process.ABC.RAP: An automated analysis applying all ABC.RAP functions in one...

In ABC.RAP: Array Based CpG Region Analysis Pipeline

Description

This function processes the ABC.RAP workflow automatically

Usage

process.ABC.RAP(x, cases_column_1, cases_column_n, controls_column_1,
  controls_column_n, ttest_cutoff, meth_cutoff, unmeth_cutoff, high_meth,
  low_meth)

Arguments

x	The normalised beta values in a data matrix format, where conditions are arranged in columns and cg probes are arranged in rows.
cases_column_1	The first column (column number) for cases in the filtered dataset
cases_column_n	The last column (column number) for cases in the filtered dataset
controls_column_1	The first column (column number) for controls in the filtered dataset
controls_column_n	The last column (column number) for controls in the filtered dataset
ttest_cutoff	The cutoff level to filter insignificant p-values
meth_cutoff	The cutoff level for the methylation difference between cases and controls (cases minus controls)
unmeth_cutoff	The cutoff level for the methylation difference between controls and cases (controls minus cases). Consequently, it requires a negative value.
high_meth	The upper margin for the highly methylated probes
low_meth	The lower margin for the low methylation

Examples

data(test_data)
data(nonspecific_probes)
data(annotation_file)
process.ABC.RAP(test_data, 1, 2, 3, 4, 1e-3,  0.5, -0.5, 0.94, 0.06)

ABC.RAP documentation built on May 2, 2019, 9:16 a.m.