PALMO (version 0.1.2)

lmeVariance: 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
)

Value

PALMO object with variance lmem_res dataframe

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

Examples

if (FALSE) {
palmo_obj=lmeVariance(data_object=palmo_obj,
featureSet=c('PTID','Time','Sex'))
}