Precise knowledge on the binding sites of an RNA-binding protein (RBP) is key to understand (post-) transcriptional regulatory processes. Here we present a workflow that describes how exact binding sites can be defined from iCLIP data. The package provides functions for binding site definition and result visualization. For details please see the vignette.
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See how to installReview the instructions the agent will receive before you install.
library(BindingSiteFinder)
library(txdbmaker)
library(rtracklayer)
# 1. Import crosslink sites
csFile <- system.file("extdata", "PureCLIP_crosslink_sites_examples.bed", package="BindingSiteFinder")
cs <- rtracklayer::import(con = csFile, format = "BED")
# 2. Create metadata table and construct BSFDataSet
files <- system.file("extdata", package="BindingSiteFinder")
clipFilesP <- list.files(files, pattern = "plus.bw$", full.names = TRUE)
clipFilesM <- list.files(files, pattern = "minus.bw$", full.names = TRUE)
meta <- data.frame(
id = 1:4,
condition = factor(rep("WT", 4)),
clPlus = clipFilesP,
clMinus = clipFilesM
)
bds <- BSFDataSetFromBigWig(ranges = cs, meta = meta, silent = TRUE)
# 3. Build gene and transcript region annotations
annoDb <- txdbmaker::makeTxDbFromGFF(file = "gencode_v37_annotation.gff3", format = "gff3")
gns <- genes(annoDb)
regions <- GRangesList(
CDS = cds(annoDb),
Intron = unlist(intronsByTranscript(annoDb)),
UTR3 = unlist(threeUTRsByTranscript(annoDb)),
UTR5 = unlist(fiveUTRsByTranscript(annoDb))
)
# 4. Run BSFind wrapper
bdsOut <- BSFind(
object = bds,
anno.genes = gns,
anno.transcriptRegionList = regions,
est.subsetChromosome = "chr22",
veryQuiet = TRUE
)
# 5. Export results
exportToBED(bdsOut, con = "./myBindingSites.bed")
Input/Output Note: Inputs a BSFDataSet and genomic annotations; outputs a refined BSFDataSet with defined binding sites and exports them to a BED file.
library(BindingSiteFinder)
library(txdbmaker)
# 1. Load Gene Annotations and Transcript Regions
annoDb <- txdbmaker::makeTxDbFromGFF(file = "gencode_v37_annotation.gff3", format = "gff3")
gns <- genes(annoDb)
regions <- GRangesList(
CDS = cds(annoDb),
Intron = unlist(intronsByTranscript(annoDb)),
UTR3 = unlist(threeUTRsByTranscript(annoDb)),
UTR5 = unlist(fiveUTRsByTranscript(annoDb))
)
# 2. Define binding sites for a condition
bdsOut <- BSFind(
object = bds,
anno.genes = gns,
anno.transcriptRegionList = regions,
est.subsetChromosome = "chr22"
)
Input/Output Note: Inputs a BSFDataSet and genomic annotations; outputs a BSFDataSet with defined binding sites prepared for downstream differential testing.
BSFind().genes(), cds(), and intronsByTranscript().DESeq2 or dexseq instead).PureCLIP first, then import results into BindingSiteFinder).GRanges object (typically single-nucleotide wide, e.g., imported from PureCLIP BED files).clPlus and clMinus).GRanges object and transcript regions as a GRangesList (e.g., CDS, Introns, 3' UTR, 5' UTR).BSFDataSet containing crosslink ranges and metadata.GRanges object containing gene annotations.GRangesList containing transcript region annotations.pureClipGlobalFilterPlot() to assess the cutoff.estimateBsWidthPlot() to evaluate the optimal binding site width based on the signal-to-flank ratio.nReps parameter (typically N-1 replicates) and verifying with reproducibilityScatterPlot().overlaps = "keepSingle" in BSFind() to reduce overlapping loci to a single instance.reproducibilityFilterPlot() to inspect and adjust the replicate-specific crosslink threshold.csaw for window-based differential binding analysis of ChIP-seq/ATAC-seq.macsr for peak calling on enrichment data.CLIPreg for integrating CLIP-seq with RNA-seq.No reviews yet. Tell others what you thought.
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