In RyDe4/ChIPanalyzer: ChIPAnalyzer

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
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Description

The goal of ChIPAnalyzer is to provide the user with tools for the analysis of ChIP-seq peaks representing protein binding sites on DNA. ChIPAnalyzer provides methods for the analysis of G-quadruplexes predicted by pqsfinder, as well as methods for analysis of ChIP-seq peaks in relation to DNA methylation.

Installation

The package can be installed from GitHub with:

require("devtools")
devtools::install_github("RyDe4/ChIPAnalyzer", build_vignettes = TRUE)
library("ChIPAnalyzer")

#To run the shinyApp:
runChIPAnalyzer()

Overview

ls("package:ChIPAnalyzer")
data(package = "ChIPAnalyzer)

ChIPAnalyzer is a package for the analysis of ChIP-seq data. It has functions for the analysis G-quadruplexes abundance in the vicinity of peaks using pqsfinder and functions for the analysis of DNA methylation of ChIP-seq peaks. See vignettes for details:

browseVignettes("ChIPAnalyzer")

Package Structure:

-ChIPAnalyzer
  |- ChIPAnalyzer.Rproj
  |- DESCRIPTION
  |- LICENSE
  |- README
  |- inst
    |- extdata
      |- MAZ_high_score.bed
      |- HEK293MethylData.bed
  |- man
    |- findQuads.Rd
    |- getMethyOverlap.Rd
    |- getQuadCoveragePercentage.Rd
    |- plotMethylPercentage.Rd
    |- plotMultipleMethylPercentage.Rd
  |- R
    |- MethylSearch.R
    |- QuadCalc.R
    |- Visualization.R
  |- vignettes
    |- Analyze_G-quadruplexes.Rmd
    |- Analyze_Peak_Methylation.Rmd
  |- tests
    |- testthat
      |- MAZ_very_small_test.bed
      |- test-getMethylOverlap.R
      |- test-getQuadCoveragePercentage.R
      |- test-getQuadMatrix.R
      |- test-plotQuadPosition.R
    |- testthat.R

Examples

Below is an example plot of G-quadruplex abundance in the vicinity of MAZ binding sites to serve as an example of what kind of output can be expected in the case of a DNA binding proteing that binds in the vicinity of G-quadruplexes. Note that there is an increase in quadruplex abundance in the vicinity of peaks(position 0). Only the highest scoring quadruplexes are used in this example.

The next example shows the G-quadruplex abundance in the vicinity of FOXA2 binding sites as an example of what the plot will look like for proteins that aren't known to bind near G-quadruplexes. Only the highest scoring quadruplexes are used in this example.

Contributions

All functions in this package were written by the author, Ryan Denniston. The function findQuads() relies on the pqsfinder package to find potential quadruplex strings. For other dependencies, see References. Various packages from the UCSC genome series are used to get sequences in the getSurroundingSeq() helper function. GenomicRanges are used throughout the package to manipulate data read in from BED files Biostrings objects are also used to represent sequences. Methylation example data was retreived from http://hgdownload.cse.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeHaibMethylRrbs/ and ChIP-SEQ example data was retreived from Series GSE104247 on GEO. There is no publication associated with this accession.

References

Lawrence M, Huber W, Pag`es H, Aboyoun P, Carlson M, et al. (2013) Software for Computing and Annotating Genomic Ranges. PLoS Comput Biol 9(8): e1003118. doi:10.1371/journal.pcbi.1003118

The Bioconductor Dev Team (2014). BSgenome.Hsapiens.UCSC.hg19: Full genome sequences for Homo sapiens (UCSC version hg19). R package version 1.4.0.

The Bioconductor Dev Team (2014). BSgenome.Mmusculus.UCSC.mm10: Full genome sequences for Mus musculus (UCSC version mm10). R package version 1.4.0.

The Bioconductor Dev Team (2014). BSgenome.Mmusculus.UCSC.mm9: Full genome sequences for Mus musculus (UCSC version mm9). R package version 1.4.0

The Bioconductor Dev Team (2015). BSgenome.Hsapiens.UCSC.hg38: Full genome sequences for Homo sapiens (UCSC version hg38). R package version 1.4.1.

Hon J, Martinek T, Zendulka J, Lexa M. (2017) pqsfinder: an exhaustive and imperfection-tolerant search tool for potential quadruplex-forming sequences in R. Bioinformatics. 33(21), 3373-3379. https://doi.org/10.1093/bioinformatics/btx413

Tang, D. (2014, January 04). Using ENCODE methylation data. Retrieved October 26, 2020, from https://davetang.org/muse/2013/05/09/using-encode-methylation-data/

H. Pagès, P. Aboyoun, R. Gentleman and S. DebRoy (2019). Biostrings: Efficient manipulation of biological strings. R package version 2.54.0.

Wickham, H. (2015). R Packages. O'Reilly & Associates.

UCSC Genome Browser Maintainers. (2011, September 22). Sequence and Annotation Downloads. Retrieved November 13, 2020, from http://hgdownload.cse.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeHaibMethylRrbs/

Partridge, E. C., Chhetri, S. B., Mendenhall, E. M., & Myers, R. M. (2019, November 27). GEO Accession viewer. Retrieved November 14, 2020, from https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE104247

Winston Chang, Joe Cheng, JJ Allaire, Yihui Xie and Jonathan McPherson (2020). shiny: Web Application Framework for R. R package version 1.5.0. https://CRAN.R-project.org/package=shiny

Grolemund, G. (2015). Learn Shiny - Video Tutorials. \href{https://shiny.rstudio.com/tutorial/}{Link}