FSCseq: Wrapper for main FSCseq function
In DavidKLim/FSCseq: Feature Selection and Clustering of RNA-seq Count Data

Description Usage Arguments Value Author(s) References

Run main CEM/EM clustering and feature selection algorithm.

FSCseq(
  ncores = 1,
  X = NULL,
  y,
  k,
  lambda = 0,
  alpha = 0,
  size_factors,
  norm_y,
  true_clusters = NULL,
  true_disc = NULL,
  init_parms = FALSE,
  init_coefs = NULL,
  init_phi = NULL,
  init_cls = NULL,
  init_wts = NULL,
  n_rinits = if (method == "EM") {     20 } else if (method == "CEM") {     1 },
  maxit_inits = if (method == "EM") {     15 } else if (method == "CEM") {     100 },
  maxit_EM = 100,
  maxit_IRLS = 50,
  maxit_CDA = 50,
  EM_tol = 1e-06,
  IRLS_tol = 1e-04,
  CDA_tol = 1e-04,
  disp = "gene",
  method = "CEM",
  init_temp = nrow(y),
  trace = F,
  trace.file = NULL,
  mb_size = NULL,
  PP_filt = 0.001
)

`ncores`	integer, number of cores to utilize in parallel computing (default 1)
`X`	(optional) design matrix of dimension n by p
`y`	count matrix of dimension g by n
`k`	integer, number of clusters
`lambda`	numeric penalty parameter, lambda >= 0
`alpha`	numeric penalty parameter, 0 <= alpha < 1
`size_factors`	numeric vector of length n, factors to correct for subject-specific variation of sequencing depth
`norm_y`	count matrix of dimension g by n, normalized for differences in sequencing depth
`true_clusters`	(optional) integer vector of true groups, if available, for diagnostic tracking
`true_disc`	(optional) logical vector of true discriminatory genes, if available, for diagnostic tracking
`init_parms`	logical, TRUE: custom parameter initializations, FALSE (default): start from scratch
`init_coefs`	matrix of dimension g by k, only if init_parms = TRUE
`init_phi`	vector of dimension g (gene-specific dispersions), only if init_parms = TRUE
`init_cls`	(optional) vector of length n, initial clustering.
`init_wts`	(optional) matrix of dim k by n to denote initial clustering (allowing partial membership). If both init_cls and init_wts specified, init_wts will be ignored and init_cls used as initial clusters
`n_rinits`	integer, number of additional random initializations to be searched (default 1)
`maxit_inits`	integer, maximum number of iterations for each initialization search (default 100)
`maxit_EM`	integer, maximum number of iterations for full CEM/EM run (default 100)
`maxit_IRLS`	integer, maximum number of iterations for IRLS algorithm, in M step (default 50)
`maxit_CDA`	integer, maximum number of iterations for CDA loop (default 50)
`EM_tol`	numeric, tolerance of convergence for EM/CEM, default is 1E-6
`IRLS_tol`	numeric, tolerance of convergence for IRLS, default is 1E-4
`CDA_tol`	numeric, tolerance of convergence for IRLS, default is 1E-4
`method`	string, either "EM" or "CEM" (default)
`init_temp`	numeric, default for CEM: init_temp = nrow(y), i.e. number of genes. temp=1 for EM
`trace`	logical, TRUE: output diagnostic messages, FALSE (default): don't output
`trace.file`	(optional) string, file into which interim diagnostics will be printed
`mb_size`	minibatch size: # of genes to include per M step iteration
`PP_filt`	numeric between (0,1), threshold on PP for sample/cl to be included in M step estimation. Default is 1e-3