fitNBglm: Fit GLM for each window

In MatthiasLienhard/qsea: IP-seq data analysis and vizualization

Fit GLM for each window

Description

This function fits a negative binomial GLM for each genomic window, according to the design matrix.

Usage

fitNBglm(qs,design,link="log",keep, disp_method="region_wise",
norm_method="rpkm",init_disp=0.5 ,verbose=TRUE, minRowSum=10, pseudocount=1,
    disp_iter = 3, nChunks = NULL, parallel = FALSE)

Arguments

qs	a qseaSet object
design	the design matrix for the GLMs
link	name of the link function. Currently, only the canonical dQuotelog link function is implemented.
keep	indices of windows to be included in the analysis.
disp_method	method to estimate dispersion parameters. Allowed values are dQuoteregion_wise for independent window wise estimates, dQuotecommon for a single estimate for all windows, dQuotecutAtQuantiles for window wise estimates trimmed at the 25% and 75% quantiles, or dQuoteinitial for using the dispersion parameters provided with the init_disp parameter.
norm_method	normalization method, as defined by normMethod() function
init_disp	initial estimate for dispersion parameter. Either a single parameter for all regions, or a vector with window wise parameters.
verbose	more messages that document the process
minRowSum	filter out windows with less than minRowSum reads over all samples
pseudocount	this value is added to the read counts
disp_iter	number of iterations for dispersion estimation
nChunks	fit GLMs in multiple chunks
parallel	use multicore processing

Value

This function returns a qseaGLM object, containing the fitted coefficients of the GLMs.

Author(s)

Mathias Lienhard

See Also

addContrast()

Examples

#tbd
qs=getExampleQseaSet()
design=model.matrix(~group, getSampleTable(qs))
TvN_glm=fitNBglm(qs, design, norm_method="beta")

MatthiasLienhard/qsea documentation built on March 22, 2023, 1:15 p.m.