VCFArray 1.20.0
VCFArray is a Bioconductor package that represents VCF files as
objects derived from the DelayedArray package and DelayedArray
class. It converts data entries from VCF file into a
DelayedArray
-derived data structure. The backend VCF file could
either be saved on-disk locally or remote as online resources. Data
entries that could be extracted include the fixed data fields (REF,
ALT, QUAL, FILTER), information field (e.g., AA, AF…), and the
individual format field (e.g., GT, DP…). The array data generated
from fixed/information fields are one-dimensional VCFArray
, with the
dimension being the length of the variants. The array data generated
from individual FORMAT
field are always returned with the first
dimension being variants
and the second dimension being
samples
. This feature is consistent with the assay data saved in
SummarizedExperiment
, and makes the VCFArray
package interoperable
with other established Bioconductor data infrastructure.
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("VCFArray")
The development version is also available to download from Github.
BiocManager::install("Bioconductor/VCFArray")
library(VCFArray)
To construct a VCFArray
object, 4 arguments are needed: file
,
vindex
and name
, and pfix
. The file
argument could take either
a character string (VCF file name), or VcfFile
object, or a
RangedVcfStack
object. name
argument must be specified to indicate
which data entry we want to extract from the input file. It’s
case-sensitive, and must be consistent with the names from VCF header
file. vindex
argument will only be used to indicate the file path
of the index file if it does not exist. pfix
is used to spefify the
category that the name
field belongs to. NOTE that the pfix
needs to be provided specifically when there are same name
in
multiple categories, otherwise, error will return.
The vcfFields()
method takes the VCF file path, VcfFile
object or
RangedVcfStack
object as input, and returns a CharacterList with all
available VCF fields within specific categories. Users should consult
the fixed
, info
and geno
category for available data entries
that could be converted into VCFArray
instances. The data entry
names can be used as input for the name
argument in VCFArray
constructor.
args(VCFArray)
#> function (file, vindex = character(), name = NA, pfix = NULL)
#> NULL
fl <- system.file("extdata", "chr22.vcf.gz", package = "VariantAnnotation")
library(VariantAnnotation)
vcfFields(fl)
#> CharacterList of length 4
#> [["fixed"]] REF ALT QUAL FILTER
#> [["info"]] LDAF AVGPOST RSQ ERATE THETA ... ASN_AF AFR_AF EUR_AF VT SNPSOURCE
#> [["geno"]] GT DS GL
#> [["samples"]] HG00096 HG00097 HG00099 HG00100 HG00101
Since the index file for our vcf file already exists, the vindex
argument would not be needed (which is the most common case for
on-disk VCF files). So we can construct the VCFArray
object for the
GT
data entry in the provided VCF file with arguments of file
and
name
only.
VCFArray(file = fl, name = "GT")
#> <10376 x 5> VCFMatrix object of type "character":
#> HG00096 HG00097 HG00099 HG00100 HG00101
#> rs7410291 "0|0" "0|0" "1|0" "0|0" "0|0"
#> rs147922003 "0|0" "0|0" "0|0" "0|0" "0|0"
#> rs114143073 "0|0" "0|0" "0|0" "0|0" "0|0"
#> ... . . . . .
#> rs5770892 "0|0" "0|0" "0|0" "0|0" "0|1"
#> rs144055359 "0|0" "0|0" "0|0" "0|0" "0|0"
#> rs114526001 "0|0" "0|0" "0|0" "0|0" "0|0"
We can also construct a VCFArray
object with the file
argument
being a VcfFile
object.
vcf <- VariantAnnotation::VcfFile(fl)
VCFArray(file = vcf, name = "DS")
#> <10376 x 5> VCFMatrix object of type "double":
#> HG00096 HG00097 HG00099 HG00100 HG00101
#> rs7410291 0 0 1 0 0
#> rs147922003 0 0 0 0 0
#> rs114143073 0 0 0 0 0
#> ... . . . . .
