plot_gene: Plotting and exporting methylation profile for candidate...
In ABC.RAP: Array Based CpG Region Analysis Pipeline

This function explores the DNA methylation profile for any gene. The function generates four plots: the top plots show the difference in DNA methylation between cases and controls (a bar chart of the delta beta values for all probes arranged from 5<e2><80><99> to 3<e2><80><99> positions and a plot showing the difference in mean DNA methylation between cases and controls). The bottom plots show the distribution of DNA methylation for each probe that interrogates a CpG site in the investigated gene, for cases (left) and controls (right), respectively. Also, an annotation table for the arranged probes is generated with the following columns: probe names, gene name, distance from TSS, mean methylation for cases, mean methylation for controls, delta beta values (cases minus controls), and t-test p.values.

1 2	plot_gene(x, b, cases_column_1, cases_column_n, controls_column_1, controls_column_n)

`x`	The filtered and annotated 450k probes
`b`	Gene name between quotation marks
`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

 
data(test_data)
data(nonspecific_probes)
data(annotation_file)
test_data_filtered <- filter_data(test_data)
test_data_annotated <- annotate_data(test_data_filtered)
KLHL34 <- plot_gene(test_data_annotated, 'KLHL34', 1, 2, 3, 4)