment: namespace:biocMultiAssay>
##
## Signatures:
## x
## target "RangedRaggedAssay"
## defined "RangedRaggedAssay"Subsetting of samples and features is harmonized through some generic functions:
methods("rownames") # features## [1] rownames,ANY-method
## [2] rownames,DataFrame-method
## [3] rownames,DataFrameList-method
## [4] rownames,ExpressionSet-method
## [5] rownames,MultiAssayExperiment-method
## [6] rownames,RangedData-method
## [7] rownames,RangedRaggedAssay-method
## [8] rownames,RangedSummarizedExperiment-method
## see '?methods' for accessing help and source codemethods("colnames") # samples## [1] colnames,ANY-method
## [2] colnames,CompressedSplitDataFrameList-method
## [3] colnames,DataFrame-method
## [4] colnames,DataFrameList-method
## [5] colnames,ExpressionSet-method
## [6] colnames,MultiAssayExperiment-method
## [7] colnames,RangedData-method
## [8] colnames,RangedRaggedAssay-method
## [9] colnames,RangedSelection-method
## [10] colnames,SDFLWrapperForTransform-method
## [11] colnames,SimpleSplitDataFrameList-method
## see '?methods' for accessing help and source codeIn this example we have 4 patients, and a bit of metadata on them:
masPheno <- data.frame(sex=c("M", "F", "M", "F"),
age=38:41,
row.names=c("Jack", "Jill", "Bob", "Barbara"))
masPheno## sex age
## Jack M 38
## Jill F 39
## Bob M 40
## Barbara F 41We have three matrix-like datasets. First let’s say expression data:
library(Biobase)
(arraydat <- matrix(seq(101, 108), ncol=4, dimnames=list(c("ENST00000294241", "ENST00000355076"), c("array1", "array2", "array3", "array4"))))## array1 array2 array3 array4
## ENST00000294241 101 103 105 107
## ENST00000355076 102 104 106 108arraypdat <- as(data.frame(slope53=rnorm(4), row.names=c("array1", "array2", "array3", "array4")), "AnnotatedDataFrame")
exprdat <- ExpressionSet(assayData=arraydat, phenoData=arraypdat)
exprdat## ExpressionSet (storageMode: lockedEnvironment)
## assayData: 2 features, 4 samples
## element names: exprs
## protocolData: none
## phenoData
## sampleNames: array1 array2 array3 array4
## varLabels: slope53
## varMetadata: labelDescription
## featureData: none
## experimentData: use 'experimentData(object)'
## Annotation:The following map matches pData sample names to exprdata sample names. Note that row orders aren’t initially matched up.
(exprmap <- data.frame(master=rownames(masPheno)[c(1, 2, 4, 3)],
assay=c("array1", "array2", "array3", "array4"), stringsAsFactors = FALSE))## master assay
## 1 Jack array1
## 2 Jill array2
## 3 Barbara array3
## 4 Bob array4Now methylation data. It uses gene identifiers also, but measures a partially overlapping set of genes. For fun, let’s store this as a simple matrix. Also, it contains a replicate for one of the patients.
(methyldat <- matrix(1:10, ncol=5,
dimnames=list(c("ENST00000355076", "ENST00000383706"),
c("methyl1", "methyl2", "methyl3", "methyl4", "methyl5"))))## methyl1 methyl2 methyl3 methyl4 methyl5
## ENST00000355076 1 3 5 7 9
## ENST00000383706 2 4 6 8 10The following map matches pData sample names to methyldat sample names.
(methylmap <- data.frame(master = c("Jack", "Jack", "Jill", "Barbara", "Bob"),
assay = c("methyl1", "methyl2", "methyl3", "methyl4", "methyl5"), stringsAsFactors = FALSE))## master assay
## 1 Jack methyl1
## 2 Jack methyl2
## 3 Jill methyl3
## 4 Barbara methyl4
## 5 Bob methyl5Now we have a microRNA platform, which has no common identifiers. It is also missing data for Jill. Just for fun, let’s use the same sample naming convention as we did for arrays.
