This was artificially generated using:
library(GenomicInteractions)
ex_hic <- GInteractions(
GRanges("chr10:103880000-103882500"),
GRanges("chr10:103892500-103895000")
)
ex_hic$distance <- calculateDistances(ex_hic)
library(rtracklayer)
library(plyranges)
library(extraChIPs)
gr <- GRanges("chr10:103860000-103920000")
gtf <- import.gff("path/to/file", type = "gene")
ids <- subsetByOverlaps(gtf, gr)$gene_id
ex_genes <- subset(gtf, gene_id %in% ids) %>%
select(gene = gene_id, symbol = gene_name) %>%
reduceMC()
gtf <- import.gff("path/to/file", type = "exon")
ex_trans <- gtf %>%
subset(gene_id %in% ids) %>%
as_tibble(rangeAsChar = FALSE) %>%
group_by(transcript_id) %>%
mutate(exon = paste0(transcript_id, "_", seq_along(transcript_id))) %>%
makeGRangesFromDataFrame(keep.extra.columns = TRUE, seqinfo = sq) %>%
mutate(feature = as.character(type)) %>%
select(type, gene = gene_id, exon, transcript = transcript_id, symbol = gene_name) %>%
sort() %>%
setNames(.$transcript)
gtf <- import.gff("path/to/file", type = "transcript")
ex_prom <- gtf %>%
promoters(upstream = 1500, downstream = 500) %>%
reduce()
These represent ER binding data from the HCI-005 PDX taken from Hickey et al (2015) The androgen receptor is a tumor suppressor in estrogen receptor-positive breast cancer Nat Med, along with the Input sample. Regions were extracted using
samtools view -h filename.bam "chr10:103860000-103920000" > fileout.bam
samtools index fileout.bam
BigWig files were created by taking bedGraph files as output by macs2 callpeak
,
converting to BigWig using the GRAVI workflow,
loading into R then exporting using
fl <- BigWigFile(file.path("path_to_complete_bigwig"))
bw <- import.bw(fl, which = gr)
export.bw(bw, "path/to/output.bw")
This was taken as the merged sample macs2 callpeak
output in narrowPeak
format and restricted to the above range
peaks <- importPeaks("path/to/source.bed")
export.bed(subsetByOverlaps(peaks[[1]], gr), "path/to/output.bed.gz")
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