Bayesian mixture models for copy number polymorphisms

Vignettes

- README.md
- Identifying Copy Number Polymorphisms
- Implementation of Bayesian mixture models for copy number estimation
- Overview of CNPBayes package
- Overview of CNPBayes package
- Identifying Copy Number Polymorphisms
- Implementation of Bayesian mixture models for copy number estimation
- Inspecting Convergence of a Model
- Overview of CNPBayes package

92

**bic-method:**Calculate BIC of a model**ggplot-functions:**Trace plots of MCMC chains and mixture model densities**logPrior-method:**Calculate log likelihood of prior for model**mcmcParams-method:**Retrieve MCMC parameters from model.**mu-method:**Retrieve overall mean**p:**Retrieve mixture proportions.**sigma2.0-method:**Retrieve the rate parameter for the sigma.2 distribution.**Browse all...**

Popular Man pages

671

Popular API

tauc
MarginalModel-class
BatchModel-class
DensityBatchModel-class
BatchModel-class
MarginalModel-class
DensityBatchModel-class

62

Popular Source code

tests/testthat/test_SingleBatchPooled.R
tests/testthat/test_copynumber-models.R
tests/testthat/test_Constructors.R
tests/testthat/test_marginal_likelihood.R
tests/testthat/test_currentExtData.R
tests/testthat/test_starting_values.R
tests/testthat/test_MultiBatchPooled.R

Description Usage Arguments Value

View source: R/methods-SingleBatchModel.R

Models of varying component sizes are compared. The log bayes factor is
calculated comparing each set of two models by marginal likelihood,
as computed by `marginalLikelihood`

.

1 |

`x` |
the result of a call to |

Log Bayes factor comparing the two models with highest likelihood.

README.md
Identifying Copy Number Polymorphisms
Implementation of Bayesian mixture models for copy number estimation
Overview of CNPBayes package
Overview of CNPBayes package
Identifying Copy Number Polymorphisms
Implementation of Bayesian mixture models for copy number estimation
Inspecting Convergence of a Model
Overview of CNPBayes package

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