Introduction
This R package makes the process of generating fragment density plots (also known as “V-plots”) straightforward. V-plots have been introduced for the first time by the Henikoff lab in 2011. Recently, V-plots have proven to be very instructive to understand the molecular organization of the chromatin. For instance, the nucleoATAC package relies on cross-correlation of ATAC-seq fragment density plots to accurately map nucleosome occupancy along the genome.
VplotR aim is to streamline the process of generating V-plots. It contains wrapping functions to import paired-end sequencing bam files and generate V-plots around genomic loci of interest.
VplotR is designed around ggplot2 and makes full use of its potential. As such, it is easy to generate V-plots in batches and combine them with other plots to make publication-ready figures.
VplotR documentation
VplotR documentation is available here or directly within R:
vignette("VplotR")V-plots: what they are and how to interpret them
V-plots are two-dimensional plots of paired-end sequencing fragments from chromatin accessibility assays (e.g. ATAC-seq, MNase-seq or DNAse-seq) of from chromatin immunoprecipitation assays (i.e. ChIP-seq).
The x axis represents the distance between sequencing fragments and genomic loci of interest (e.g. nucleosome-depleted regions, or NDR), while the y axis indicates the length of the sequenced fragments. The color scale indicates the density of fragments mapping over aggregated genomic loci of interest.
Thus, V-plots can reveal where protein bound to DNA (e.g. nucleosomes) protect it from digestion.
System requirements
VplotR has been tested on Mac OS (>= 10.13), Ubuntu (>= 18.04) and Windows Server (2012).
VplotR requires R >= 4.0 and is available from Bioconductor (release > 3.12).
Installation
VplotR and all its dependencies can be installed from Bioconductor:
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("VplotR")
library("VplotR")VplotR developpment version can be installed from Github as follows:
install.packages("devtools")
devtools::install_github("js2264/VplotR")Citation
If you are using VplotR in your research, please cite:
Generating fragment density plots in R/Bioconductor with VplotR
J. Serizay & J. Ahringer
Journal of Open Source Software, 2021
Distinctive regulatory architectures of germline-active and somatic genes in C. elegans
J. Serizay, Y. Dong, J. Jänes, M. Chesney, C. Cerrato & J. Ahringer
Genome Research, 2020
Main functions
The main user-level functions of VplotR are getFragmentsDistribution(), plotVmat(), plotFootprint() and plotProfile().
-
getFragmentsDistribution()computes the distribution of fragment sizes over sets of genomic ranges; -
plotVmat()is used to compute fragment density and generate V-plots; -
plotFootprint()generates the MNase-seq or ATAC-seq footprint at a set of genomic ranges. -
plotProfile()is used to plot the distribution of paired-end fragments at a single locus of interest.
See the package vignette for an in-depth introduction to the package functionalities and the reference for a full description of each function, a list of the available data provided in the package and examples of use cases.
Getting started with VplotR
Plotting a V-plot
V-plots can be generated using the plotVmat() function:
data(MNase_sacCer3_Henikoff2011)
data(ABF1_sacCer3)
p <- plotVmat(
x = MNase_sacCer3_Henikoff2011,
granges = ABF1_sacCer3
)
p
Importing sequencing fragments as GRanges
Paired-end .bam files are imported using the importPEBamFiles() function as follows:
library(VplotR)
bamfile <- system.file("extdata", "ex1.bam", package = "Rsamtools")
fragments <- importPEBamFiles(
bamfile,
shift_ATAC_fragments = TRUE
)
