View source: R/MultiAssayExperiment-class.R
MultiAssayExperiment | R Documentation |
MultiAssayExperiment
The constructor function for the MultiAssayExperiment combines
multiple data elements from the different hierarchies of data
(study, experiments, and samples). It can create instances where neither
a sampleMap
or a colData
set is provided. Please see the
MultiAssayExperiment API documentation for more information.
MultiAssayExperiment(
experiments = ExperimentList(),
colData = S4Vectors::DataFrame(),
sampleMap = S4Vectors::DataFrame(assay = factor(), primary = character(), colname =
character()),
metadata = list(),
drops = list()
)
experiments |
A |
colData |
A |
sampleMap |
A |
metadata |
An optional argument of "ANY" class (usually list) for content describing the experiments |
drops |
A |
A MultiAssayExperiment
object that can store
experiment and phenotype data
The colData
input can be either DataFrame
or data.frame
with
subsequent coercion to DataFrame. The rownames in the colData
must match
the colnames in the experiments if no sampleMap is provided.
The experiments
input can be of class SimpleList
or list
.
This input becomes the ExperimentList
. Each element of the
input list
or List
must be named, rectangular with two dimensions, and
have dimnames
.
The sampleMap
can either be input as DataFrame
or
data.frame
with eventual coercion to DataFrame
. The sampleMap
relates
biological units and biological measurements within each assay. Each row in
the sampleMap
is a single such link. The standard column names of the
sampleMap
are "assay", "primary", and "colname". Note that the "assay"
column is a factor corresponding to the names of each experiment in the
ExperimentList
. In the case where these names do not match between the
sampleMap
and the experiments, the documented experiments in the
sampleMap
take precedence and experiments are dropped by the harmonization
procedure. The constructor function will generate a sampleMap
in the case
where it is not provided and this method may be a 'safer' alternative for
creating the MultiAssayExperiment
(so long as the rownames are identical
in the colData
, if provided). An empty sampleMap
may produce empty
experiments if the levels of the "assay" factor in the sampleMap
do not
match the names in the ExperimentList
.
MultiAssayExperiment
## Run the example ExperimentList
example("ExperimentList")
## Create sample maps for each experiment
exprmap <- data.frame(
primary = c("Jack", "Jill", "Barbara", "Bob"),
colname = c("array1", "array2", "array3", "array4"),
stringsAsFactors = FALSE)
methylmap <- data.frame(
primary = c("Jack", "Jack", "Jill", "Barbara", "Bob"),
colname = c("methyl1", "methyl2", "methyl3", "methyl4", "methyl5"),
stringsAsFactors = FALSE)
rnamap <- data.frame(
primary = c("Jack", "Jill", "Bob", "Barbara"),
colname = c("samparray1", "samparray2", "samparray3", "samparray4"),
stringsAsFactors = FALSE)
gistmap <- data.frame(
primary = c("Jack", "Bob", "Jill"),
colname = c("samp0", "samp1", "samp2"),
stringsAsFactors = FALSE)
## Combine as a named list and convert to a DataFrame
maplist <- list(Affy = exprmap, Methyl450k = methylmap,
RNASeqGene = rnamap, GISTIC = gistmap)
## Create a sampleMap
sampMap <- listToMap(maplist)
## Create an example phenotype data
colDat <- data.frame(sex = c("M", "F", "M", "F"), age = 38:41,
row.names = c("Jack", "Jill", "Bob", "Barbara"))
## Create a MultiAssayExperiment instance
mae <- MultiAssayExperiment(experiments = ExpList, colData = colDat,
sampleMap = sampMap)
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