(microdat <- matrix(201:212, ncol=3,
dimnames=list(c("hsa-miR-21", "hsa-miR-191", "hsa-miR-148a", "hsa-miR148b"),
c("micro1", "micro2", "micro3"))))## micro1 micro2 micro3
## hsa-miR-21 201 205 209
## hsa-miR-191 202 206 210
## hsa-miR-148a 203 207 211
## hsa-miR148b 204 208 212And the following map matches pData sample names to microdat sample names.
(micromap <- data.frame(master = c("Jack", "Barbara", "Bob"),
assay = c("micro1", "micro2", "micro3"), stringsAsFactors = FALSE))## master assay
## 1 Jack micro1
## 2 Barbara micro2
## 3 Bob micro3Let’s include a GRangesList:
suppressPackageStartupMessages(library(GenomicRanges))
gr1 <-
GRanges(seqnames = "chr3", ranges = IRanges(58000000, 59502360), #completely encompasses ENST00000355076
strand = "+", score = 5L, GC = 0.45)
gr2 <-
GRanges(seqnames = c("chr3", "chr3"),
ranges = IRanges(c(58493000, 3), width=9000), #first is within ENST0000035076
strand = c("+", "-"), score = 3:4, GC = c(0.3, 0.5))
gr3 <-
GRanges(seqnames = c("chr1", "chr2"),
ranges = IRanges(c(1, 4), c(3, 9)),
strand = c("-", "-"), score = c(6L, 2L), GC = c(0.4, 0.1))
grl <- GRangesList("gr1" = gr1, "gr2" = gr2, "gr3" = gr3)
names(grl) <- c("snparray1", "snparray2", "snparray3")
grl## GRangesList object of length 3:
## $snparray1
## GRanges object with 1 range and 2 metadata columns:
## seqnames ranges strand | score GC
## <Rle> <IRanges> <Rle> | <integer> <numeric>
## [1] chr3 [58000000, 59502360] + | 5 0.45
##
## $snparray2
## GRanges object with 2 ranges and 2 metadata columns:
## seqnames ranges strand | score GC
## [1] chr3 [58493000, 58501999] + | 3 0.3
## [2] chr3 [ 3, 9002] - | 4 0.5
##
## $snparray3
## GRanges object with 2 ranges and 2 metadata columns:
## seqnames ranges strand | score GC
## [1] chr1 [1, 3] - | 6 0.4
## [2] chr2 [4, 9] - | 2 0.1
##
## -------
## seqinfo: 3 sequences from an unspecified genome; no seqlengthsThe following data.frame matches pData sample to the GRangesList:
(rangemap <- data.frame(master = c("Jack", "Jill", "Jill"),
assay = c("snparray1", "snparray2", "snparray3"), stringsAsFactors = FALSE))## master assay
## 1 Jack snparray1
## 2 Jill snparray2
## 3 Jill snparray3Adding the new RangedSummarizedExperiment class:
Create a GenomicRangesList object for the RangedSummarizedExperiment:
library(SummarizedExperiment)
nrows <- 5; ncols <- 4
counts <- matrix(runif(nrows * ncols, 1, 1e4), nrows)
rowRanges <- GRanges(rep(c("chr1", "chr2"), c(2, nrows - 2)),
IRanges(floor(runif(nrows, 1e5, 1e6)), width=100),
strand=sample(c("+", "-"), nrows, TRUE),
feature_id=sprintf("ID\\%03d", 1:nrows))
names(rowRanges) <- letters[1:5]
colData <- DataFrame(Treatment=rep(c("ChIP", "Input"), 2),
row.names= c("mysnparray1", "mysnparray2", "mysnparray3", "mysnparray4"))
rse <- SummarizedExperiment(assays=SimpleList(counts=counts),
rowRanges=rowRanges, colData=colData)(rangemap2 <- data.frame(master = c("Jack", "Jill", "Bob", "Barbara"),
assay = c("mysnparray1", "mysnparray2", "mysnparray3", "mysnparray4"), stringsAsFactors = FALSE))## master assay
## 1 Jack mysnparray1
## 2 Jill mysnparray2
## 3 Bob mysnparray3
## 4 Barbara mysnparray4MultiAssayExperiment objectCreate an ID map for all available experiments. Names required, and must be identical to names of Elist.
