create_methyl_region: Create methylation regions for each gene promoter.
In andreaskapou/BPRMeth-devel: Model higher-order methylation profiles

Description Usage Arguments Value Author(s) See Also Examples

create_methyl_region creates methylation regions using BS-Seq and annotated gene promoter regions. BS-Seq data give information for the methylation of CpGs individually, and annotated data are used to locate the TSS of each gene and its promoter region.

create_methyl_region(bs_data, prom_region, cpg_density = 10,
  sd_thresh = 0.1, ignore_strand = TRUE, is_single_cell = FALSE,
  fmin = -1, fmax = 1)

create_methyl_region_array(bs_data, prom_region, cpg_density = 10,
  sd_thresh = 0.1, ignore_strand = TRUE, is_single_cell = FALSE,
  fmin = -1, fmax = 1)

create_methyl_region_saar_levels(bs_data, prom_region, cpg_density = 10,
  sd_thresh = 0.1, ignore_strand = TRUE, is_single_cell = FALSE,
  fmin = -1, fmax = 1)

create_methyl_region_saar_eff(bs_data, prom_region, cpg_density = 10,
  sd_thresh = 0.1, ignore_strand = TRUE, is_single_cell = FALSE,
  fmin = -1, fmax = 1)

`bs_data`	`GRanges` object containing the BS-Seq data. The GRanges object should also have two additional metadata columns named `total_reads` and `meth_reads`. A GRanges object used in this function can be the output of `read_bs_encode_haib` or its wrapper function `preprocess_bs_seq`.
`prom_region`	`GRanges` object containing promoter regions, i.e. N bp upstream and M bp downstream of TSS location. The GRanges object should also have one additional metadata column named `tss`. A GRanges object used in this function can be the output of `create_prom_region`.
`cpg_density`	Optional integer defining the minimum number of CpGs that have to be in a methylated region. Regions with less than `n` CpGs are discarded.
`sd_thresh`	Optional numeric defining the minimum standard deviation of the methylation change in a region. This is used to filter regions with no methylation change.
`ignore_strand`	Logical, whether or not to ignore strand information.
`is_single_cell`	Logical, if we work with single cell data, then we keep only the information of methylated or not for each CpG location.
`fmin`	Optional minimum range value for region location scaling. Under this version, this parameter should be left to its default value.
`fmax`	Optional maximum range value for region location scaling. Under this version, this parameter should be left to its default value.

A methyl_region object containing the following information:

meth_data: A list containing methylation data, where each entry in the list is an L_{i} X 3 dimensional matrix, where L_{i} denotes the number of CpGs found in region i. The columns contain the following information:
1. 1st column: Contains the locations of CpGs relative to TSS. Note that the actual locations are scaled to the (fmin, fmax) region.
2. 2nd column: Contains the total reads of each CpG in the corresponding location. NOTE that for single-cell data this column is not stored in the object.
3. 3rd column: Contains the methylated reads each CpG in the corresponding location.
prom_ind: A vector storing the corresponding promoter indices, so as to map each methylation region with its corresponding gene promoter.

The lengths of meth_data and prom_ind should be the same.

C.A.Kapourani C.A.Kapourani@ed.ac.uk

preprocess_bs_seq, create_prom_region

# Obtain the path to the BS file and then read it
bs_file <- system.file("extdata", "rrbs.bed", package = "BPRMeth")
bs_data <- read_bs_encode_haib(bs_file)

# Create promoter regions
rnaseq_file <- system.file("extdata", "rnaseq.bed", package = "BPRMeth")
annot_data <- read_rna_encode_caltech(rnaseq_file)
prom_region <- create_prom_region(annot_data)

# Finally, create methylation regions
meth_region <- create_methyl_region(bs_data, prom_region)