getOverdispersedGenes: Normalize gene expression variance relative to...

In JEFworks-Lab/STdeconvolve: Reference-free Cell-Type Deconvolution of Multi-Cellular Spatially Resolved Transcriptomics Data

Normalize gene expression variance relative to transcriptome-wide expectations (Modified from SCDE/PAGODA2 code)

Description

Normalizes gene expression magnitudes to with respect to its ratio to the transcriptome-wide expectation as determined by local regression on expression magnitude

Usage

getOverdispersedGenes(
  counts,
  gam.k = 5,
  alpha = 0.05,
  plot = FALSE,
  use.unadjusted.pvals = FALSE,
  do.par = TRUE,
  max.adjusted.variance = 1000,
  min.adjusted.variance = 0.001,
  verbose = TRUE,
  details = FALSE
)

Arguments

counts	Read count matrix. The rows correspond to genes, columns correspond to individual cells
gam.k	Generalized additive model parameter; the dimension of the basis used to represent the smooth term (default: 5)
alpha	Significance threshold (default: 0.05)
plot	Whether to plot the results (default: FALSE)
use.unadjusted.pvals	If true, will apply BH correction (default: FALSE)
do.par	Whether to adjust par for plotting if plotting (default: TRUE)
max.adjusted.variance	Ceiling on maximum variance after normalization to prevent infinites (default: 1e3)
min.adjusted.variance	Floor on minimum variance after normalization (default: 1e-3)
verbose	Verbosity (default: TRUE)
details	If true, will return data frame of normalization parameters. Else will return list of overdispersed genes. (default: FALSE)

Value

If details is true, will return data frame of normalization parameters. Else will return list of overdispersed genes.

Examples

data(mOB)
od <- getOverdispersedGenes(counts = mOB$counts, gam.k = 5, alpha = 0.05, details = FALSE)
head(od)

od <- getOverdispersedGenes(counts = mOB$counts, gam.k = 5, alpha = 0.05, details = TRUE)
head(od$mat)
head(od$ods)
head(od$df)

JEFworks-Lab/STdeconvolve documentation built on Nov. 14, 2024, 7:24 p.m.