nTopDeltaCV: nTopDeltaCV
In EngeLab/RNAseqFunctions: RNA sequencing functions for the Enge lab
Description
Arguments
Author(s)
View source: R/featureSelectionFuns.R
Description
Selected informative genes by fitting a support-vector regression to the
coefficient of variation (CV) as a function of the mean, and selecting genes
having the greatest offset from the fitted curve; this would correspond to
genes with higher-than-expected variance. Adpoted from Linnarsson lab python
implementation:
https://github.com/linnarsson-lab/cytograph/blob/master/cytograph/feature_selection.py.
Note this displays a rendency to prioritize lowly expressed genes.
Arguments
cpm
matrix; Matrix containing cpm values.
n
Number of genes to select.
Author(s)
Jason T. Serviss
EngeLab/RNAseqFunctions documentation built on May 5, 2019, 9:43 p.m.
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Description Arguments Author(s)
View source: R/featureSelectionFuns.R
Description
Selected informative genes by fitting a support-vector regression to the coefficient of variation (CV) as a function of the mean, and selecting genes having the greatest offset from the fitted curve; this would correspond to genes with higher-than-expected variance. Adpoted from Linnarsson lab python implementation: https://github.com/linnarsson-lab/cytograph/blob/master/cytograph/feature_selection.py. Note this displays a rendency to prioritize lowly expressed genes.
Arguments
cpm |
matrix; Matrix containing cpm values. |
n |
Number of genes to select. |
Author(s)
Jason T. Serviss
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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