In RyDe4/ChIPanalyzer: ChIPAnalyzer

knitr::opts_chunk$set(
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ChIPAnalyzer is an R package for investigating ChIP-seq peak calling data. ChIPAnalyzer has functions for analyzing G-quadruplex abundance in the vicinity of ChIP-seq peaks as well as functions for analyzing the DNA methylation of peaks.

library(ChIPAnalyzer)
ls("package:ChIPAnalyzer")

Executing the following set of commands will generate a plot of G-quadruplex abundance in the vicinity of ChIP-seq peaks.

system.file("extdata", "MAZ_high_score.bed", package = "ChIPAnalyzer")
reports <- findQuads(bedPath = "MAZ_high_score.bed",
seqWidth = 275,
   assemblyVersion = "hg19")
 qMatrix <- getQuadMatrix(quadReports = reports, maxOnly = TRUE)
 quadCoveragePercentage <- getQuadCoveragePercentage(quadMatrix = qMatrix)
plotQuadPosition(quadCoveragePercentage, "MAZ G-Quad Abundance")

The image below shows the plot generated by this code. The vertical line in the centre of the plot represents the centre of a peak and the numbers on the x axis to the left and right represent a position upstream or downstream from a peak. The percentage on the y-axis represents the percentage of peaks that have a G-quadruplex at the given position.

Executing the following code will plot a pie graph of the percentage of bases within peaks that are methylated.

system.file("extdata", "MAZ_high_score.bed", package = "ChIPAnalyzer")
system.file("extdata", "HcfUMethylData.bed", package = "ChIPAnalyzer")
overlap <- getMethylOverlap("MAZ_high_score.bed", "HcfUMethylData.bed")
plotMethylPercentage(overlap)

We can see below that about 97.7% of bases in the MAZ peaks are not methylated

ChIPAnalyzer also offers a Shiny GUI for ease of use.

#to run the ChIPAnalyzer Shiny App
runChIPAnalyzer()

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}

RyDe4/ChIPanalyzer documentation built on Sept. 1, 2023, 9:18 a.m.