fit_betas_to_distribution: Categorize betas based on bimodal distribution
In ethanmoyer/ICCE: Iterative Construction of Cyto-epigenetic Evolution
Description
Usage
Arguments
Value
Examples
View source: R/preprocessData.R
Description
This function uses a given bimodal distribution generated within cell types
in order to categorize betas as either methylated (1), unmethylated (0), or
ambiguous (-1).
Usage
1
fit_betas_to_distribution(betas, bi)
Arguments
betas
matrix (rows are cell names, columns are probe names)
bi
matrix specifying mu0, mu1, sigma0, sigma1 across all cell types
Value
betas matrix categorized based on bimodal distribution
Examples
1
betas <- fit_betas_to_distribution(betas, bi)
ethanmoyer/ICCE documentation built on Aug. 25, 2020, 5:18 p.m.
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Description Usage Arguments Value Examples
View source: R/preprocessData.R
Description
This function uses a given bimodal distribution generated within cell types in order to categorize betas as either methylated (1), unmethylated (0), or ambiguous (-1).
Usage
1 | fit_betas_to_distribution(betas, bi)
|
Arguments
betas |
matrix (rows are cell names, columns are probe names) |
bi |
matrix specifying mu0, mu1, sigma0, sigma1 across all cell types |
Value
betas matrix categorized based on bimodal distribution
Examples
1 | betas <- fit_betas_to_distribution(betas, bi)
|
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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