#> rs5770892 0 0 0 0 1
#> rs144055359 0 0 0 0 0
#> rs114526001 0 0 0 0 0
The file
argument could also take RangedVcfStack
object. Note that
an ordinary VcfStack
object without Range
information could not
be used to construct a VCFArray
.
extdata <- system.file(package = "GenomicFiles", "extdata")
files <- dir(extdata, pattern="^CEUtrio.*bgz$", full=TRUE)[1:2]
names(files) <- sub(".*_([0-9XY]+).*", "\\1", basename(files))
seqinfo <- as(readRDS(file.path(extdata, "seqinfo.rds")), "Seqinfo")
stack <- GenomicFiles::VcfStack(files, seqinfo)
gr <- as(GenomicFiles::seqinfo(stack)[rownames(stack)], "GRanges")
## RangedVcfStack
rgstack <- GenomicFiles::RangedVcfStack(stack, rowRanges = gr)
rgstack
#> VcfStack object with 2 files and 3 samples
#> GRanges object with 2 ranges and 0 metadata columns
#> Seqinfo object with 25 sequences from hg19 genome
#> use 'readVcfStack()' to extract VariantAnnotation VCF.
Here we choose the name = SB
, which returns a 3-dimensional
VCFArray
object, with the first 2 dimensions correspond to variants
and samples respectively.
vcfFields(rgstack)$geno
#> [1] "GT" "AD" "DP" "GQ" "MIN_DP" "PGT" "PID" "PL"
#> [9] "SB"
VCFArray(rgstack, name = "SB")
#> <318 x 3 x 4> VCFArray object of type "integer":
#> ,,1
#> NA12878 NA12891 NA12892
#> rs771898125 NA NA NA
#> rs6118055 NA NA NA
#> ... . . .
#> rs2009307 NA NA NA
#> rs2273444 NA NA NA
#>
#> ...
#>
#> ,,4
#> NA12878 NA12891 NA12892
#> rs771898125 NA NA NA
#> rs6118055 NA NA NA
#> ... . . .
#> rs2009307 NA NA NA
#> rs2273444 NA NA NA
As the vignette title suggest, the backend VCF file could also be
remote files. Here we included an example of representing VCF file of
chromosome 22 from the 1000 Genomes Project (Phase 3). NOTE that for
a remote VCF file, the vindex
argument must be specified. Since
this VCF files is relatively big, and it takes longer time, we only
show the code here without evaluation.
chr22url <- "https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20130502/ALL.chr22.phase3_shapeit2_mvncall_integrated_v5b.20130502.genotypes.vcf.gz"
chr22url.tbi <- paste0(chr22url, ".tbi")
va <- VCFArray(chr22url, vindex =chr22url.tbi, name = "GT")
VCFArray
represents VCF files as DelayedArray
instances. It has
methods like dim
, dimnames
defined, and it inherits array-like
operations and methods from DelayedArray
, e.g., the subsetting
method of [
.
NOTE that for 1-dimensional VCFArray
objects that are generated
from the fixed / information data field of VCF file, drop = FALSE
should always be used with [
subsetting to ensure VCFArray
object
as returned value.
seed
returns the VCFArraySeed
of the VCFArray
object, which
includes information about the backend VCF file, e.g., the vcf file
path, index file path, name of the data entry (with a prefix of
category), dimension and etc.
va <- VCFArray(fl, name = "GT")
seed(va)
#> VCFArraySeed
#> VCF file path: /home/biocbuild/bbs-3.19-bioc/R/site-library/VariantAnnotation/extdata/chr22.vcf.gz
#> VCF index path: /home/biocbuild/bbs-3.19-bioc/R/site-library/VariantAnnotation/extdata/chr22.vcf.gz.tbi
#> array data: GT
#> dim: 10376 x 5
vcffile
returns the VcfFile
object corresponding to the backend
VCF file.
