CleanCITE.nb.internal: Removes noise from CITE-seq protein data by fitting a...

In CamaraLab/STvEA: Spatially-resolved Transcriptomics via Epitope Anchoring

Removes noise from CITE-seq protein data by fitting a two-component Negative Binomial mixture and computing each expression measurement as the cumulative distribution of the Negative Binomial with the higher median. Normalizes CITE-seq protein data by the original total counts per cell. Takes matrices and data frames instead of STvEA.data class

Description

Removes noise from CITE-seq protein data by fitting a two-component Negative Binomial mixture and computing each expression measurement as the cumulative distribution of the Negative Binomial with the higher median. Normalizes CITE-seq protein data by the original total counts per cell. Takes matrices and data frames instead of STvEA.data class

Usage

CleanCITE.nb.internal(
  cite_protein,
  num_cores = 1,
  maxit = 500,
  factr = 1e-09,
  optim_inits = NULL,
  normalize = TRUE
)

Arguments

cite_protein	Raw CITE-seq protein data (cell x protein)
num_cores	number of cores to use for parallelized fits. On Windows, this must be set to 1.
maxit	maximum number of iterations for optim function
factr	accuracy of optim function
optim_inits	a matrix of (proteins x params) with initialization parameters for each protein to input to the optim function. If NULL, starts at two default parameter sets and picks the better one
normalize	divide cleaned CITE-seq expression by total ADT counts per cell

Value

Cleaned CITE-seq protein data matrix (cell x protein)

CamaraLab/STvEA documentation built on April 2, 2024, 6:07 a.m.