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Export Candidate Gene Regions to BED, CSV, or biomaRt Format

Source: R/haplotype_analysis.R
export_candidate_regions.Rd

Converts the output of define_qtl_regions into formats ready for downstream annotation: standard BED (for BEDtools, UCSC), a plain CSV, or a named list suitable for direct use with biomaRt::getBM() filters.

Usage

export_candidate_regions(
  qtl_regions,
  format = c("bed", "csv", "biomart"),
  out_file = NULL,
  chr_prefix = "",
  use_lead_snp = TRUE,
  padding_bp = 0L
)

Arguments

qtl_regions

Data frame from define_qtl_regions.

format

Character. Output format: "bed", "csv", or "biomart". Default "bed".

out_file

Character path. If NULL (default), returns the object invisibly without writing to disk.

chr_prefix

Character. Prefix to add to chromosome names in BED output (e.g. "chr" for UCSC, "" for Ensembl). Default "".

use_lead_snp

Logical. If TRUE and ld_decay was supplied to define_qtl_regions, use the LD-extended candidate_region_start/candidate_region_end columns instead of block boundaries. Default TRUE.

padding_bp

Integer. Additional bp to add on each side of each region (applied after the LD extension if any). Default 0L.

Value

Invisibly:

"bed"

Data frame with columns chrom, start (0-based), end, name, score, strand.

"csv"

The qtl_regions data frame, optionally written to out_file.

"biomart"

Named list with elements chromosome_name, start, end suitable for biomaRt::getBM(filters = c("chromosome_name","start","end"), ...).

See also

define_qtl_regions, compute_ld_decay

Examples

# \donttest{
data(ldx_geno, ldx_snp_info, ldx_blocks, ldx_gwas, package = "LDxBlocks")
qtl <- define_qtl_regions(ldx_gwas, ldx_blocks, ldx_snp_info,
                           p_threshold = NULL)
# BED file
bed <- export_candidate_regions(qtl, format = "bed", chr_prefix = "chr")
head(bed)
#>   chrom  start    end                  name score strand
#> 1  chr1    999  25027    block_1_1000_25027     3      .
#> 2  chr1  81063  99022   block_1_81064_99022     3      .
#> 3  chr1 155367 179371 block_1_155368_179371     3      .
#> 4  chr2    999  30023    block_2_1000_30023     4      .
#> 5  chr2  86235 105290  block_2_86236_105290     3      .
#> 6  chr3    999  19068    block_3_1000_19068     4      .
# biomaRt-ready list
bm  <- export_candidate_regions(qtl, format = "biomart")
# biomaRt::getBM(attributes = c("ensembl_gene_id","external_gene_name"),
#                filters = c("chromosome_name","start","end"),
#                values  = bm, mart = my_mart)
# }