VplotR

Jacques Serizay

2022-04-26

Introduction

Overview

VplotR is an R package streamlining the process of generating V-plots, i.e. two-dimensional paired-end fragment density plots. It contains functions to import paired-end sequencing bam files from any type of DNA accessibility experiments (e.g. ATAC-seq, DNA-seq, MNase-seq) and can produce V-plots and one-dimensional footprint profiles over single or aggregated genomic loci of interest. The R package is well integrated within the Bioconductor environment and easily fits in standard genomic analysis workflows. Integrating V-plots into existing analytical frameworks has already brought additional insights in chromatin organization (Serizay et al., 2020).

The main user-level functions of VplotR are getFragmentsDistribution(), plotVmat(), plotFootprint() and plotProfile().

Installation

VplotR can be installed from Bioconductor:

Importing sequencing datasets

Using importPEBamFiles() function

Paired-end .bam files are imported using the importPEBamFiles() function as follows:

Provided datasets

Several datasets are available for this package:

data(ce11_proms)
ce11_proms
#> GRanges object with 17458 ranges and 3 metadata columns:
#>           seqnames            ranges strand |   TSS.fwd   TSS.rev which.tissues
#>              <Rle>         <IRanges>  <Rle> | <numeric> <numeric>      <factor>
#>       [1]     chrI       11273-11423      + |     11294     11416       Intest.
#>       [2]     chrI       11273-11423      - |     11294     11416       Intest.
#>       [3]     chrI       26903-27053      - |     27038     26901       Ubiq.  
#>       [4]     chrI       36019-36169      - |     36112     36028       Intest.
#>       [5]     chrI       42127-42277      - |     42216     42119       Soma   
#>       ...      ...               ...    ... .       ...       ...           ...
#>   [17454]     chrX 17670496-17670646      + |  17670678  17670478  Muscle      
#>   [17455]     chrX 17684894-17685044      - |  17684919  17684932  Hypod.      
#>   [17456]     chrX 17686030-17686180      - |  17686189  17686064  Unclassified
#>   [17457]     chrX 17694789-17694939      + |  17694962  17694934  Intest.     
#>   [17458]     chrX 17711839-17711989      - |  17711974  17711854  Germline    
#>   -------
#>   seqinfo: 6 sequences from an unspecified genome; no seqlengths
data(ATAC_ce11_Serizay2020)
ATAC_ce11_Serizay2020
#> $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

Fragment size distribution

A preliminary control to check the distribution of fragment sizes (regardless of their location relative to genomic loci) can be performed using the getFragmentsDistribution() function.

df <- getFragmentsDistribution(
    MNase_sacCer3_Henikoff2011, 
    ABF1_sacCer3
)
#> Warning in as.cls(x): NAs introduced by coercion

#> Warning in as.cls(x): NAs introduced by coercion

#> Warning in as.cls(x): NAs introduced by coercion
p <- ggplot(df, aes(x = x, y = y)) + geom_line() + theme_ggplot2()
p
#> Warning: Removed 2 row(s) containing missing values (geom_path).

Vplot(s)

Single Vplot

Once data is imported, a V-plot of paired-end fragments over loci of interest is generated using the plotVmat() function:

Multiple Vplots

The generation of multiple V-plots can be parallelized using a list of parameters:

For instance, ATAC-seq fragment density can be visualized at different classes of ubiquitous and tissue-specific promoters in C. elegans.

Vplots normalization

Different normalization approaches are available using the normFun argument.

Footprints

VplotR also implements a function to profile the footprint from MNase or ATAC-seq over sets of genomic loci. For instance, CTCF is known for its ~40-bp large footprint at its binding loci.

p <- plotFootprint(
    MNase_sacCer3_Henikoff2011,
    ABF1_sacCer3
)
#> - Getting cuts
#> - Getting cut coverage
#> - Getting cut coverage / target
#> - Reformatting data into matrix
#> - Plotting footprint
p

Local fragment distribution

VplotR provides a function to plot the distribution of paired-end fragments over an individual genomic window.

data(MNase_sacCer3_Henikoff2011_subset)
genes_sacCer3 <- GenomicFeatures::genes(TxDb.Scerevisiae.UCSC.sacCer3.sgdGene::
    TxDb.Scerevisiae.UCSC.sacCer3.sgdGene
)
p <- plotProfile(
    fragments = MNase_sacCer3_Henikoff2011_subset,
    window = "chrXV:186,400-187,400", 
    loci = ABF1_sacCer3, 
    annots = genes_sacCer3,
    min = 20, max = 200, alpha = 0.1, size = 1.5
)
#> Filtering and resizing fragments
#> 32276 fragments mapped over 1001 bases
#> Filtering and resizing fragments
#> Generating plot
#> Warning: Removed 49 row(s) containing missing values (geom_path).
#> Warning: Removed 5176 rows containing missing values (geom_point).
#> Warning: Removed 19 row(s) containing missing values (geom_path).
p

Session Info

sessionInfo()
#> R version 4.2.0 RC (2022-04-21 r82226)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Ubuntu 20.04.4 LTS
#> 
#> Matrix products: default
#> BLAS:   /home/biocbuild/bbs-3.16-bioc/R/lib/libRblas.so
#> LAPACK: /home/biocbuild/bbs-3.16-bioc/R/lib/libRlapack.so
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=en_GB              LC_COLLATE=C              
#>  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
#>  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
#>  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
#> 
#> attached base packages:
#> [1] stats4    stats     graphics  grDevices utils     datasets  methods  
#> [8] base     
#> 
#> other attached packages:
#> [1] VplotR_1.7.0         magrittr_2.0.3       ggplot2_3.3.5       
#> [4] GenomicRanges_1.49.0 GenomeInfoDb_1.33.0  IRanges_2.31.0      
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#> 
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