delta_beta_data {ABC.RAP}

Applying delta beta analysis to calculate the difference between cases and controls

Description

This function calculates the delta beta value for the filtered probes. It calculates the difference in mean DNA methylation between cases and controls for each probe. Also, it selects probes with DNA methylation differences that are higher in cases than controls by a user specified meth_cutoff value and differences that are lower in cases than controls by the unmeth_cutoff value. In addition, the function provides the option to specify probes where the average beta value of the cases or controls is greater than a high_meth cutoff value or less than a low_meth cutoff value.

Usage

delta_beta_data(x, cases_column_1, cases_column_n, controls_column_1,
  controls_column_n, meth_cutoff, unmeth_cutoff, high_meth, low_meth)

Arguments

x

the filtered 450k probes from filter_data function

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

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 (cases minus controls). 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)
test_data_filtered <- filter_data(test_data)
test_data_delta_beta <- delta_beta_data(test_data_filtered, 1, 2, 3, 4, 0.5, -0.5, 0.94, 0.06)