vcffile(va)
#> class: VcfFile
#> path: /home/biocbuild/bbs-3.19-bioc/R/site-library/VariantAnnota.../chr22.vcf.gz
#> index: /home/biocbuild/bbs-3.19-bioc/R/site-library/VariantA.../chr22.vcf.gz.tbi
#> isOpen: FALSE
#> yieldSize: NA
dim()
and dimnames()
The dimnames(VCFArray)
returns an unnamed list, with the length of
each element being the same as return from dim(VCFArray)
.
va <- VCFArray(fl, name = "GT")
dim(va)
#> [1] 10376 5
class(dimnames(va))
#> [1] "list"
lengths(dimnames(va))
#> [1] 10376 5
[
subsettingVCFArray
instances can be subsetted, following the usual R
conventions, with numeric or logical vectors; logical vectors are
recycled to the appropriate length.
va[1:3, 1:3]
#> <3 x 3> DelayedMatrix object of type "character":
#> HG00096 HG00097 HG00099
#> rs7410291 "0|0" "0|0" "1|0"
#> rs147922003 "0|0" "0|0" "0|0"
#> rs114143073 "0|0" "0|0" "0|0"
va[c(TRUE, FALSE), ]
#> <5188 x 5> DelayedMatrix object of type "character":
#> HG00096 HG00097 HG00099 HG00100 HG00101
#> rs7410291 "0|0" "0|0" "1|0" "0|0" "0|0"
#> rs114143073 "0|0" "0|0" "0|0" "0|0" "0|0"
#> rs182170314 "0|0" "0|0" "0|0" "0|0" "0|0"
#> ... . . . . .
#> rs9628212 "0|0" "0|0" "0|0" "0|0" "0|0"
#> rs9628178 "0|0" "0|0" "0|0" "0|0" "0|0"
#> rs144055359 "0|0" "0|0" "0|0" "0|0" "0|0"
Numeric calculations could be evaluated on VCFArray
objects.
ds <- VCFArray(fl, name = "DS")
log(ds+5)
#> <10376 x 5> DelayedMatrix object of type "double":
#> HG00096 HG00097 HG00099 HG00100 HG00101
#> rs7410291 1.609438 1.609438 1.791759 1.609438 1.609438
#> rs147922003 1.609438 1.609438 1.609438 1.609438 1.609438
#> rs114143073 1.609438 1.609438 1.609438 1.609438 1.609438
#> ... . . . . .
#> rs5770892 1.609438 1.609438 1.609438 1.609438 1.791759
#> rs144055359 1.609438 1.609438 1.609438 1.609438 1.609438
#> rs114526001 1.609438 1.609438 1.609438 1.609438 1.609438
The VCFArraySeed
class represents the ‘seed’ for the VCFArray
object. It is not exported from the VCFArray package. Seed objects
should contain the VCF file path, and are expected to satisfy the
“seed contract” of DelayedArray, i.e. to support dim()
and
dimnames()
.
seed <- VCFArray:::VCFArraySeed(fl, name = "GT", pfix = NULL)
seed
#> VCFArraySeed
#> VCF file path: /home/biocbuild/bbs-3.19-bioc/R/site-library/VariantAnnotation/extdata/chr22.vcf.gz
#> VCF index path: /home/biocbuild/bbs-3.19-bioc/R/site-library/VariantAnnotation/extdata/chr22.vcf.gz.tbi
#> array data: GT
#> dim: 10376 x 5
path(vcffile(seed))
#> [1] "/home/biocbuild/bbs-3.19-bioc/R/site-library/VariantAnnotation/extdata/chr22.vcf.gz"
The seed can be used to construct a VCFArray
instance.