fragments
## GRanges object with 1572 ranges and 0 metadata columns:
## seqnames ranges strand
## <Rle> <IRanges> <Rle>
## [1] seq1 41-215 +
## [2] seq1 54-255 +
## [3] seq1 56-258 +
## [4] seq1 65-255 +
## [5] seq1 65-265 +
## ... ... ... ...
## [1568] seq2 1326-1542 -
## [1569] seq2 1336-1544 -
## [1570] seq2 1358-1550 -
## [1571] seq2 1380-1557 -
## [1572] seq2 1353-1562 -
## -------
## seqinfo: 2 sequences from an unspecified genome; no seqlengthsPlotting fragment size distribution
The distribution of fragment sizes can be computed with the getFragmentsDistribution() function:
library(VplotR)
data(MNase_sacCer3_Henikoff2011)
data(ABF1_sacCer3)
df <- getFragmentsDistribution(
MNase_sacCer3_Henikoff2011,
ABF1_sacCer3
)
p <- ggplot(df, aes(x = x, y = y)) +
geom_line() +
theme_ggplot2() +
labs(x = "Fragment size", y = "# of fragments")
p
Datasets provided in VplotR
Several dataset samples are provided as GRanges object in this package:
- A set of tissue-specific ATAC-seq experiments in young adult C. elegans (Serizay et al., 2020):
## $Germline
## GRanges object with 462371 ranges and 0 metadata columns:
## seqnames ranges strand
## <Rle> <IRanges> <Rle>
## [1] chrI 426-514 +
## [2] chrI 3588-3854 +
## [3] chrI 3640-3798 +
## [4] chrI 3650-3694 +
## [5] chrI 3732-3863 +
## ... ... ... ...
## [462367] chrX 17712277-17712469 -
## [462368] chrX 17712279-17712342 -
## [462369] chrX 17712282-17712565 -
## [462370] chrX 17712285-17712384 -
## [462371] chrX 17712287-17712576 -
## -------
## seqinfo: 7 sequences from an unspecified genome; no seqlengths
##
## $Neurons
## GRanges object with 367935 ranges and 0 metadata columns:
## seqnames ranges strand
## <Rle> <IRanges> <Rle>
## [1] chrI 4011-4241 +
## [2] chrI 7397-7614 +
## [3] chrI 11279-11502 +
## [4] chrI 12744-12819 +
## [5] chrI 14381-14433 +
## ... ... ... ...
## [367931] chrX 17687948-17687982 -
## [367932] chrX 17699614-17699853 -
## [367933] chrX 17706798-17706923 -
## [367934] chrX 17708264-17708347 -
## [367935] chrX 17709920-17710007 -
## -------
## seqinfo: 7 sequences from an unspecified genome; no seqlengths- An MNase-seq experiment in yeast (Henikoff et al., 2011) and associated ABF1 binding sites:
## GRanges object with 400000 ranges and 0 metadata columns:
## seqnames ranges strand
## <Rle> <IRanges> <Rle>
## [1] chrI 2-116 +
## [2] chrI 14-66 +
## [3] chrI 15-134 +
## [4] chrI 54-167 +
## [5] chrI 66-104 +
## ... ... ... ...
## [399996] chrXVI 920439-920471 -
## [399997] chrXVI 920439-920486 -
## [399998] chrXVI 920439-920528 -
## [399999] chrXVI 920442-920659 -
## [400000] chrXVI 920454-920683 -
## -------
## seqinfo: 17 sequences from an unspecified genome- A
.bamfile sample containing 100,000 reads mapped to C. elegans:
## GRanges object with 100000 ranges and 0 metadata columns:
## seqnames ranges strand
## <Rle> <IRanges> <Rle>
## [1] chrI 425-554 +
## [2] chrI 426-555 +
## [3] chrI 459-604 +
## [4] chrI 459-604 +
## [5] chrI 504-634 +
## ... ... ... ...
## [99996] chrI 355817-355907 -
## [99997] chrI 355863-356018 +
## [99998] chrI 355864-355975 +
## [99999] chrI 355880-355917 +
## [100000] chrI 355883-355988 +
## -------
## seqinfo: 7 sequences from an unspecified genome; no seqlengthsFor a full list of the data available in this package, please go to the reference page.
Contributions
Code contributions, bug reports, fixes and feature requests are most welcome. Please make any pull requests against the master branch at https://github.com/js2264/VplotR and file issues at https://github.com/js2264/VplotR/issues.
Feel free to reach out to J. Serizay for any query.
Code of Conduct
Please note that VplotR is released with a Contributor Code of Conduct.
By contributing to this project, you agree to abide by its terms.
