process.ABC.RAP {ABC.RAP} | R Documentation |
An automated analysis applying all ABC.RAP functions in one script
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)