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# Use biomaRt to obtain data.
mart <- "ensemble"
library(biomaRt)
regulatory <- useEnsembl(
biomart = "regulation",
dataset = "hsapiens_regulatory_feature",
GRCh = 37
)
saveRDS(regulatory, "inst/states/regulatory_data.rds")
# Download the regulatory CTCF binding sites and convert them to
# a GRanges object.
CTCF <- getBM(
attributes = c(
"chromosome_name",
"chromosome_start",
"chromosome_end",
"feature_type_name"
),
filters = "regulatory_feature_type_name",
values = "CTCF Binding Site",
mart = regulatory
)
CTCF_g <- reduce(GRanges(
CTCF$chromosome_name,
IRanges(
CTCF$chromosome_start,
CTCF$chromosome_end
)
))
seqlevels(CTCF_g) <- c(1:22, "X", "Y")
CTCF_g <- sort(CTCF_g)
CTCF_g <- CTCF_g[sample.int(length(CTCF_g), 50000)]
saveRDS(CTCF_g, "inst/states/CTCF_g_data.rds")
# Download the promoter regions and conver them to a GRanges object.
promoter <- getBM(
attributes = c(
"chromosome_name", "chromosome_start",
"chromosome_end", "feature_type_name"
),
filters = "regulatory_feature_type_name",
values = "Promoter",
mart = regulatory
)
promoter_g <- reduce(GRanges(
promoter$chromosome_name,
IRanges(
promoter$chromosome_start,
promoter$chromosome_end
)
))
seqlevels(promoter_g) <- c(1:22, "X", "Y")
promoter_g <- sort(promoter_g)
saveRDS(promoter_g, "inst/states/promoter_g_data.rds")
flanking <- getBM(
attributes = c(
"chromosome_name",
"chromosome_start",
"chromosome_end",
"feature_type_name"
),
filters = "regulatory_feature_type_name",
values = "Promoter Flanking Region",
mart = regulatory
)
flanking_g <- reduce(GRanges(
flanking$chromosome_name,
IRanges(
flanking$chromosome_start,
flanking$chromosome_end
)
))
seqlevels(flanking_g) <- c(1:22, "X", "Y")
flanking_g <- sort(flanking_g)
flanking_g <- flanking_g[sample.int(length(flanking_g), 50000)]
saveRDS(flanking_g, "inst/states/promoter_flanking_g_data.rds")
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