escoEstDropout: Estimate esco dropout parameters
In JINJINT/splattermodify: Simple Simulation of Single-cell RNA Sequencing Data
Description
Usage
Arguments
Details
Value
View source: R/esco-estimate.R
Description
Estimate the midpoint and shape parameters
for the logistic function used
when simulating dropout.
Usage
1
escoEstDropout(norm.counts, params)
Arguments
norm.counts
library size normalised counts matrix.
params
escoParams object to store estimated values in.
Details
Logistic function parameters are estimated
by fitting a logistic function
to the relationship between log2 mean gene
expression and the proportion of
zeros in each gene. See nls
for details of fitting.
Note this is done on the experiment level.
Value
escoParams object with estimated values.
JINJINT/splattermodify documentation built on May 19, 2021, 4:05 p.m.
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Description Usage Arguments Details Value
View source: R/esco-estimate.R
Description
Estimate the midpoint and shape parameters for the logistic function used when simulating dropout.
Usage
1 | escoEstDropout(norm.counts, params)
|
Arguments
norm.counts |
library size normalised counts matrix. |
params |
|
Details
Logistic function parameters are estimated
by fitting a logistic function
to the relationship between log2 mean gene
expression and the proportion of
zeros in each gene. See nls
for details of fitting.
Note this is done on the experiment level.
Value
escoParams object with estimated values.
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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