(va <- VCFArray(seed))
#> <10376 x 5> VCFMatrix object of type "character":
#> HG00096 HG00097 HG00099 HG00100 HG00101
#> rs7410291 "0|0" "0|0" "1|0" "0|0" "0|0"
#> rs147922003 "0|0" "0|0" "0|0" "0|0" "0|0"
#> rs114143073 "0|0" "0|0" "0|0" "0|0" "0|0"
#> ... . . . . .
#> rs5770892 "0|0" "0|0" "0|0" "0|0" "0|1"
#> rs144055359 "0|0" "0|0" "0|0" "0|0" "0|0"
#> rs114526001 "0|0" "0|0" "0|0" "0|0" "0|0"
The DelayedArray()
constructor with VCFArraySeed
object as inputs
will return the same content as the VCFArray()
constructor over the
same VCFArraySeed
.
da <- DelayedArray(seed)
class(da)
#> [1] "VCFMatrix"
#> attr(,"package")
#> [1] "VCFArray"
all.equal(da, va)
#> [1] TRUE
sessionInfo()
#> R version 4.4.0 beta (2024-04-15 r86425)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 22.04.4 LTS
#>
#> Matrix products: default
#> BLAS: /home/biocbuild/bbs-3.19-bioc/R/lib/libRblas.so
#> LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
#>
#> locale:
#> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
#> [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
#> [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
#>
#> time zone: America/New_York
#> tzcode source: system (glibc)
#>
#> attached base packages:
#> [1] stats4 stats graphics grDevices utils datasets methods
#> [8] base
#>
#> other attached packages:
#> [1] VariantAnnotation_1.50.0 Rsamtools_2.20.0
#> [3] Biostrings_2.72.0 XVector_0.44.0
#> [5] SummarizedExperiment_1.34.0 Biobase_2.64.0
#> [7] GenomicRanges_1.56.0 GenomeInfoDb_1.40.0
#> [9] VCFArray_1.20.0 DelayedArray_0.30.0
#> [11] SparseArray_1.4.0 S4Arrays_1.4.0
#> [13] abind_1.4-5 IRanges_2.38.0
#> [15] S4Vectors_0.42.0 MatrixGenerics_1.16.0
#> [17] matrixStats_1.3.0 Matrix_1.7-0
#> [19] BiocGenerics_0.50.0 BiocStyle_2.32.0
#>
#> loaded via a namespace (and not attached):
#> [1] KEGGREST_1.44.0 rjson_0.2.21 xfun_0.43
#> [4] bslib_0.7.0 lattice_0.22-6 vctrs_0.6.5
#> [7] tools_4.4.0 bitops_1.0-7 curl_5.2.1
#> [10] parallel_4.4.0 AnnotationDbi_1.66.0 RSQLite_2.3.6
#> [13] blob_1.2.4 BSgenome_1.72.0 lifecycle_1.0.4
#> [16] GenomeInfoDbData_1.2.12 compiler_4.4.0 codetools_0.2-20
#> [19] GenomicFiles_1.40.0 htmltools_0.5.8.1 sass_0.4.9
#> [22] RCurl_1.98-1.14 yaml_2.3.8 crayon_1.5.2
#> [25] jquerylib_0.1.4 BiocParallel_1.38.0 cachem_1.0.8
#> [28] digest_0.6.35 restfulr_0.0.15 bookdown_0.39
#> [31] fastmap_1.1.1 grid_4.4.0 cli_3.6.2
#> [34] GenomicFeatures_1.56.0 XML_3.99-0.16.1 UCSC.utils_1.0.0
#> [37] bit64_4.0.5 rmarkdown_2.26 httr_1.4.7
#> [40] bit_4.0.5 png_0.1-8 memoise_2.0.1
#> [43] evaluate_0.23 knitr_1.46 BiocIO_1.14.0
#> [46] rtracklayer_1.64.0 rlang_1.1.3 DBI_1.2.2
#> [49] BiocManager_1.30.22 jsonlite_1.8.8 R6_2.5.1
#> [52] GenomicAlignments_1.40.0 zlibbioc_1.50.0