interactionModeClassifier: Interaction mode classification with limma and edgeR
In taylo5jm/interactions: Classification of gene expression profile sets generated from combination stimuli
Description
Usage
Arguments
Value
Description
Interaction mode classification with limma and edgeR
Usage
1
2
interactionModeClassifier(data, DRUG_COMBINATION = TRUE, ci = 0.99,
alpha = 0.01)
Arguments
alpha
numeric vector indicating what alpha should be used to
code pairwise comparison outcome vectors
counts
numeric matrix of counts where rows are genes and columns are libraries
genes
data.frame of gene metadata
metadata
data.frame with metadata retrieved for 4 conditions
null
Boolean TRUE if null distribution should be simulated by permuting
columns of counts matrix
Value
nested list
taylo5jm/interactions documentation built on May 31, 2019, 3:57 a.m.
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Description Usage Arguments Value
Description
Interaction mode classification with limma and edgeR
Usage
1 2 | interactionModeClassifier(data, DRUG_COMBINATION = TRUE, ci = 0.99,
alpha = 0.01)
|
Arguments
alpha |
numeric vector indicating what alpha should be used to code pairwise comparison outcome vectors |
counts |
numeric matrix of counts where rows are genes and columns are libraries |
genes |
data.frame of gene metadata |
metadata |
data.frame with metadata retrieved for 4 conditions |
null |
Boolean TRUE if null distribution should be simulated by permuting columns of counts matrix |
Value
nested list
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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