cnv_fitMixModels: Fit optimal number of mixture model components
In ShixiangWang/VSHunter: Capture Variation Signatures from Genomic Data

Description Usage Arguments Value Author(s) See Also Examples

Apply mixture modelling to breakdown each feature distribution into mixtures of Gaussian or mixtures of Poison distributions using the flexmix package.

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cnv_fitMixModels(CN_features, seed = 123456, min_comp = 2,
  max_comp = 10, min_prior = 0.001, model_selection = "BIC",
  nrep = 1, niter = 1000, cores = 1, featsToFit = seq(1, 6))

`CN_features`	a `list` generate from `cnv_derivefeatures()` function.
`seed`	seed number.
`min_comp`	minimal number of components to fit, default is 2.
`max_comp`	maximal number of components to fit, default is 10.
`min_prior`	minimal prior value, default is 0.001. Details about custom setting please refer to flexmix package.
`model_selection`	model selection strategy, default is 'BIC'. Details about custom setting please refer to flexmix package.
`nrep`	number of run times for each value of component, keep only the solution with maximum likelihood.
`niter`	maximal number of iteration to achive converge.
`cores`	number of compute cores to run this task. You can use `parallel::detectCores()` function to check how many cores you can use. If you are using `cnv_pipe()` feature, please do not use maximal number of cores in your computer, it may cause some unexpected problems.
`featsToFit`	integer vector used for task assignment in parallel computation. Do not change it!

a list contain flexmix object of copy-number features.

Geoffrey Macintyre, Shixiang Wang

cnv_plotMixComponents() for plotting mixture component models.

Other CNV analysis functions: cnv_autoCaptureSignatures, cnv_chooseSigNumber, cnv_derivefeatures, cnv_extractSignatures, cnv_generateSbCMatrix, cnv_getLengthFraction, cnv_pipe, cnv_plotDistributionProfile, cnv_plotFeatureDistribution, cnv_plotMixComponents, cnv_plotSignatures, cnv_quantifySigExposure, cnv_readprofile

## Not run: 
## load example copy-number data from tcga
load(system.file("inst/extdata", "example_cn_list.RData", package = "VSHunter"))
## generate copy-number features
tcga_features = cnv_derivefeatures(CN_data = tcga_segTabs, cores = 1, genome_build = "hg19")
## fit mixture model  (this will take some time)
tcga_components = cnv_fitMixModels(CN_features = tcga_features, cores = 1)

## End(Not run)