Description Usage Arguments Value Slots See Also Examples
The ModifierML class is a virtual class, which provides the central
functionality for searching with a machine learning models for patterns of
post-transcriptional RNA modifications in high throughput sequencing data.
It extends the virtual Modifier class form the RNAmodR package
and add the useMLModel function. If not called directly for a
ModifierML class, the useMLModel will be called from the
aggregate function.
The slot mlModel is added and serves a dual purpose. If mlModel
is a character, a class of the type ModifierMLModel is created upon
creation of a ModifierML object. However, for developing purposes
the slot can also remain empty and a ModifierMLModel object can be set
using the setMLModel function and retrieved using the
getMLModel. If the mlModel slot is empty, the findMod
setting will be set to FALSE and the ModifierML object will
be returned just with the aggregate data. Such an object can then be used to
train a machine learning model. The data can be accessed using
trainingData.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | setMLModel(x) <- value
getMLModel(x)
hasMLModel(x)
useMLModel(x)
## S4 replacement method for signature 'ModifierML'
setMLModel(x) <- value
## S4 method for signature 'ModifierML'
getMLModel(x)
## S4 method for signature 'ModifierML'
hasMLModel(x)
## S4 method for signature 'ModifierML'
aggregate(x, force = FALSE)
## S4 method for signature 'ModifierML'
useMLModel(x)
## S4 method for signature 'ModifierML'
modify(x, force = FALSE)
|
x |
a |
value |
a |
force |
whether to recreate the aggregated data, if it is already stored
inside the |
a ModifierML object
mlModela character describing a class name for creating a
ModifierMLModel object or a ModifierMLModel object itself.
If mlModel is a character, the class will tried to be create
by calling a function of the same name.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | # an example implementation of a ModifierML object
setClass("ModMLExample",
contains = c("RNAModifierML"),
prototype = list(mod = c("D"),
score = "score",
dataType = c("PileupSequenceData",
"CoverageSequenceData"),
mlModel = character(0)))
# constructor function for ModMLExample
ModMLExample <- function(x, annotation = NA, sequences = NA, seqinfo = NA,
...){
RNAmodR:::Modifier("ModMLExample", x = x, annotation = annotation,
sequences = sequences, seqinfo = seqinfo, ...)
}
|
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