README.md

In LouisKwok-PICB/motifscanr: Tools for Scanning TF motif on DNA regions

motifscanR

Scan input genomic regions with known DNA motifs

Given a set of input genomic regions, motifscanR scans the sequences to detect the occurrences of known motifs. It can also applies a statistical test on each motif to check whether the motif is significantly over- or under-represented (enriched or depleted) in the input genomic regions compared to another set of control regions.

Citation

To cite the motifscanR package in publications, please use

Sun, H., Wang, J., Gong, Z. et al. Quantitative integration of epigenomic variation and transcription factor binding using MAmotif toolkit identifies an important role of IRF2 as transcription activator at gene promoters. Cell Discov 4, 38 (2018).

Installation

The latest version release of motifscanR could install with:

BiocManager::install('LouisKwok-PICB/motifscanR')

Usage

motifscanR could be used for genomic regions motif enrichment analysis with motifScan function.

library(motifscanR)
library(BSgenome.Hsapiens.UCSC.hg19)

# Get a motif pwms
example_motifs <- getJasparMotifs(species = "Homo sapiens",
                                  collection = "CORE")

# Make a set of peaks
peaks <- GenomicRanges::GRanges(seqnames = c("chr1","chr2","chr2"),
                ranges = IRanges::IRanges(start = c(76585873,42772928,100183786),
                                          width = 500))

# Scan motif for example motifs
motif_ix <- motifScan(example_motifs, peaks, genome = "BSgenome.Hsapiens.UCSC.hg19")

The input object of genomic regions could be either GenomicRanges, DNAStringSet, DNAString, or character vector. You could see more detail with ?motifScan

motifscanR could also be used for genomic regions motif enrichment analysis between two sets of genomic regions with motifEnrichment function.

# Get a motif pwms
example_motifs <- getJasparMotifs(species = "Homo sapiens",
                                  collection = "CORE")
# Make a set of input regions
Input <- GenomicRanges::GRanges(seqnames = c("chr1","chr2","chr2"),
                                ranges = IRanges::IRanges(start = c(76585873,42772928,100183786),
                                                          width = 500))
# Make a set of control regions
Control <- GenomicRanges::GRanges(seqnames = c("chr1","chr3","chr5"),
                                  ranges = IRanges::IRanges(start = c(453123,6524593,100184233),
                                                            width = 500))
# Scan motif for example motifs
motif_ix_input <- motifScan(example_motifs, Input, genome = "BSgenome.Hsapiens.UCSC.hg19")
motif_ix_control <- motifScan(example_motifs, Control, genome = "BSgenome.Hsapiens.UCSC.hg19")

# Find Enrichment motif of input by control
Enrichment_result <- motifEnrichment(motif_ix_input, motif_ix_control)

You could type ?motifEnrichment for more detail.

LouisKwok-PICB/motifscanr documentation built on July 22, 2024, 6:36 a.m.