quantify exposure for samples using Linear Combination Decomposition (LCD)

quantify exposure for samples using Linear Combination Decomposition (LCD)

cnv_quantifySigExposure(sample_by_component,
  component_by_signature = NULL)

Arguments

sample_by_component	a sample-by-component matrix, generate from cnv_generateSbCMatrix function.
component_by_signature	a componet by signature matrix, default is NULL, it will use pre-compiled data from CNV signature paper https://www.nature.com/articles/s41588-018-0179-8

Value

a list contains absolute/relative exposure.

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)
## generate a sample-by-component matrix
tcga_sample_component_matrix = cnv_generateSbCMatrix(tcga_features, tcga_components, cores = 1)
## optimal rank survey
 tcga_sig_choose = cnv_chooseSigNumber(tcga_sample_component_matrix,
 nrun = 10, cores = 1, plot = FALSE)
 tcga_signatures = cnv_extractSignatures(tcga_sample_component_matrix, nsig = 3, cores = 1)
 w = NMF::basis(tcga_signatures) # signature matrix
 tcga_exposure = cnv_quantifySigExposure(sample_by_component =
 tcga_sample_component_matrix, component_by_signature = w)
# }