A list-based S4 classes for storing expression values (E-values), for example for a set of one-channel microarrays or a set of RNA-seq samples.
EListRaw holds expression values on the raw scale.
EList holds expression values on the log scale, usually after background correction and normalization.
EListRaw objects are often created by
EList objects are often created by
normalizeBetweenArrays or by
EList object can be created directly by
x is a list.
These classes contains no slots (other than
.Data), but objects should contain a list component
numeric matrix containing expression values.
EListRaw object, the expression values are unlogged, while in an
EList object, they are log2 values.
Rows correspond to probes and columns to samples.
Optional components include:
numeric matrix containing unlogged background expression values, of same dimensions as
E. For an
EListRaw object only.
numeric matrix of same dimensions as
E containing relative spot quality weights. Elements should be non-negative.
list containing other matrices, all of the same dimensions as
data.frame containing probe information. Should have one row for each probe. May have any number of columns.
data.frame containing information on the target RNA samples. Rows correspond to samples. May have any number of columns.
EListRaw objects may contain other optional components, but all probe or sample information should be contained in the above components.
These classes inherit directly from class
list so any operation appropriate for lists will work on objects of this class.
EList objects can be subsetted and combined.
EList objects will return dimensions and hence functions such as
ncol are defined.
ELists also inherit a
show method from the virtual class
LargeDataObject, which means that
ELists will print in a compact way.
02.Classes gives an overview of all the classes defined by this package.
ExpressionSet is a more formal class in the Biobase package used for the same purpose.
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# Two ways to make an EList object: y <- matrix(rnorm(10,5),10,5) rownames(y) <- paste0("Gene",1:10) colnames(y) <- LETTERS[1:5] Genes <- data.frame(Chr=sample(1:21,10)) row.names(Genes) <- row.names(y) # Create the object, than add components: E <- new("EList") E$E <- y E$genes <- Genes # Create with components: E <- new("EList", list(E=y, genes=Genes))
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