removeAssaysWithMissingMetadata: Step 9: Remove assays with missing metadata

In NeilPearson-Lilly/MethyLiution: MethyLiution: A QC Pipeline For Methylation Data

Description

This probably isn't something you want to run directly. Just use the runPipeline() function.

Usage

removeAssaysWithMissingMetadata(begin, mset_file, logfile,
  feature_data_file, metafile, missing_meta_file, meta_data_file, outdir,
  col.name = NULL, mset.lumi = NULL, meth.B = NULL, meth.M = NULL,
  bmiq.B = NULL, bmiq.M = NULL)

Arguments

begin	Step the pipeline begins at
mset_file	Path to file in which dataset object is stored between steps (auto-filled by runPipeline() function)
logfile	Path to log file (auto-filled by runPipeline() function)
feature_data_file	Path to a file containing feature data (auto-filled by runPipeline() function)
metafile	Path to file containing experimental metadata
missing_meta_file	Path to a file where assays with missing data are explicitly listed (auto-filled by runPipeline() function)
meta_data_file	Path to a file containing valid metadata from samples that have passed this filter (auto-filled by runPipeline() function)
outdir	Path to output directory
col.name	List of column names, generated by setColumnNames() (auto-filled by runPipeline() function)
mset.lumi	Microarray dataset object (auto-filled by runPipeline() function)
meth.B	Object containing normalised data, made during Step 7. (auto-filled by runPipeline() function)
meth.M	Object containing normalised data, made during Step 7. (auto-filled by runPipeline() function)
bmiq.B	Object containing BMIQ-normalised data, made during Step 8. (auto-filled by runPipeline() function)
bmiq.M	Object containing BMIQ-normalised data, made during Step 8. (auto-filled by runPipeline() function)

Value

list - mset.lumi dataset, BMIQ-normalised data object (B values)

NeilPearson-Lilly/MethyLiution documentation built on May 21, 2019, 11:29 a.m.