Accessing and modifying information in MultiAssayExperiment — MultiAssayExperiment-methods • MultiAssayExperiment

A set of accessor and setter generic functions to extract either the sampleMap, the ExperimentList, colData, or metadata slots of a MultiAssayExperiment object

Usage

# S4 method for class 'MultiAssayExperiment'
sampleMap(x)

# S4 method for class 'MultiAssayExperiment'
experiments(x)

# S4 method for class 'MultiAssayExperiment'
colData(x, ...)

# S4 method for class 'MultiAssayExperiment'
drops(x)

# S4 method for class 'MultiAssayExperiment,DataFrame'
sampleMap(object) <- value

# S4 method for class 'MultiAssayExperiment,ANY'
sampleMap(object) <- value

drops(x, ...) <- value

# S4 method for class 'MultiAssayExperiment,ExperimentList'
experiments(object) <- value

# S4 method for class 'MultiAssayExperiment,List'
experiments(object) <- value

# S4 method for class 'MultiAssayExperiment,DataFrame'
colData(x) <- value

# S4 method for class 'MultiAssayExperiment,ANY'
colData(x) <- value

# S4 method for class 'MultiAssayExperiment'
drops(x, ...) <- value

# S4 method for class 'MultiAssayExperiment'
x$name <- value

# S4 method for class 'MultiAssayExperiment'
names(x) <- value

# S4 method for class 'MultiAssayExperiment,List'
colnames(x) <- value

# S4 method for class 'MultiAssayExperiment,list'
colnames(x) <- value

# S4 method for class 'MultiAssayExperiment'
x$name

# S4 method for class 'MultiAssayExperiment'
metadata(x, ...)

# S4 method for class 'MultiAssayExperiment'
metadata(x, ...) <- value

Arguments

...: Argument not in use
object, x: A MultiAssayExperiment object
value: See details.
name: A column in colData

Value

Accessors: Either a sampleMap, ExperimentList, or DataFrame object

Setters: A MultiAssayExperiment object

Accessors

Eponymous names for accessing MultiAssayExperiment slots with the exception of the ExperimentList accessor named experiments.

colData: Access the colData slot
sampleMap: Access the sampleMap slot
experiments: Access the ExperimentList slot
[[: Access the ExperimentList slot
$: Access a column in colData
drops: Get a vector of dropped ExperimentList names

Setters

Setter method values (i.e., 'function(x) <- value'):

experiments<-: An ExperimentList object containing experiment data of supported classes
sampleMap<-: A DataFrame object relating samples to biological units and assays
colData<-: A DataFrame object describing the biological units
metadata<-: A list object of metadata
[[<-: Equivalent to the experiments<- setter method for convenience
$<-: A vector to replace the indicated column in colData
drops<-: Trace ExperimentList names that have been removed

