GenomicTuples is an R/Bioconductor package that defines general
purpose containers for storing and manipulating genomic tuples. A
genomic tuple of size m is of the form
chromosome:strand:{pos_1, pos_2, ..., pos_m} where pos_1 <
pos_2 < ... < pos_m are positions along the chromosome.
GenomicTuples aims to provide functionality for tuples of genomic
co-ordinates that are analogous to those available for genomic ranges in
the
GenomicRanges
R/Bioconductor package.
Most users will want to install GenomicTuples using the current release of Bioconductor using:
if (!requireNamespace("BiocManager", quietly = TRUE)) {
install.packages("BiocManager")
}
BiocManager::install("GenomicTuples")The master branch of this repository is the development version of the package. The development version of GenomicTuples can only be installed using the development version of Bioconductor. Please first read these instructions on installing the development version of Bioconductor; GenomicTuples can then be installed by:
if (!requireNamespace("BiocManager", quietly = TRUE)) {
install.packages("BiocManager")
}
BiocManager::install("GenomicTuples", version = "devel")Here we use the GenomicTuples package to define two GTuples objects, one containing 5 3-tuples and one containing 3 3-tuples, demonstrate how to identify ‘equal’ genomic tuples, and how this calculation would be incorrect if we were to mistakenly treat these genomic tuples as genomic ranges:
# Load the package
library(GenomicTuples)
# Create a GTuples object containing 5 3-tuples
x <- GTuples(
seqnames = c('chr1', 'chr1', 'chr1', 'chr1', 'chr2'),
tuples = matrix(
c(10L, 20L, 30L,
10L, 20L, 30L,
10L, 20L, 35L,
10L, 25L, 30L,
10L, 20L, 30L),
ncol = 3,
byrow = TRUE),
strand = c('+', '-', '*', '+', '+'))
x
#> GTuples object with 5 x 3-tuples and 0 metadata columns:
#> seqnames pos1 pos2 pos3 strand
#> [1] chr1 10 20 30 +
#> [2] chr1 10 20 30 -
#> [3] chr1 10 20 35 *
#> [4] chr1 10 25 30 +
#> [5] chr2 10 20 30 +
#> ---
#> seqinfo: 2 sequences from an unspecified genome; no seqlengths
# Create a new GTuples object containing 3 3-tuples by subsetting x
y <- x[2:4]
y
#> GTuples object with 3 x 3-tuples and 0 metadata columns:
#> seqnames pos1 pos2 pos3 strand
#> [1] chr1 10 20 30 -
#> [2] chr1 10 20 35 *
#> [3] chr1 10 25 30 +
#> ---
#> seqinfo: 2 sequences from an unspecified genome; no seqlengths
# Find equal genomic tuples
subsetByOverlaps(x, y, type = "equal")
#> GTuples object with 3 x 3-tuples and 0 metadata columns:
#> seqnames pos1 pos2 pos3 strand
#> [1] chr1 10 20 30 -
#> [2] chr1 10 20 35 *
#> [3] chr1 10 25 30 +
#> ---
#> seqinfo: 2 sequences from an unspecified genome; no seqlengths
# Find equal genomic tuples when ignoring strand
subsetByOverlaps(x, y, type = "equal", ignore.strand = TRUE)
#> GTuples object with 4 x 3-tuples and 0 metadata columns:
#> seqnames pos1 pos2 pos3 strand
#> [1] chr1 10 20 30 +
#> [2] chr1 10 20 30 -
#> [3] chr1 10 20 35 *
#> [4] chr1 10 25 30 +
#> ---
#> seqinfo: 2 sequences from an unspecified genome; no seqlengths
# Note that if were to mistakenly treat these as genomic ranges, then the set
# of 'equal' genomic tuples would be incorrect since treating these tuples as
# ranges ignores the "internal positions" (pos2).
# The set of overlaps when correctly treated as genomic tuples:
findOverlaps(x, y, type = "equal")
#> Hits object with 3 hits and 0 metadata columns:
#> queryHits subjectHits
#> <integer> <integer>
#> [1] 2 1
#> [2] 3 2
#> [3] 4 3
#> -------
#> queryLength: 5 / subjectLength: 3
# The set of overlaps when incorrected treated as genomic ranges:
findOverlaps(as(x, "GRanges"), as(y, "GRanges"), type = 'equal')
#> Hits object with 4 hits and 0 metadata columns:
#> queryHits subjectHits
#> <integer> <integer>
#> [1] 1 3
#> [2] 2 1
#> [3] 3 2
#> [4] 4 3
#> -------
#> queryLength: 5 / subjectLength: 3GenomicTuples includes extensive documentation available through the R help system:
# See all documentation for the package
help(package = "GenomicTuples")
# See documentation for the GTuples class
?GTuplesThe package also includes a comprehensive vignette that explains in greater detail the different between a genomic tuple and a genomic range, when genomic tuples may be usefu, and common operations on genomic tuples. The vignette can be viewed at http://bioconductor.org/packages/release/bioc/vignettes/GenomicTuples/inst/doc/GenomicTuplesIntroduction.html or accessed from R using:
vignette("GenomicTuplesIntroduction", package = "GenomicTuples")GenomicTuples has been published in The Journal of Open Source Software, http://joss.theoj.org/papers/10.21105/joss.00020.
If you use GenomicTuples, please cite the paper and software version. This can be done as follows:
citation("GenomicTuples")
#>
#> To cite GenomicTuples in publications, please use:
#>
#> Peter F Hickey, (2016) Representation and Manipulation of Genomic
#> Tuples in R. JOSS: doi:10.21105/joss.00020
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Article{,
#> title = {Representation and Manipulation of Genomic Tuples in R},
#> author = {Peter F Hickey},
#> year = {2016},
#> journal = {The Journal of Open Source Software},
#> doi = {http://dx.doi.org/10.21105/joss.00020},
#> url = {http://joss.theoj.org/papers/64b99f363d24b8a7e9025188183e9865},
#> }
packageVersion("GenomicTuples")
#> [1] '1.27.0'GenomicTuples is licensed under Artistic 2.0.
Please note that the GenomicTuples project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.