GDSArray 1.6.0
GDSArray is a Bioconductor package that represents GDS files as
objects derived from the DelayedArray package and DelayedArray
class. It converts a GDS node in the file to a DelayedArray-derived
data structure. The rich common methods and data operations defined on
GDSArray makes it more R-user-friendly than working with the GDS
file directly. The array data from GDS files are always returned with
the first dimension being variants/snps and the second dimension
being samples. This feature is consistent with the assay data saved
in SummarizedExperiment, and makes the GDSArray package
interoperable with other established Bioconductor data
infrastructure.
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("GDSArray")library(GDSArray)The Bioconductor package gdsfmt has provided a high-level R interface to CoreArray Genomic Data Structure (GDS) data files, which is designed for large-scale datasets, especially for data which are much larger than the available random-access memory.
The GDS format has been widely used in genetic/genomic research for
high-throughput genotyping or sequencing data. There are two major
classes that extends the gds.class: SNPGDSFileClass suited for
genotyping data (e.g., GWAS), and SeqVarGDSClass that are designed
specifically for DNA-sequencing data. The file format attribute in
each data class is set as SNP_ARRAY and SEQ_ARRAY. There are rich
functions written based on these data classes for common data
operation and statistical analysis.
More details about GDS format can be found in the vignettes of the gdsfmt, SNPRelate, and SeqArray packages.
GDSArray, GDSMatrix, and GDSFileGDSArray represents GDS 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 [.
The GDSArray() constructor takes as arguments the file path and the
GDS node inside the GDS file. The GDSArray() constructor always
returns the object with rows being features (genes / variants / snps)
and the columns being “samples”. This is consistent with the assay
data inside SummarizedExperiment.
file <- SeqArray::seqExampleFileName("gds")
GDSArray(file, "genotype/data")## <1348 x 90 x 2> array of class GDSArray and type "integer":
## ,,1
## NA06984 NA06985 NA06986 NA06989 ... NA12889 NA12890 NA12891 NA12892
## 1 3 3 0 3 . 0 0 0 0
## 2 3 3 0 3 . 0 0 0 0
## ... . . . . . . . . .
## 1347 0 0 0 0 . 0 0 0 0
## 1348 3 3 0 3 . 3 3 3 3
##
## ,,2
## NA06984 NA06985 NA06986 NA06989 ... NA12889 NA12890 NA12891 NA12892
## 1 3 3 0 3 . 0 0 0 0
## 2 3 3 0 3 . 0 0 0 0
## ... . . . . . . . . .
## 1347 0 0 0 0 . 0 0 0 0
## 1348 3 3 1 3 . 3 3 3 3A GDSMatrix is a 2-dimensional GDSArray, and will be returned from
the GDSArray() constructor automatically if the input GDS node is
2-dimensional.
GDSArray(file, "phase/data")## <1348 x 90> matrix of class GDSMatrix and type "integer":
## NA06984 NA06985 NA06986 NA06989 ... NA12889 NA12890 NA12891 NA12892
## 1 0 0 0 0 . 0 0 0 0
## 2 0 0 0 0 . 0 0 0 0
## 3 0 0 0 0 . 0 0 0 0
## ... . . . . . . . . .
## 1346 0 0 0 0 . 0 0 0 0
## 1347 0 0 0 0 . 0 0 0 0
## 1348 0 0 0 0 . 0 0 0 0GDSFileThe GDSFile is a light-weight class to represent GDS files. It
has the $ completion method to complete any possible gds nodes. It
could be used as a convenient GDSArray constructor if the slot of
current_path in GDSFile object represents a valid gds node.
