Fit optimal number of mixture model components

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

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))

Arguments

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 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.

Value

a list contain flexmix object of copy-number features.

Examples

# 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)
# }