Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs
Chromatin looping is an essential feature of eukaryotic genomes and can
bring regulatory sequences, such as enhancers or transcription factor
binding sites, in the close physical proximity of regulated target
genes. Here, we provide sevenC, an R package that uses protein binding
signals from ChIP-seq and sequence motif information to predict
chromatin looping events. Cross-linking of proteins that bind close to
loop anchors result in ChIP-seq signals at both anchor loci. These
signals are used at CTCF motif pairs together with their distance and
orientation to each other to predict whether they interact or not. The
resulting chromatin loops might be used to associate enhancers or
transcription factor binding sites (e.g., ChIP-seq peaks) to regulated
target genes.
A more detailed explanation of the sevenC method together with
prediction performance analysis is available in the associated
publication:
Ibn-Salem, J. & Andrade-Navarro, M.A. 7C: Computational Chromosome
Conformation Capture by Correlation of ChIP-seq at CTCF motifs. BMC
Genomics 20, 777 (2019). https://doi.org/10.1186/s12864-019-6088-0
Intallation
To install the sevenC package, start R and enter:
if (!requireNamespace("BiocManager", quietly=TRUE))
install.packages("BiocManager")
BiocManager::install("sevenC")
Alternatively, the development version of sevenC can be installed from
GitHub:
Here we show how to use sevenC to predict chromatin looping
interactions among CTCF motif locations on chromosome 22. As input, we
only use CTCF motif locations and a single bigWig file from a STAT1
ChIP-seq experiment in human GM12878 cells.
Get motif pairs
library(sevenC)
# load provided CTCF motifs in human genome
motifs <- motif.hg19.CTCF.chr22
# get motifs pairs
gi <- prepareCisPairs(motifs, maxDist = 10^6)
Add ChIP-seq data and compute correaltion
# use example ChIP-seq bigWig file
bigWigFile <- system.file("extdata", "GM12878_Stat1.chr22_1-30000000.bigWig",
package = "sevenC")
# add ChIP-seq coverage and compute correaltion at motif pairs
gi <- addCor(gi, bigWigFile)
Predict loops
# predict looping interactions among all motif pairs
loops <- predLoops(gi)
sevenC
Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs
Chromatin looping is an essential feature of eukaryotic genomes and can bring regulatory sequences, such as enhancers or transcription factor binding sites, in the close physical proximity of regulated target genes. Here, we provide sevenC, an R package that uses protein binding signals from ChIP-seq and sequence motif information to predict chromatin looping events. Cross-linking of proteins that bind close to loop anchors result in ChIP-seq signals at both anchor loci. These signals are used at CTCF motif pairs together with their distance and orientation to each other to predict whether they interact or not. The resulting chromatin loops might be used to associate enhancers or transcription factor binding sites (e.g., ChIP-seq peaks) to regulated target genes.
A more detailed explanation of the sevenC method together with prediction performance analysis is available in the associated publication:
Ibn-Salem, J. & Andrade-Navarro, M.A. 7C: Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs. BMC Genomics 20, 777 (2019). https://doi.org/10.1186/s12864-019-6088-0
Intallation
To install the sevenC package, start R and enter:
Alternatively, the development version of sevenC can be installed from GitHub:
Basic usage example
Here we show how to use sevenC to predict chromatin looping interactions among CTCF motif locations on chromosome 22. As input, we only use CTCF motif locations and a single bigWig file from a STAT1 ChIP-seq experiment in human GM12878 cells.
Get motif pairs
Add ChIP-seq data and compute correaltion
Predict loops
For more detailed usage instructions, see the package vignette or reference documentation.
Issues
Please report issues here: https://github.com/ibn-salem/sevenC/issues