listmap <- list(exprmap, methylmap, micromap, rangemap, rangemap2)
names(listmap) <- c("Affy", "Methyl 450k", "Mirna", "CNV gistic", "CNV gistic2")
listmap## $Affy
## master assay
## 1 Jack array1
## 2 Jill array2
## 3 Barbara array3
## 4 Bob array4
##
## $`Methyl 450k`
## master assay
## 1 Jack methyl1
## 2 Jack methyl2
## 3 Jill methyl3
## 4 Barbara methyl4
## 5 Bob methyl5
##
## $Mirna
## master assay
## 1 Jack micro1
## 2 Barbara micro2
## 3 Bob micro3
##
## $`CNV gistic`
## master assay
## 1 Jack snparray1
## 2 Jill snparray2
## 3 Jill snparray3
##
## $`CNV gistic2`
## master assay
## 1 Jack mysnparray1
## 2 Jill mysnparray2
## 3 Bob mysnparray3
## 4 Barbara mysnparray4Allowing for the possibility of ID maps entered as dataframes, convert to conventional list:
dfmap <- biocMultiAssay:::.convertList(listmap)
toListMap(dfmap, "assayname")## $Affy
## DataFrame with 4 rows and 2 columns
## master assay
## <Rle> <character>
## 1 Jack array1
## 2 Jill array2
## 3 Barbara array3
## 4 Bob array4
##
## $`CNV gistic`
## DataFrame with 3 rows and 2 columns
## master assay
## <Rle> <character>
## 1 Jack snparray1
## 2 Jill snparray2
## 3 Jill snparray3
##
## $`CNV gistic2`
## DataFrame with 4 rows and 2 columns
## master assay
## <Rle> <character>
## 1 Jack mysnparray1
## 2 Jill mysnparray2
## 3 Bob mysnparray3
## 4 Barbara mysnparray4
##
## $`Methyl 450k`
## DataFrame with 5 rows and 2 columns
## master assay
## <Rle> <character>
## 1 Jack methyl1
## 2 Jack methyl2
## 3 Jill methyl3
## 4 Barbara methyl4
## 5 Bob methyl5
##
## $Mirna
## DataFrame with 3 rows and 2 columns
## master assay
## <Rle> <character>
## 1 Jack micro1
## 2 Barbara micro2
## 3 Bob micro3Create an named list of experiments objlist for the MultiAssay function
objlist <- list("Affy" = exprdat, "Methyl 450k" = methyldat, "Mirna" = microdat, "CNV gistic" = grl, "CNV gistic2" = rse)multiAssayExperiment class objectmyMultiAssay <- MultiAssayExperiment(objlist, masPheno, dfmap)
myMultiAssay## A "MultiAssayExperiment" object of 5 listed
## experiments with user-defined names and respective classes.
## Containing an "Elist" class object of length 5:
## [1] Affy: "ExpressionSet" - 2 rows, 4 columns
## [2] Methyl 450k: "matrix" - 2 rows, 5 columns
## [3] Mirna: "matrix" - 4 rows, 3 columns
## [4] CNV gistic: "RangedRaggedAssay" - 5 rows, 3 columns
## [5] CNV gistic2: "RangedSummarizedExperiment" - 5 rows, 4 columns
## To access slots use:
## Elist() - to obtain the "Elist" of experiment instances
## pData() - for the phenotype "DataFrame"
## sampleMap() - for the sample availability "DataFrame"
## metadata() - for the metadata object of 'ANY' class
## See also: subsetByAssay(), subsetByFeature(), subsetBySample()Elist(myMultiAssay)## "Elist" class object of length 5:
## [1] Affy: "ExpressionSet" - 2 rows, 4 columns
## [2] Methyl 450k: "matrix" - 2 rows, 5 columns
## [3] Mirna: "matrix" - 4 rows, 3 columns
## [4] CNV gistic: "RangedRaggedAssay" - 5 rows, 3 columns
## [5] CNV gistic2: "RangedSummarizedExperiment" - 5 rows, 4 columnspData(myMultiAssay)## DataFrame with 4 rows and 2 columns