Otherwise, it will return the GDSFile object with an updated current_path.
gf <- GDSFile(file)
gf$annotation$info## class: GDSFile
## file: /home/biocbuild/bbs-3.10-bioc/R/library/SeqArray/extdata/CEU_Exon.gds
## current node: annotation/info
## subnodes:
## annotation/info/AA
## annotation/info/AC
## annotation/info/AN
## annotation/info/DP
## annotation/info/HM2
## annotation/info/HM3
## annotation/info/OR
## annotation/info/GP
## annotation/info/BNgf$annotation$info$AC## <1348> array of class GDSArray and type "integer":
## 1 2 3 4 . 1345 1346 1347 1348
## 4 1 6 128 . 2 11 1 1Try typing in gf$ann and pressing tab key for the completion.
GDSArray methodsseed returns the GDSArraySeed of the GDSArray object.ga <- GDSArray(file, "genotype/data")
seed(ga)## GDSArraySeed
## gds file: /home/biocbuild/bbs-3.10-bioc/R/library/SeqArray/extdata/CEU_Exon.gds
## array data: genotype/data
## dim: 1348 x 90 x 2gdsfile returns the file path of the corresponding GDS file.gdsfile(ga)## [1] "/home/biocbuild/bbs-3.10-bioc/R/library/SeqArray/extdata/CEU_Exon.gds"gdsnodes() takes the GDS file path or GDSFile object as input, and
returns all nodes that can be converted to GDSArray instances. The
returned GDS node names can be used as input for the GDSArray(name=)
constructor.
gdsnodes(file)## [1] "description" "sample.id"
## [3] "variant.id" "position"
## [5] "chromosome" "allele"
## [7] "genotype/data" "genotype/~data"
## [9] "genotype/extra.index" "genotype/extra"
## [11] "phase/data" "phase/~data"
## [13] "phase/extra.index" "phase/extra"
## [15] "annotation/id" "annotation/qual"
## [17] "annotation/filter" "annotation/info/AA"
## [19] "annotation/info/AC" "annotation/info/AN"
## [21] "annotation/info/DP" "annotation/info/HM2"
## [23] "annotation/info/HM3" "annotation/info/OR"
## [25] "annotation/info/GP" "annotation/info/BN"
## [27] "annotation/format/DP/data" "annotation/format/DP/~data"
## [29] "sample.annotation/family"identical(gdsnodes(file), gdsnodes(gf))## [1] FALSEGDSArray(file, name=gdsnodes(file)[2])## <90> array of class GDSArray and type "character":
## NA06984 NA06985 NA06986 . NA12891 NA12892
## "NA06984" "NA06985" "NA06986" . "NA12891" "NA12892"dim(), dimnames()The dimnames(GDSArray) returns an unnamed list, with the length of
each element to be the same as return from dim(GDSArray).
ga <- GDSArray(file, "phase/data")
dim(ga)## [1] 1348 90class(dimnames(ga))## [1] "list"lengths(dimnames(ga))## variant.id sample.id
## 1348 90[ subsettingGDSArray instances can be subset, following the usual R
conventions, with numeric or logical vectors; logical vectors are
recycled to the appropriate length.
ga[1:3, 10:15]## <3 x 6> matrix of class DelayedMatrix and type "integer":
## sample.id
## variant.id NA07346 NA07347 NA07357 NA10847 NA10851 NA11829
## 1 0 0 0 0 0 0
## 2 0 0 0 0 0 0
## 3 0 0 0 0 0 0ga[c(TRUE, FALSE), ]## <674 x 90> matrix of class DelayedMatrix and type "integer":
## NA06984 NA06985 NA06986 NA06989 ... NA12889 NA12890 NA12891 NA12892
## 1 0 0 0 0 . 0 0 0 0
## 3 0 0 0 0 . 0 0 0 0
## 5 0 0 0 0 . 0 0 0 0
## ... . . . . . . . . .
## 1343 0 0 0 0 . 0 0 0 0
## 1345 0 0 0 0 . 0 0 0 0
## 1347 0 0 0 0 . 0 0 0 0dp <- GDSArray(file, "annotation/format/DP/data")
dp## <1348 x 90> matrix of class GDSMatrix and type "integer":
