omixerRand: Multivariate Randomization

In Omixer: Randomize Samples for -omics Profiling

Description

As the main function of the Omixer package, this function outputs a randomized sample list that minimizes correlations between biological factors and technical covariates.

Usage

omixerRand(
  df,
  sampleId = "sampleId",
  block = "block",
  iterNum = 1000,
  wells,
  div = "none",
  positional = FALSE,
  plateNum = 1,
  layout,
  mask = 0,
  techVars,
  randVars
)

Arguments

df	Sample list
sampleId	String specifying sample ID variable
block	Paired sample identifier
iterNum	Number of layouts to generate
wells	Number of wells on a plate
div	Plate subdivisions
positional	Logical indicator of positional batch effects
plateNum	Number of plates
layout	Custom plate layout as data frame
mask	Wells to be left empty
techVars	Technical covariates
randVars	Randomization variables

Value

Selected randomized sample list as a data frame

Randomization environment of optimal list generation

Examples

library(tibble)
library(forcats)
library(stringr)

sampleList <- tibble(sampleId=str_pad(1:48, 4, pad="0"),
sex=as_factor(sample(c("m", "f"), 48, replace=TRUE)), 
age=round(rnorm(48, mean=30, sd=8), 0), 
smoke=as_factor(sample(c("yes", "ex", "never"), 48, replace=TRUE)),
date=sample(seq(as.Date('2008/01/01'), as.Date('2016/01/01'), 
               by="day"), 48))
               
randVars <- c("sex", "age", "smoke", "date")

omixerLayout <- omixerRand(sampleList, sampleId="sampleId", 
block="block", iterNum=10, wells=48, div="row", 
plateNum=1, randVars=randVars)

Example output

Random seed saved to working directory

Omixer documentation built on Feb. 4, 2021, 2:01 a.m.