fit_beta_em: Estimate mixed beta distribution parameters based on EM...
In Yi-Jiang/MethyGenotyper: MethylGenotyper: Accurate estimation of SNP genotypes from DNA methylation data
View source: R/call_genotypes.R
fit_beta_em R Documentation
Estimate mixed beta distribution parameters based on EM algorithm
Description
The Expectation–maximization (EM) algorithm is used to fit a mixture of three beta distributions representing the three genotypes (AA, AB, and BB) and one uniform distribution representing the outliers (adapted from ewastools).
Usage
fit_beta_em(RAI, maxiter = 50, verbose = 1)
Arguments
RAI
A matrix of RAI (Ratio of Alternative allele Intensity) for probes. Provide probes as rows and samples as columns.
maxiter
Maximal number of iterations for the EM algorithm.
verbose
Verbose mode: 0/1/2.
Value
A list containing
shapes
Shapes of the mixed beta distributions
weights
Prior probabilities that the RAI values belong to one of the three genotypes
U
Overall probability of RAI values being outlier
outliers
Probability of each RAI value being outlier
logLik
Log-likelihood
GP
Genotype probabilities of the three genotypes
Yi-Jiang/MethyGenotyper documentation built on Sept. 4, 2024, 12:47 p.m.
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View source: R/call_genotypes.R
| fit_beta_em | R Documentation |
Estimate mixed beta distribution parameters based on EM algorithm
Description
The Expectation–maximization (EM) algorithm is used to fit a mixture of three beta distributions representing the three genotypes (AA, AB, and BB) and one uniform distribution representing the outliers (adapted from ewastools).
Usage
fit_beta_em(RAI, maxiter = 50, verbose = 1)
Arguments
RAI |
A matrix of RAI (Ratio of Alternative allele Intensity) for probes. Provide probes as rows and samples as columns. |
maxiter |
Maximal number of iterations for the EM algorithm. |
verbose |
Verbose mode: 0/1/2. |
Value
A list containing
shapes |
Shapes of the mixed beta distributions |
weights |
Prior probabilities that the RAI values belong to one of the three genotypes |
U |
Overall probability of RAI values being outlier |
outliers |
Probability of each RAI value being outlier |
logLik |
Log-likelihood |
GP |
Genotype probabilities of the three genotypes |
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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