zeroProbModel: Predict zero probability using logistic rgression
In SPsimSeq: Semi-parametric simulation tool for bulk and single-cell RNA sequencing data
Description
Usage
Arguments
Value
View source: R/zeroProbModel.R
Description
Predict zero probability using logistic rgression
Usage
1
zeroProbModel(cpm.data, logL, zeroMat, n.mean.class)
Arguments
cpm.data
log CPM matrix
logL
log library size of the source data
zeroMat
the matrix of zero indicators
n.mean.class
a fraction of the number of genes
for the number of groups to be created for the mean log CPM of genes
Value
The coefficients of the estimated logistic regression
SPsimSeq documentation built on Nov. 8, 2020, 5:09 p.m.
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Description Usage Arguments Value
View source: R/zeroProbModel.R
Description
Predict zero probability using logistic rgression
Usage
1 | zeroProbModel(cpm.data, logL, zeroMat, n.mean.class)
|
Arguments
cpm.data |
log CPM matrix |
logL |
log library size of the source data |
zeroMat |
the matrix of zero indicators |
n.mean.class |
a fraction of the number of genes for the number of groups to be created for the mean log CPM of genes |
Value
The coefficients of the estimated logistic regression
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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