## sex age
## <factor> <integer>
## Jack M 38
## Jill F 39
## Bob M 40
## Barbara F 41sampleMap(myMultiAssay)## DataFrame with 19 rows and 3 columns
## master assay assayname
## <Rle> <character> <Rle>
## 1 Jack array1 Affy
## 2 Jill array2 Affy
## 3 Barbara array3 Affy
## 4 Bob array4 Affy
## 5 Jack methyl1 Methyl 450k
## ... ... ... ...
## 15 Jill snparray3 CNV gistic
## 16 Jack mysnparray1 CNV gistic2
## 17 Jill mysnparray2 CNV gistic2
## 18 Bob mysnparray3 CNV gistic2
## 19 Barbara mysnparray4 CNV gistic2metadata(myMultiAssay) ## NULLRangedRaggedAssay classNote that the GRangesList got converted to a RangedRaggedAssay, which has some additional methods:
class(Elist(myMultiAssay)[[4]])## [1] "RangedRaggedAssay"
## attr(,"package")
## [1] "biocMultiAssay"rownames(Elist(myMultiAssay)[[4]])## [1] "1" "1" "2" "1" "2"colnames(Elist(myMultiAssay)[[4]])## [1] "snparray1" "snparray2" "snparray3"assay(Elist(myMultiAssay)[[4]])## DataFrame with 5 rows and 2 columns
## score GC
## <integer> <numeric>
## 1 5 0.45
## 2 3 0.30
## 3 4 0.50
## 4 6 0.40
## 5 2 0.10MultiAssayView_cl <- MultiAssayView(myMultiAssay, 2:1, "colnames")
MultiAssayView_cl## A "MultiAssayView" class object of length 5:
## Query: Jill, Jack
## Viewed by: "colnames"
## [1] Affy: 2 colnames
## [2] Methyl 450k: 3 colnames
## [3] Mirna: 1 colname
## [4] CNV gistic: 3 colnames
## [5] CNV gistic2: 2 colnamesMultiAssayView class to subsetsubMultiAssay <- subset(myMultiAssay, MultiAssayView_cl)
as.list(Elist(subMultiAssay))
subset(subMultiAssay, c(TRUE, FALSE, FALSE, TRUE, FALSE), "assays", drop = TRUE)[[1]] %>% exprs
subMultiAssayEndogenous operation, returns a MultiAssay object containing Elist of length 1, map of length 1, and pData for only Jack, Barbara, and Bob. The “Mirna” argument is used to index the Elist object using [, so could also be integer or logical:
subset(myMultiAssay, "Mirna", "assays")## A "MultiAssayExperiment" object of 1 listed
## experiment with a user-defined name and respective class.
## Containing an "Elist" class object of length 1:
## [1] Mirna: "matrix" - 4 rows, 3 columns
## To access slots use:
## Elist() - to obtain the "Elist" of experiment instances
## pData() - for the phenotype "DataFrame"
## sampleMap() - for the sample availability "DataFrame"
## metadata() - for the metadata object of 'ANY' class
## See also: subsetByAssay(), subsetByFeature(), subsetBySample()The bracket method for the MultiAssayExperiment returns a specified subset of the data. The positions within the bracket operator, indicate rownames, colnames, and assays respectively. To subset by a particular assay, one can use this syntax:
myMultiAssay[,,"Mirna"]## A "MultiAssayExperiment" object of 1 listed
## experiment with a user-defined name and respective class.
## Containing an "Elist" class object of length 1:
## [1] Mirna: "matrix" - 4 rows, 3 columns
## To access slots use:
## Elist() - to obtain the "Elist" of experiment instances
## pData() - for the phenotype "DataFrame"
## sampleMap() - for the sample availability "DataFrame"
## metadata() - for the metadata object of 'ANY' class
## See also: subsetByAssay(), subsetByFeature(), subsetBySample()This operation returns a MultiAssayExperiment class, with any Elist element not containing the feature having zero rows.
