processBismark: Preprocess cytosine reports

In ben-laufer/DMRichR: Enrich your DMR Analysis with the Tidyverse

Preprocess cytosine reports

Description

Process bismark cytosine reports into bsseq objects with design matrix pData

Usage

processBismark(
  files = list.files(path = getwd(), pattern = "*.CpG_report.txt.gz"),
  meta = openxlsx::read.xlsx("sample_info.xlsx", colNames = TRUE) %>%
    dplyr::mutate_if(is.character, as.factor),
  testCovariate = testCovariate,
  adjustCovariate = NULL,
  matchCovariate = NULL,
  coverage = coverage,
  cores = cores,
  perGroup = perGroup,
  sexCheck = FALSE
)

Arguments

files	List of cytosine report file paths
meta	Design matrix data frame with sample name in the Name column
testCovariate	Factor of interest
adjustCovariate	Variables to adjust for
matchCovariate	Variable to block for when constructing permutations
coverage	CpG coverage cutoff (1x recommended)
cores	Integer specifying the number of cores to use
perGroup	Percent of samples per a group to apply the CpG coverage cutoff to (from 0 to 1)
sexCheck	Logical (TRUE or FALSE) indicating whether to confirm the sex of samples and drop the sex chromosomes if both sexes are present. This function requires a column called "Sex" (case sensitive) in sample_info.xlsx. Males should be coded as either "Male", "male", "M", or "m". Females coded as "Female", "female", "F", or "f".

Details

processBismark

ben-laufer/DMRichR documentation built on Oct. 1, 2023, 7:25 a.m.