Zero-inflated Variance Decomposition for pseudobulked scATAC data
Source:R/varZIGLMM.R
varZIGLMM.Rd
`r lifecycle::badge("deprecated")`
This function is deprecated - improved modeling functions can be found in
the package "ChAI" at https://github.com/aifimmunology/ChAI
varZIGLMM
Identified variance decomposition on a given
cell type across both zero-inflated and continuous space using a
zero-inflated general linear mixed model glmmTMB
Usage
varZIGLMM(
TSAM_Object,
cellPopulation = NULL,
continuousRandom = NULL,
ziRandom = NULL,
zi_threshold = 0.1,
verbose = FALSE,
numCores = 1
)
Arguments
- TSAM_Object
A SummarizedExperiment object generated from getSampleTileMatrix.
- cellPopulation
Name of a cell type(s), or 'all'. The function will combine the cell types mentioned into one matrix before running the model.
- continuousRandom
Random effects to test in the continuous portion. All factors must be found in column names of the TSAM_Object metadata, except for FragNumber and CellCount, which will be extracted from the TSAM_Object's metadata.
- ziRandom
Random effects to test in the zero-inflated portion. All factors must be found in column names of the TSAM_Object colData metadata, except for FragNumber and CellCount, which will be extracted from the TSAM_Object's metadata.
- zi_threshold
Zero-inflated threshold ( range = 0-1), representing the fraction of samples with zeros. When the percentage of zeros in the tile is between 0 and zi_threshold, samples with zeroes are dropped and only the continous formula is used. Use this parameter at your own risk. Default is 0.
- verbose
Set TRUE to display additional messages. Default is FALSE.
- numCores
integer. Number of cores to parallelize across.