LevelstoNormFC: Accessors for the 'LevelstoNormFC' slot of a ABSDataSet...
In ABSSeq: ABSSeq: a new RNA-Seq analysis method based on modelling absolute expression differences
Description
Usage
Arguments
Details
See Also
Examples
Description
Accessor functions for the 'LevelstoNormFC' slot of a ABSDataSet
object.
Usage
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## S4 method for signature 'ABSDataSet'
LevelstoNormFC(object)
## S4 replacement method for signature 'ABSDataSet,numeric'
LevelstoNormFC(object)<-value
Arguments
object
an ABSDataSet object.
value
a positive numeric object
Details
The 'LevelstoNormFC' is maximal level of average standard deviation in fold-change normalization
according to expression level.
See Also
Examples
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data(simuN5)
obj <- ABSDataSet(counts=simuN5$counts, groups=factor(simuN5$groups))
LevelstoNormFC(obj)
LevelstoNormFC(obj) <- 200
LevelstoNormFC(obj)
ABSSeq documentation built on Nov. 8, 2020, 5:07 p.m.
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Description Usage Arguments Details See Also Examples
Description
Accessor functions for the 'LevelstoNormFC' slot of a ABSDataSet object.
Usage
1 2 3 4 5 | ## S4 method for signature 'ABSDataSet'
LevelstoNormFC(object)
## S4 replacement method for signature 'ABSDataSet,numeric'
LevelstoNormFC(object)<-value
|
Arguments
object |
an |
value |
a positive numeric object |
Details
The 'LevelstoNormFC' is maximal level of average standard deviation in fold-change normalization according to expression level.
See Also
Examples
1 2 3 4 5 | data(simuN5)
obj <- ABSDataSet(counts=simuN5$counts, groups=factor(simuN5$groups))
LevelstoNormFC(obj)
LevelstoNormFC(obj) <- 200
LevelstoNormFC(obj)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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