Returns object of class MultiAssayView:
MultiAssayView(myMultiAssay, "ENST00000355076", "rownames") Returns MultiAssayExperiment where Affy and Methyl 450k contain only ENST0000035076 row, and “Mirna” and “CNV gistic” have zero rows: (drop argument is set to TRUE by default)
featSubsetted0 <- subset(myMultiAssay, "ENST00000355076", "rownames")
class(featSubsetted0)## [1] "MultiAssayExperiment"
## attr(,"package")
## [1] "biocMultiAssay"class(Elist(featSubsetted0))## [1] "Elist"
## attr(,"package")
## [1] "biocMultiAssay"Elist(featSubsetted0)## "Elist" class object of length 2:
## [1] Affy: "ExpressionSet" - 1 rows, 4 columns
## [2] Methyl 450k: "matrix" - 1 rows, 5 columns[ methodmyMultiAssay["ENST00000355076",,]## A "MultiAssayExperiment" object of 2 listed
## experiments with user-defined names and respective classes.
## Containing an "Elist" class object of length 2:
## [1] Affy: "ExpressionSet" - 1 rows, 4 columns
## [2] Methyl 450k: "matrix" - 1 rows, 5 columns
## To access slots use:
## Elist() - to obtain the "Elist" of experiment instances
## pData() - for the phenotype "DataFrame"
## sampleMap() - for the sample availability "DataFrame"
## metadata() - for the metadata object of 'ANY' class
## See also: subsetByAssay(), subsetByFeature(), subsetBySample()In the following, Affy ExpressionSet keeps both rows but with their order reversed, and Methyl 450k keeps only its second row.
featSubsetted <- subset(myMultiAssay, c("ENST00000355076", "ENST00000294241"), "rownames")
exprs(Elist(myMultiAssay)[[1]])
exprs(Elist(featSubsetted)[[1]])Note that the output of this function could be used as the input for subset.
MultiAssayView(myMultiAssay, c("ENST00000355076", "ENST00000294241"), "rownames") See arguments to IRanges::subsetByOverlaps for flexible types of subsetting. The first two arguments are for subset, the rest passed on through “…”:
rangeSubset <- GRanges(seqnames = c("chr1"), strand = c("-", "+", "-"), ranges = IRanges(start = c(1, 4, 6), width = 3))
subsetted <- subset(myMultiAssay, rangeSubset, "rownames", maxgap = 2L, type = "within")
Elist(subsetted)## "Elist" class object of length 1:
## [1] CNV gistic: "RangedRaggedAssay" - 1 rows, 3 columnsmyMultiAssay[rangeSubset, , ]## A "MultiAssayExperiment" object of 1 listed
## experiment with a user-defined name and respective class.
## Containing an "Elist" class object of length 1:
## [1] CNV gistic: "RangedRaggedAssay" - 1 rows, 3 columns
## To access slots use:
## Elist() - to obtain the "Elist" of experiment instances
## pData() - for the phenotype "DataFrame"
## sampleMap() - for the sample availability "DataFrame"
## metadata() - for the metadata object of 'ANY' class
## See also: subsetByAssay(), subsetByFeature(), subsetBySample()myMultiAssay[c("ENST00000355076", "ENST00000294241"), , ]## A "MultiAssayExperiment" object of 2 listed
## experiments with user-defined names and respective classes.
## Containing an "Elist" class object of length 2:
## [1] Affy: "ExpressionSet" - 2 rows, 4 columns
## [2] Methyl 450k: "matrix" - 1 rows, 5 columns
## To access slots use:
## Elist() - to obtain the "Elist" of experiment instances
## pData() - for the phenotype "DataFrame"
## sampleMap() - for the sample availability "DataFrame"
## metadata() - for the metadata object of 'ANY' class
## See also: subsetByAssay(), subsetByFeature(), subsetBySample()myMultiAssay[, c("Jack", "Jill"), ]## A "MultiAssayExperiment" object of 5 listed
