process_beatson_enh_wrap: Wrapper method for processing Beatson enhancer RNA-Seq and...
In andreaskapou/processHTS: Process HTS Files and Data

Description Usage Arguments Value Author(s) Examples

process_beatson_enh_wrap is a wrapper method for processing HTS data and returning the methylation enhancer regions and the corresponding gene expression data for those enhancer regions. Note that the format of BS-Seq data should be in the Bismark Cov format and for the RNA-Seq data in Beatson format.

process_beatson_enh_wrap(bs_files, rna_files, enh_files,
  chrom_size_file = NULL, chr_discarded = NULL, upstream = -15000,
  downstream = 15000, min_bs_cov = 0, max_bs_cov = 1000,
  cpg_density = 1, sd_thresh = 0, ignore_strand = FALSE, fmin = -1,
  fmax = 1)

`bs_files`	Filename (or vector of filenames if there are replicates) of the BS-Seq '.bed' formatted data to read values from.
`rna_files`	Filename of the RNA-Seq '.bed' formatted data to read values from. Currently, this version does not support pooling RNA-Seq replicates.
`enh_files`	Filename of the enhancer annotation .bed formatted data.
`chrom_size_file`	Optional filename containing genome chromosome sizes.
`chr_discarded`	A vector with chromosome names to be discarded.
`upstream`	Integer defining the length of bp upstream of TSS for creating the promoter region.
`downstream`	Integer defining the length of bp downstream of TSS for creating the promoter region.
`min_bs_cov`	The minimum number of reads mapping to each CpG site. CpGs with less reads will be considered as noise and will be discarded.
`max_bs_cov`	The maximum number of reads mapping to each CpG site. CpGs with more reads will be considered as noise and will be discarded.
`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.
`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 processHTS object which contains following information:

methyl_region: 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.
3. 3rd column: Contains the methylated reads each CpG in the corresponding location.
prom_region: A GRanges object containing corresponding annotated promoter regions for each entry of the methyl_region list. The GRanges object has one additional metadata column named tss, which stores the TSS of each promoter.
rna_data: A GRanges object containing the corresponding RNA-Seq data for each entry of the methyl_region list. The GRanges object has three additional metadata columns which are explained in read_rna_beatson
upstream: Integer defining the length of bp upstream of TSS.
downstream: Integer defining the length of bp downstream of TSS.
cpg_density: 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: Numeric defining the minimum standard deviation of the methylation change in a region. This is used to filter regions with no methylation change.
fmin: Minimum range value for region location scaling.
fmax: Maximum range value for region location scaling.

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

# Get the location of the files
bs_file <- system.file("extdata", "bism_rep1.bed", package = "processHTS")
rna_file <- system.file("extdata", "rna_beatson2.bed", package = "processHTS")
enh_file <- system.file("extdata", "enhancers_beatson.bed", package = "processHTS")
#data <- process_beatson_enh_wrap(bs_file, rna_file, enh_file)