MOCHA (version 1.1.0)

runZIGLMM: Run Zero-inflated Generalized Linear Mixed Modeling on pseudobulked scATAC data

Description

`r lifecycle::badge("deprecated")` This function is deprecated - improved modeling functions can be found in the package "ChAI" at https://github.com/aifimmunology/ChAI runZIGLMM Runs linear mixed-effects modeling for zero-inflated data using glmmTMB.

Usage

runZIGLMM(
  TSAM_Object,
  cellPopulation = "all",
  continuousFormula = NULL,
  ziformula = NULL,
  zi_threshold = 0,
  initialSampling = 5,
  verbose = FALSE,
  numCores = 1
)

Value

results a SummarizedExperiment containing LMEM results

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.

continuousFormula

The formula for the continuous data that should be used within glmmTMB. It should be in the format (exp ~ factors). All factors must be found in column names of the TSAM_Object metadata, except for CellType, FragNumber and CellCount, which will be extracted from the TSAM_Object. modelFormula must start with 'exp' as the response. See glmmTMB.

ziformula

The formula for the zero-inflated data that should be used within glmmTMB. It should be in the format ( ~ factors). All factors must be found in column names of the TSAM_Object colData metadata, except for CellType, FragNumber and CellCount, which will be extracted from the TSAM_Object.

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.

initialSampling

Size of data to use for pilot

verbose

Set TRUE to display additional messages. Default is FALSE.

numCores

integer. Number of cores to parallelize across.

Examples

if (FALSE) {
modelList <- runZIGLMM(STM[c(1:1000), ],
  cellPopulation = "CD16 Mono",
  continuousFormula = exp ~ Age + Sex + days_since_symptoms + (1 | PTID),
  ziformula = ~ FragNumber + Age,
  verbose = TRUE,
  numCores = 35
)
}