## NA06984 NA06985 NA06986 NA06989 ... NA12889 NA12890 NA12891 NA12892
## 1 0 0 107 0 . 3 81 67 156
## 2 0 0 92 0 . 4 84 47 150
## 3 12 17 247 11 . 9 217 134 417
## ... . . . . . . . . .
## 1346 5 8 15 1 . 3 61 57 101
## 1347 4 7 26 1 . 4 92 71 144
## 1348 0 0 3 0 . 0 0 2 2log(dp)## <1348 x 90> matrix of class DelayedMatrix and type "double":
## NA06984 NA06985 NA06986 ... NA12891 NA12892
## 1 -Inf -Inf 4.672829 . 4.204693 5.049856
## 2 -Inf -Inf 4.521789 . 3.850148 5.010635
## 3 2.484907 2.833213 5.509388 . 4.897840 6.033086
## ... . . . . . .
## 1346 1.609438 2.079442 2.708050 . 4.0430513 4.6151205
## 1347 1.386294 1.945910 3.258097 . 4.2626799 4.9698133
## 1348 -Inf -Inf 1.098612 . 0.6931472 0.6931472dp[rowMeans(dp) < 60, ]## <413 x 90> matrix of class DelayedMatrix and type "integer":
## NA06984 NA06985 NA06986 NA06989 ... NA12889 NA12890 NA12891 NA12892
## 1 0 0 107 0 . 3 81 67 156
## 2 0 0 92 0 . 4 84 47 150
## 4 15 4 177 1 . 2 110 111 195
## ... . . . . . . . . .
## 1346 5 8 15 1 . 3 61 57 101
## 1347 4 7 26 1 . 4 92 71 144
## 1348 0 0 3 0 . 0 0 2 2GDSArraySeedThe GDSArraySeed class represents the ‘seed’ for the GDSArray
object. It is not exported from the GDSArray package. Seed objects
should contain the GDS file path, and are expected to satisfy the
“seed contract” i.e. to support dim() and dimnames().
seed <- GDSArray:::GDSArraySeed(file, "genotype/data")
seed## GDSArraySeed
## gds file: /home/biocbuild/bbs-3.10-bioc/R/library/SeqArray/extdata/CEU_Exon.gds
## array data: genotype/data
## dim: 1348 x 90 x 2The seed can be used to construct a GDSArray instance.
GDSArray(seed)## <1348 x 90 x 2> array of class GDSArray and type "integer":
## ,,1
## NA06984 NA06985 NA06986 NA06989 ... NA12889 NA12890 NA12891 NA12892
## 1 3 3 0 3 . 0 0 0 0
## 2 3 3 0 3 . 0 0 0 0
## ... . . . . . . . . .
## 1347 0 0 0 0 . 0 0 0 0
## 1348 3 3 0 3 . 3 3 3 3
##
## ,,2
## NA06984 NA06985 NA06986 NA06989 ... NA12889 NA12890 NA12891 NA12892
## 1 3 3 0 3 . 0 0 0 0
## 2 3 3 0 3 . 0 0 0 0
## ... . . . . . . . . .
## 1347 0 0 0 0 . 0 0 0 0
## 1348 3 3 1 3 . 3 3 3 3The DelayedArray() constructor with GDSArraySeed object as
argument will return the same content as the GDSArray() constructor
over the same GDSArraySeed.
class(DelayedArray(seed))## [1] "GDSArray"
## attr(,"package")
## [1] "GDSArray"sessionInfo()## R version 3.6.1 (2019-07-05)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 18.04.3 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.10-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.10-bioc/R/lib/libRlapack.so
##
## 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
##
## attached base packages:
## [1] stats4 parallel stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] GDSArray_1.6.0 DelayedArray_0.12.0 BiocParallel_1.20.0
## [4] IRanges_2.20.0 S4Vectors_0.24.0 matrixStats_0.55.0
## [7] BiocGenerics_0.32.0 gdsfmt_1.22.0 BiocStyle_2.14.0
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.2 compiler_3.6.1 BiocManager_1.30.9
## [4] GenomeInfoDb_1.22.0 XVector_0.26.0 bitops_1.0-6
## [7] tools_3.6.1 zlibbioc_1.32.0 digest_0.6.22
## [10] evaluate_0.14 lattice_0.20-38 rlang_0.4.1
## [13] Matrix_1.2-17 SeqArray_1.26.0 yaml_2.2.0
## [16] xfun_0.10 GenomeInfoDbData_1.2.2 stringr_1.4.0
## [19] knitr_1.25 Biostrings_2.54.0 grid_3.6.1
## [22] rmarkdown_1.16 bookdown_0.14 magrittr_1.5
## [25] htmltools_0.4.0 GenomicRanges_1.38.0 SNPRelate_1.20.0
## [28] stringi_1.4.3 RCurl_1.95-4.12