preprocess_final_HTS_data {BPRMeth} | R Documentation |
(DEPRECATED) preprocess_final_HTS_data
performs a final
filtering and preprocessing on the data for use in downstream analysis.
These include, removing noisy gene expression data, removing or not
un-expressed genes and log2-transorming of the FPKM values.
preprocess_final_HTS_data(methyl_region, prom_reg, rna_data, gene_log2_transf = TRUE, gene_outl_thresh = TRUE, gex_outlier = 300)
methyl_region |
Methylation region data, which are the output of the
" |
prom_reg |
A |
rna_data |
A |
gene_log2_transf |
Logical, whether or not to log2 transform the gene expression data. |
gene_outl_thresh |
Logical, whehter or not to remove outlier gene expression data. |
gex_outlier |
Numeric, denoting the threshold above of which the gene expression data (before the log2 transformation) are considered as noise. |
An object which contains following information:
methyl_region
: The subset of promoter methylation region data after
the filtering process.
gex
: A vectoring storing only the
corresponding gene expression values for each promoter region.
rna_data
: The corresponding gene expression data stored as a GRanges
object.
C.A.Kapourani C.A.Kapourani@ed.ac.uk
read_rna_encode_caltech
process_haib_caltech_wrap
# 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_anno_region(annot_data) # Create methylation regions methyl_reg <- create_region_object(bs_data, prom_region, filter_empty_region = FALSE) # Keep only covered genomic regions cov_ind <- which(!is.na(methyl_reg)) methyl_reg <- methyl_reg[cov_ind] prom_region <- prom_region[cov_ind, ] annot_data <- annot_data[cov_ind, ] # Finally preprocess the HTS data res <- preprocess_final_HTS_data(methyl_reg, prom_region, annot_data)