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".