Description Usage Arguments Details Value Author(s) See Also Examples
The InteractionSet class stores information about pairwise genomic interactions, and is intended for use in data analysis from Hi-C or ChIA-PET experiments. Each row of the InteractionSet corresponds to a pairwise interaction between two loci, as defined in the GInteractions object. Each column corresponds to a library or sample. Each InteractionSet also contains one or more assays, intended to hold experimental data about interaction frequencies for each interaction in each sample.
1 2 3 4 5 | ## S4 method for signature 'ANY,GInteractions'
InteractionSet(assays, interactions, ...)
## S4 method for signature 'missing,missing'
InteractionSet(assays, interactions, ...)
|
assays |
A numeric matrix or a list or |
interactions |
A GInteractions object of length equal to the number of rows in |
... |
Other arguments to be passed to |
The InteractionSet class inherits from the SummarizedExperiment class and has access to all of its data members and methods
(see ?SummarizedExperiment-class
for more details).
It also contains an additional interactions
slot which holds a GInteractions object (or an object from any derived classes, e.g., StrictGInteractions).
Each row of the InteractionSet object corresponds to a pairwise interaction between two genomic loci in interactions
.
The constructor will return an InteractionSet object containing all of the specified information
- for InteractionSet,missing,missing-method
, an empty InteractionSet object is returned.
Note that any metadata
arguments will be placed in the metadata of the internal SummarizedExperiment object,
not the metadata of the internal GInteractions object.
This is consistent with the behaviour of similar classes like RangedSummarizedExperiment.
For the constructors, an InteractionSet object is returned.
Aaron Lun
SummarizedExperiment
,
interaction-access
,
interaction-subset
,
interaction-compare
,
SummarizedExperiment-class
1 2 3 4 5 6 7 8 9 10 11 12 | example(GInteractions, echo=FALSE)
Nlibs <- 4
counts <- matrix(rpois(Np*Nlibs, lambda=10), ncol=Nlibs)
colnames(counts) <- seq_len(Nlibs)
iset <- InteractionSet(counts, gi)
iset <- InteractionSet(counts, gi, colData=DataFrame(lib.size=1:Nlibs*1000))
iset <- InteractionSet(counts, gi, metadata=list(name="My Hi-C data"))
# Note differences in metadata storage:
metadata(iset)
metadata(interactions(iset))
|
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