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.
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 HG00101Since 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 0The 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 NAAs 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.
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: /github/workspace/pkglib/VariantAnnotation/extdata/chr22.vcf.gz
#> VCF index path: /github/workspace/pkglib/VariantAnnotation/extdata/chr22.vcf.gz.tbi
#> array data: GT
#> dim: 10376 x 5vcffile returns the VcfFile object
corresponding to the backend VCF file.
dim() and dimnames()The dimnames(VCFArray) returns an unnamed list, with the
length of each element being the same as return from
dim(VCFArray).
[ 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 1.609438The 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: /github/workspace/pkglib/VariantAnnotation/extdata/chr22.vcf.gz
#> VCF index path: /github/workspace/pkglib/VariantAnnotation/extdata/chr22.vcf.gz.tbi
#> array data: GT
#> dim: 10376 x 5
path(vcffile(seed))
#> [1] "/github/workspace/pkglib/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.
sessionInfo()
#> R version 4.4.2 (2024-10-31)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 24.04.1 LTS
#>
#> Matrix products: default
#> BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
#> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so; LAPACK version 3.12.0
#>
#> locale:
#> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
#> [3] LC_TIME=en_US.UTF-8 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
#>
#> time zone: Etc/UTC
#> tzcode source: system (glibc)
#>
#> attached base packages:
#> [1] stats4 stats graphics grDevices utils datasets methods
#> [8] base
#>
#> other attached packages:
#> [1] VariantAnnotation_1.53.0 Rsamtools_2.23.0
#> [3] Biostrings_2.75.1 XVector_0.47.0
#> [5] SummarizedExperiment_1.37.0 Biobase_2.67.0
#> [7] GenomicRanges_1.59.0 GenomeInfoDb_1.43.1
#> [9] VCFArray_1.23.0 DelayedArray_0.33.2
#> [11] SparseArray_1.7.2 S4Arrays_1.7.1
#> [13] abind_1.4-8 IRanges_2.41.1
#> [15] S4Vectors_0.45.2 MatrixGenerics_1.19.0
#> [17] matrixStats_1.4.1 Matrix_1.7-1
#> [19] BiocGenerics_0.53.3 generics_0.1.3
#> [21] BiocStyle_2.35.0
#>
#> loaded via a namespace (and not attached):
#> [1] KEGGREST_1.47.0 rjson_0.2.23 xfun_0.49
#> [4] bslib_0.8.0 lattice_0.22-6 vctrs_0.6.5
#> [7] tools_4.4.2 bitops_1.0-9 curl_6.0.1
#> [10] parallel_4.4.2 AnnotationDbi_1.69.0 RSQLite_2.3.8
#> [13] blob_1.2.4 BSgenome_1.75.0 lifecycle_1.0.4
#> [16] GenomeInfoDbData_1.2.13 compiler_4.4.2 codetools_0.2-20
#> [19] GenomicFiles_1.43.0 htmltools_0.5.8.1 sys_3.4.3
#> [22] buildtools_1.0.0 sass_0.4.9 RCurl_1.98-1.16
#> [25] yaml_2.3.10 crayon_1.5.3 jquerylib_0.1.4
#> [28] BiocParallel_1.41.0 cachem_1.1.0 digest_0.6.37
#> [31] restfulr_0.0.15 maketools_1.3.1 fastmap_1.2.0
#> [34] grid_4.4.2 cli_3.6.3 GenomicFeatures_1.59.1
#> [37] XML_3.99-0.17 UCSC.utils_1.3.0 bit64_4.5.2
#> [40] rmarkdown_2.29 httr_1.4.7 bit_4.5.0
#> [43] png_0.1-8 memoise_2.0.1 evaluate_1.0.1
#> [46] knitr_1.49 BiocIO_1.17.0 rtracklayer_1.67.0
#> [49] rlang_1.1.4 DBI_1.2.3 BiocManager_1.30.25
#> [52] jsonlite_1.8.9 R6_2.5.1 GenomicAlignments_1.43.0
#> [55] zlibbioc_1.52.0