lmeVariance: lmeVariance Function

In aifimmunology/PALMO: Identify Intra and Inter-Donor Variations in Bulk or Single Cell Longitudinal Dataset

lmeVariance Function

Description

This function allows you to calculate inter-donor variation between participants over longitudinal timepoints. It uses linear mixed model to calculate variance contribution from each given feature list.

Usage

lmeVariance(
  data_object,
  featureSet,
  fixed_effect_var = NULL,
  meanThreshold = NULL,
  selectedFeatures = NULL,
  NA_to_zero = FALSE,
  cl = 2,
  lmer_control = FALSE,
  fileName = NULL,
  filePATH = NULL
)

Arguments

data_object	Input PALMO S4 object. It contains annotation information and expression data from Bulk or single cell data.
featureSet	Variance analysis carried out for the feature set provided such as c('PTID', 'Time', 'Sex')
fixed_effect_var	Fixed effect variables. In linear mixed model fixed_effect_var included as fixed effect variables and variance contribution obtained by adding them as random variables
meanThreshold	Average expression threshold to filter lowly expressed genes/features Default is 0
selectedFeatures	User-defined gene/feature list
NA_to_zero	Convert NAs to zero. Default FALSE
cl	Number of clusters. Use nCores-1 to run parallel. Default 2
lmer_control	control structures for mixed model fitting. Default optimizer is "bobyqa". Reduces the run time for large data significantly.
fileName	User-defined file name, Default outputFile
filePATH	User-defined output directory PATH Default, current directory

Value

PALMO object with variance lmem_res dataframe

Examples

## Not run: 
palmo_obj=lmeVariance(data_object=palmo_obj,
featureSet=c('PTID','Time','Sex'))

## End(Not run)

aifimmunology/PALMO documentation built on Oct. 21, 2022, 7:39 p.m.