evalDropoutModel: Compute value of logistic dropout function given with scale...
In LineagePulse: Differential expression analysis and model fitting for single-cell RNA-seq data
Description
Usage
Arguments
Value
Author(s)
See Also
View source: R/srcLineagePulse_evalDropoutModel.R
Description
Computes value of logistic function for one observation and uses offset
to correct model. The drop-out magnitude boundary parameter scaOffset is
set in here.
Usage
1
evalDropoutModel(vecPiModel, vecPiPredictors)
Arguments
vecPiModel
(numeric vector length linear model) Linear model
for drop-out rate in logit space.
vecPiPredictors
(vector length of predictors) Predictors of
the drop-out rate in the linear model. Minimum are a constant
offset and log of the negative binomial mean parameter.
Other gene-specific predictors can be added.
Value
scaDropoutRate (scalar)
Drop-out rate estimate.
Author(s)
David Sebastian Fischer
See Also
evalDropoutModel_comp
LineagePulse documentation built on Nov. 8, 2020, 7:01 p.m.
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Description Usage Arguments Value Author(s) See Also
View source: R/srcLineagePulse_evalDropoutModel.R
Description
Computes value of logistic function for one observation and uses offset to correct model. The drop-out magnitude boundary parameter scaOffset is set in here.
Usage
1 | evalDropoutModel(vecPiModel, vecPiPredictors)
|
Arguments
vecPiModel |
(numeric vector length linear model) Linear model for drop-out rate in logit space. |
vecPiPredictors |
(vector length of predictors) Predictors of the drop-out rate in the linear model. Minimum are a constant offset and log of the negative binomial mean parameter. Other gene-specific predictors can be added. |
Value
scaDropoutRate (scalar) Drop-out rate estimate.
Author(s)
David Sebastian Fischer
See Also
evalDropoutModel_comp
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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