Normalize filtered samples with minfi and wateRmelon methods

Source: R/preprocessingMinfiEwasWater_steps.R

Apply one or more supported normalization methods to a filtered RGSet and return all normalized objects together in a single result object.

normalizeMinfiEwasWater(
  sampleData,
  sexColumn = "Sex",
  normMethods = "adjustedfunnorm",
  verbose = FALSE,
  logs = FALSE,
  log_dir = NULL,
  log_file = "log_normalizeMinfiEwasWater.txt"
)

Arguments

sampleData

Object returned by filterSamplesMinfiEwasWater().

sexColumn

Character. Name of the phenotype column used as the optional sex covariate for normalization methods that support it.

normMethods

Character vector or semicolon-separated string of normalization methods. Supported values are "adjustedfunnorm", "funnorm", "illumina", "quantile", and "swan".

verbose

Logical. If TRUE, emit progress messages with message().

logs

Logical. If TRUE, write the same messages to a log file.

log_dir

Character or NULL. Directory used for the log file when logs = TRUE.

log_file

Character. File name used when logs = TRUE.

Value

A list with class "dnaEPICO_minfiEwasWater_norm" containing the requested normalized objects and the first method as primary.

Examples

ex <- dnaEPICO:::exampleMinfiBaseDataDnaEpico()
sample_data <- filterSamplesMinfiEwasWater(
  RGSet = ex$RGSet,
  targets = ex$targets,
  failedSamples = character(0),
  SampleID = "Sample_Name",
  verbose = FALSE,
  logs = FALSE
)
norm_data <- normalizeMinfiEwasWater(
  sampleData = sample_data,
  sexColumn = "Sex",
  normMethods = "quantile",
  verbose = FALSE,
  logs = FALSE
)
#> [preprocessQuantile] Mapping to genome.
#> [preprocessQuantile] Fixing outliers.
#> [preprocessQuantile] Quantile normalizing.
names(norm_data$normalized)
#> [1] "quantile"