sepNMF: Single Data Set Decomposition with Nonnegative Matrix...

In CHuanSite/SJD: Structured Joint Decomposition (SJD)

Single Data Set Decomposition with Nonnegative Matrix Factorization

Description

Apply NMF (Nonnegative Matrix Factorization) to a single data set

Usage

sepNMF(
  dataset,
  comp_num,
  weighting = NULL,
  perturbation = 1e-04,
  enable_normalization = TRUE,
  column_sum_normalization = FALSE,
  screen_prob = NULL
)

Arguments

dataset	A dataframe/matrix to be decomposed
comp_num	Number of NMFs to be extracted
weighting	Weighting of each dataset, initialized to be NULL
perturbation	A small perturbation to ensure nmf works well
enable_normalization	An argument to decide whether to use normalizaiton or not, default is TRUE
column_sum_normalization	An argument to decide whether to use column sum normalization or not, default it FALSE
screen_prob	A vector of probabilies for genes to be chosen

Value

A list of scores and component

Examples

dataset = list(matrix(runif(5000, 1, 2), nrow = 100, ncol = 50))
comp_num = 2
res_sepNMF = sepNMF(dataset, comp_num)

CHuanSite/SJD documentation built on Nov. 29, 2024, 5:52 a.m.