## experiments with user-defined names and respective classes.
## Containing an "Elist" class object of length 5:
## [1] Affy: "ExpressionSet" - 2 rows, 2 columns
## [2] Methyl 450k: "matrix" - 2 rows, 3 columns
## [3] Mirna: "matrix" - 4 rows, 1 columns
## [4] CNV gistic: "RangedRaggedAssay" - 5 rows, 3 columns
## [5] CNV gistic2: "RangedSummarizedExperiment" - 5 rows, 2 columns
## To access slots use:
## Elist() - to obtain the "Elist" of experiment instances
## pData() - for the phenotype "DataFrame"
## sampleMap() - for the sample availability "DataFrame"
## metadata() - for the metadata object of 'ANY' class
## See also: subsetByAssay(), subsetByFeature(), subsetBySample()myMultiAssay[, , "Mirna"]## A "MultiAssayExperiment" object of 1 listed
## experiment with a user-defined name and respective class.
## Containing an "Elist" class object of length 1:
## [1] Mirna: "matrix" - 4 rows, 3 columns
## To access slots use:
## Elist() - to obtain the "Elist" of experiment instances
## pData() - for the phenotype "DataFrame"
## sampleMap() - for the sample availability "DataFrame"
## metadata() - for the metadata object of 'ANY' class
## See also: subsetByAssay(), subsetByFeature(), subsetBySample()exprss1 <- matrix(rnorm(16), ncol = 4,
dimnames = list(sprintf("ENST00000%i", sample(288754:290000, 4)),
c("Jack", "Jill", "Bob", "Bobby")))
exprss2 <- matrix(rnorm(16), ncol = 4,
dimnames = list(sprintf("ENST00000%i", sample(288754:290000, 4)),
c("Jack", "Jane", "Bob", "Bobby")))
doubleExp <- list("methyl 2k" = exprss1, "methyl 3k" = exprss2)
(genMapMA <- MultiAssayExperiment(doubleExp, masPheno))## Warning in MultiAssayExperiment(doubleExp, masPheno): sampleMap not
## provided, map will be generated## Warning in .generateMap(pData, Elist): Data from rows:
## Bobby - methyl 2k
## Jane - methyl 3k
## Bobby - methyl 3k
## dropped due to missing phenotype data## A "MultiAssayExperiment" object of 2 listed
## experiments with user-defined names and respective classes.
## Containing an "Elist" class object of length 2:
## [1] methyl 2k: "matrix" - 4 rows, 3 columns
## [2] methyl 3k: "matrix" - 4 rows, 2 columns
## To access slots use:
## Elist() - to obtain the "Elist" of experiment instances
## pData() - for the phenotype "DataFrame"
## sampleMap() - for the sample availability "DataFrame"
## metadata() - for the metadata object of 'ANY' class
## See also: subsetByAssay(), subsetByFeature(), subsetBySample()For now, fill the map with all observed samples:
sampleMap(MultiAssayExperiment(doubleExp, masPheno))## DataFrame with 5 rows and 3 columns
## master assay assayname
## <Rle> <character> <Rle>
## 1 Jack Jack methyl 2k
## 2 Jill Jill methyl 2k
## 3 Bob Bob methyl 2k
## 4 Jack Jack methyl 3k
## 5 Bob Bob methyl 3kAny data classes in the Elist object must support the following methods:
colnames()rownames()assay() #to return experimental data[Here is what happens if one of the methods doesn’t:
objlist2 <- objlist
objlist2[[2]] <- data.frame(objlist2[[2]])
invalid.obj <- try(MultiAssayExperiment(objlist2, masPheno, dfmap))
invalid.obj## [1] "Error in validObject(.Object) : \n invalid class \"Elist\" object: Element [2] of class 'data.frame' does not have method(s): assay\n"
## attr(,"class")
## [1] "try-error"
## attr(,"condition")
## <simpleError in validObject(.Object): invalid class "Elist" object: Element [2] of class 'data.frame' does not have method(s): assay>c() function for adding new assays to existing MultiAssayExperiment