Examples

## Load example MultiAssayExperiment
example(MultiAssayExperiment)
#> 
#> MltAsE> ## Run the example ExperimentList
#> MltAsE> example("ExperimentList")
#> 
#> ExprmL> ## Create an empty ExperimentList instance
#> ExprmL> ExperimentList()
#> ExperimentList class object of length 0:
#>  
#> ExprmL> ## Create array matrix and AnnotatedDataFrame to create an ExpressionSet class
#> ExprmL> arraydat <- matrix(data = seq(101, length.out = 20), ncol = 4,
#> ExprmL+     dimnames = list(
#> ExprmL+         c("ENST00000294241", "ENST00000355076",
#> ExprmL+         "ENST00000383706","ENST00000234812", "ENST00000383323"),
#> ExprmL+         c("array1", "array2", "array3", "array4")
#> ExprmL+     ))
#> 
#> ExprmL> colDat <- data.frame(slope53 = rnorm(4),
#> ExprmL+     row.names = c("array1", "array2", "array3", "array4"))
#> 
#> ExprmL> ## SummarizedExperiment constructor
#> ExprmL> exprdat <- SummarizedExperiment::SummarizedExperiment(arraydat,
#> ExprmL+     colData = colDat)
#> 
#> ExprmL> ## Create a sample methylation dataset
#> ExprmL> methyldat <- matrix(data = seq(1, length.out = 25), ncol = 5,
#> ExprmL+     dimnames = list(
#> ExprmL+         c("ENST00000355076", "ENST00000383706",
#> ExprmL+           "ENST00000383323", "ENST00000234812", "ENST00000294241"),
#> ExprmL+         c("methyl1", "methyl2", "methyl3",
#> ExprmL+           "methyl4", "methyl5")
#> ExprmL+     ))
#> 
#> ExprmL> ## Create a sample RNASeqGene dataset
#> ExprmL> rnadat <- matrix(
#> ExprmL+     data = sample(c(46851, 5, 19, 13, 2197, 507,
#> ExprmL+         84318, 126, 17, 21, 23979, 614), size = 20, replace = TRUE),
#> ExprmL+     ncol = 4,
#> ExprmL+     dimnames = list(
#> ExprmL+         c("XIST", "RPS4Y1", "KDM5D", "ENST00000383323", "ENST00000234812"),
#> ExprmL+         c("samparray1", "samparray2", "samparray3", "samparray4")
#> ExprmL+     ))
#> 
#> ExprmL> ## Create a mock RangedSummarizedExperiment from a data.frame
#> ExprmL> rangedat <- data.frame(chr="chr2", start = 11:15, end = 12:16,
#> ExprmL+     strand = c("+", "-", "+", "*", "."),
#> ExprmL+     samp0 = c(0,0,1,1,1), samp1 = c(1,0,1,0,1), samp2 = c(0,1,0,1,0),
#> ExprmL+     row.names = c(paste0("ENST", "00000", 135411:135414), "ENST00000383323"))
#> 
#> ExprmL> rangeSE <- SummarizedExperiment::makeSummarizedExperimentFromDataFrame(rangedat)
#> 
#> ExprmL> ## Combine to a named list and call the ExperimentList constructor function
#> ExprmL> assayList <- list(Affy = exprdat, Methyl450k = methyldat, RNASeqGene = rnadat,
#> ExprmL+                 GISTIC = rangeSE)
#> 
#> ExprmL> ## Use the ExperimentList constructor
#> ExprmL> ExpList <- ExperimentList(assayList)
#> 
#> MltAsE> ## Create sample maps for each experiment
#> MltAsE> exprmap <- data.frame(
#> MltAsE+     primary = c("Jack", "Jill", "Barbara", "Bob"),
#> MltAsE+     colname = c("array1", "array2", "array3", "array4"),
#> MltAsE+     stringsAsFactors = FALSE)
#> 
#> MltAsE> methylmap <- data.frame(
#> MltAsE+     primary = c("Jack", "Jack", "Jill", "Barbara", "Bob"),
#> MltAsE+     colname = c("methyl1", "methyl2", "methyl3", "methyl4", "methyl5"),
#> MltAsE+     stringsAsFactors = FALSE)
#> 
#> MltAsE> rnamap <- data.frame(
#> MltAsE+     primary = c("Jack", "Jill", "Bob", "Barbara"),
#> MltAsE+     colname = c("samparray1", "samparray2", "samparray3", "samparray4"),
#> MltAsE+     stringsAsFactors = FALSE)
#> 
#> MltAsE> gistmap <- data.frame(
#> MltAsE+     primary = c("Jack", "Bob", "Jill"),
#> MltAsE+     colname = c("samp0", "samp1", "samp2"),
#> MltAsE+     stringsAsFactors = FALSE)
#> 
#> MltAsE> ## Combine as a named list and convert to a DataFrame
#> MltAsE> maplist <- list(Affy = exprmap, Methyl450k = methylmap,
#> MltAsE+     RNASeqGene = rnamap, GISTIC = gistmap)
#> 
#> MltAsE> ## Create a sampleMap
#> MltAsE> sampMap <- listToMap(maplist)
#> 
#> MltAsE> ## Create an example phenotype data
#> MltAsE> colDat <- data.frame(sex = c("M", "F", "M", "F"), age = 38:41,
#> MltAsE+     row.names = c("Jack", "Jill", "Bob", "Barbara"))
#> 
#> MltAsE> ## Create a MultiAssayExperiment instance
#> MltAsE> mae <- MultiAssayExperiment(experiments = ExpList, colData = colDat,
#> MltAsE+     sampleMap = sampMap)

## Access the sampleMap
sampleMap(mae)
#> DataFrame with 16 rows and 3 columns
#>          assay     primary     colname
#>       <factor> <character> <character>
#> 1   Affy              Jack      array1
#> 2   Affy              Jill      array2
#> 3   Affy           Barbara      array3
#> 4   Affy               Bob      array4
#> 5   Methyl450k        Jack     methyl1
#> ...        ...         ...         ...
#> 12  RNASeqGene         Bob  samparray3
#> 13  RNASeqGene     Barbara  samparray4
#> 14  GISTIC            Jack       samp0
#> 15  GISTIC             Bob       samp1
#> 16  GISTIC            Jill       samp2

## Replacement method for a MultiAssayExperiment sampleMap
sampleMap(mae) <- S4Vectors::DataFrame()
#> harmonizing input:
#>   removing 4 colData rownames not in sampleMap 'primary'

## Access the ExperimentList
experiments(mae)
#> ExperimentList class object of length 0:
#>  

## Replace with an empty ExperimentList
experiments(mae) <- ExperimentList()

## Access the metadata
metadata(mae)
#> list()

## Replace metadata with a list
metadata(mae) <- list(runDate =
    format(Sys.time(), "%B %d, %Y"))

## Access the colData
colData(mae)
#> DataFrame with 0 rows and 2 columns

## Access a column in colData
mae$age
#> integer(0)

## Replace a column in colData
mae$age <- mae$age + 1