The goal of nascentrna
is to make it easy to narrow in on interesting regions of genome activity measured by nascent RNA sequencing by classifying these active regions in relation to known, annotated genes using a decision tree.
You can install the latest version of nascentrna from GitHub with:
Below is a basic example of running the annotate()
function to find interesting gene activity.
library(nascentrna) # annotate()
library(rtracklayer) # import.bed()
library(TxDb.Hsapiens.UCSC.hg38.knownGene)
# Obtain transcription start sites derived from experimental nascent RNA data.
file_tss <- system.file(package = "dREG.HD", "extdata", "k562.chr21.predictions.bed")
if (file_tss == "") {
file_tss <- "https://raw.githubusercontent.com/coregenomics/dREG.HD/master/dREG.HD/inst/extdata/k562.chr21.predictions.bed"
}
tss <- import.bed(file_tss)
# Fetch annotated genes near our TSS data.
genes_all <- genes(TxDb.Hsapiens.UCSC.hg38.knownGene)
genes_long <- subsetByOverlaps(genes_all, range(tss * 0.9))
genes <- genes_long[width(genes) < 1e6]
# Find interesting activity by proximity to genes.
annotate(tss, genes)