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#' @title Map DNAm to target genes using distance approaches, and
#' TF to the DNAm region using JASPAR2020 TFBS.
#' @description This function wraps two other functions
#' \code{get_region_target_gene} and \code{get_tf_in_region} from the package.
#' This function will map a region to a target gene using three methods
#' (mapping to the closest gene,
#' mapping to any gene within a given window of distance, or mapping to a
#' fixed number of nearby genes upstream or downstream).
#' To find TFs binding to the region, JASPAR2020 is used.
#'
#' @importFrom tidyr separate
#' @import GenomicRanges
#' @param region A Granges or a named vector with
#' regions (i.e "chr21:100002-1004000")
#' @param genome Human genome reference "hg38" or "hg19"
#' @param target.method How genes are mapped to regions: regions
#' overlapping gene promoter ("genes.promoter.overlap");
#' genes within a window around the region ("window"); or fixed number of
#' nearby genes upstream and downstream from the region
#' @param target.window.size When \code{method = "window"}, number of base
#' pairs to extend the region (+- window.size/2).
#' Default is 500kbp (or +/- 250kbp, i.e. 250k bp from start or end of the region)
#' @param target.num.flanking.genes Number of flanking genes upstream and
#' downstream to search.
#' For example, if \code{target.num.flanking.genes = 5}, it will return the
#' 5 genes upstream and 5 genes downstream
#' @param target.rm.promoter.regions.from.distal.linking When performing distal linking
#' with method = "windows" or method = "nearby.genes", or "closest.gene.tss",
#' if set to TRUE (default), probes in promoter regions will be removed
#' from the input.
#' @param target.promoter.upstream.dist.tss Number of base pairs (bp) upstream of
#' TSS to consider as promoter regions. Defaults to 2000 bp.
#' @param target.promoter.downstream.dist.tss Number of base pairs (bp) downstream of
#' TSS to consider as promoter regions. Defaults to 2000 bp.
#' @param motif.search.window.size Integer value to extend the regions.
#' For example, a value of 50 will
#' extend 25 bp upstream and 25 downstream the region. Default is no increase
#' @param motif.search.p.cutoff motifmatchr pvalue cut-off. Default 1e-8.
#' @param TF.peaks.gr A granges with TF peaks to be overlaped with input region
#' Metadata column expected "id" with TF name. Default NULL. Note that Remap catalog
#' can be used as shown in the examples.
#' @param max.distance.region.target Max distance between region and target gene. Default 1Mbp.
#' @param cores Number of CPU cores to be used. Default 1.
#' @return A data frame with TF, target and RegionID information.
#' @examples
#' regions.names <- c("chr3:189631389-189632889","chr4:43162098-43163498")
#' triplet <- create_triplet_distance_based(
#' region = regions.names,
#' motif.search.window.size = 500,
#' target.method = "closest.gene"
#' )
#' @export
create_triplet_distance_based <- function(
region,
genome = c("hg38","hg19"),
target.method = c(
"genes.promoter.overlap",
"window",
"nearby.genes",
"closest.gene"
),
target.window.size = 500 * 10^3,
target.num.flanking.genes = 5,
target.promoter.upstream.dist.tss = 2000,
target.promoter.downstream.dist.tss = 2000,
target.rm.promoter.regions.from.distal.linking = TRUE,
motif.search.window.size = 0,
motif.search.p.cutoff = 1e-8,
TF.peaks.gr = NULL,
max.distance.region.target = 10^6,
cores = 1
){
target.method <- match.arg(target.method)
genome <- match.arg(genome)
probeID <- NULL
if (is(region,"character") | is(region,"factor")) {
region.gr <- make_granges_from_names(region)
} else if (is(region,"GenomicRanges")) {
region.gr <- region
if ("probeID" %in% colnames(values(region))) {
probeID <- values(region)$probeID
}
} else if (is(region,"SummarizedExperiment")) {
region.gr <- rowRanges(region)
if ("probeID" %in% colnames(values(region))) {
probeID <- values(region)$probeID
}
} else {
stop(
"region input is a ", class(region),
". Expecting a charcter, GRanges or SE"
)
}
region.names <- make_names_from_granges(region.gr)
message("Finding target genes")
region.target <- get_region_target_gene(
regions.gr = region.gr,
genome = genome,
window.size = target.window.size,
method = target.method,
num.flanking.genes = target.num.flanking.genes,
promoter.upstream.dist.tss = target.promoter.upstream.dist.tss,
promoter.downstream.dist.tss = target.promoter.downstream.dist.tss,
rm.promoter.regions.from.distal.linking = target.rm.promoter.regions.from.distal.linking
)
message("Looking for TFBS")
region.tf <- get_tf_in_region(
region = region.gr,
genome = genome,
window.size = motif.search.window.size,
p.cutoff = motif.search.p.cutoff,
cores = cores,
TF.peaks.gr = TF.peaks.gr
)
triplet <- dplyr::inner_join(region.target, region.tf)
message("Removing regions and target genes from different chromosomes")
triplet <- triplet %>% dplyr::filter(!is.na(.data$distance_region_target_tss))
message("Removing regions and target genes with ditance higher than ", max.distance.region.target, " bp")
triplet <- triplet %>% dplyr::filter(abs(.data$distance_region_target_tss) < max.distance.region.target)
triplet <- triplet %>%
dplyr::relocate(.data$distance_region_target_tss, .after = dplyr::last_col()) %>%
dplyr::relocate(contains("pos"), .after = dplyr::last_col())
if (!is.null(probeID)) {
triplet$probeID <- probeID[match(triplet$regionID, region.names)]
triplet <- triplet %>%
dplyr::relocate(.data$probeID, .after = "regionID")
}
return(triplet)
}
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