scase: Main function for estimating ASE in single-cell data

In lulizou/spASE: Detecting Allele-Specific Expression in Spatial Transcriptomics

Main function for estimating ASE in single-cell data

Description

This function fits a beta-binomial model and returns estimates of p and confidence intervals

Usage

scase(
  matrix1,
  matrix2,
  covariates = NULL,
  method = "betabinomial",
  min.cells = 10,
  cores = 1,
  genes = NULL,
  add.var = 0,
  verbose = F
)

Arguments

matrix1	a matrix of counts where the rows are genes and the columns are cells for allele 1. This one is the one that gets its probability modeled. Must have row names and column names to identify genes and cells.
matrix2	a matrix of counts where the rows are genes and the columns are cells for allele 2.
min.cells	numeric specifying the minimum number of cells a gene should be present on to fit. Default is 10 cells.
cores	number of cores to use for parallelization. Default is 1.
genes	which genes to fit the model on, should be a subset of the rownames of matrix1, default is all of the genes
add.var	amount of additional variance to add, default is 0. If non-zero, addds additional columns to result data frame suffixed with .adj to indicate calculated with the adjusted standard error
verbose	whether or not to print a lot of status messages. Default is FALSE.

Details

Fits a beta-binomial model for each gene and returns a results data frame.

Value

A data frame of results containing the gene names, estimated p and standard errors on the logit scale.

lulizou/spASE documentation built on May 22, 2024, 5:24 a.m.