# PlinkMatrix: DelayedArray interface to plink bed-type files

# Introduction

Many genetic studies employ PLINK for data management and analysis.

This package facilitates interrogation of PLINK bed files through the Bioconductor DelayedArray protocol

# Installation

Use Bioconductor 3.23.

    BiocManager::install("PlinkMatrix")

# Demonstration

The `example_PlinkMatrix` function will

- retrieve a zip archive from a cloud store if needed, and place it in the default BiocFileCache cache
- unzip the cached archive to bed, bim, fam files
- create the DelayedArray interface to the unzipped archive

The example data are those distributed with tensorQTL, transformed to bed using plink2.

    library(PlinkMatrix)
    gdemo <- example_PlinkMatrix()

    colnames(gdemo) <- gsub("0_", "", colnames(gdemo))
    gdemo

    ## <367759 x 445> DelayedMatrix object of type "double":
    ##                         HG00096 HG00097 HG00099 ... NA20826 NA20828
    ##     chr18_10644_C_G_b38       0       0       0   .       0       0
    ##     chr18_10847_C_A_b38       0       0       0   .       0       0
    ##     chr18_11275_G_A_b38       0       0       0   .       0       0
    ##     chr18_11358_G_A_b38       0       0       0   .       0       0
    ##     chr18_11445_G_A_b38       0       0       0   .       0       0
    ##                     ...       .       .       .   .       .       .
    ## chr18_80259028_AG_A_b38       1       2       2   .       0       1
    ##  chr18_80259147_G_C_b38       0       0       0   .       0       0
    ##  chr18_80259181_A_G_b38       0       0       0   .       0       0
    ##  chr18_80259190_C_G_b38       1       0       0   .       1       0
    ##  chr18_80259245_C_A_b38       0       0       0   .       0       0

# Sanity check

We will use ancestry information and approximate PCA to illustrate plausibility of the approach used here.

We have codes for the ancestral origins of samples.

    data(g445samples)
    table(g445samples$Population.code)

    ##
    ## CEU FIN GBR TSI YRI
    ##  89  92  86  91  87

We’ll take a random sample of 1000 SNP and retrieve 10 PCs, then visualize aspects of the reexpression to PCs for discriminating population of ancestry.

    library(irlba)
    set.seed(1234)
    ss <- sort(sample(seq_len(nrow(gdemo)), size = 1000))
    pca <- prcomp_irlba(t(gdemo[ss, ]), 10)
    pairs(pca$x[, 1:4], col = factor(g445samples$Population.code), pch = 19, cex = .5)

    boxplot(split(pca$x[, 2] + pca$x[, 1], g445samples$Population.code))

# SummarizedExperiment wrapper; subsetting with GenomicRanges

    data(example_GRanges)
    library(SummarizedExperiment)
    nse <- SummarizedExperiment(list(genotypes = gdemo),
      rowData = example_GRanges, colData = g445samples
    )
    nse

    ## class: RangedSummarizedExperiment
    ## dim: 367759 445
    ## metadata(0):
    ## assays(1): genotypes
    ## rownames(367759): chr18_10644_C_G_b38 chr18_10847_C_A_b38 ...
    ##   chr18_80259190_C_G_b38 chr18_80259245_C_A_b38
    ## rowData names(0):
    ## colnames(445): HG00096 HG00097 ... NA20826 NA20828
    ## colData names(5): Sex Population.code Population.name
    ##   Superpopulation.code Superpopulation.name

    little <- GenomicRanges::GRanges("chr18:1-100000")
    subsetByOverlaps(nse, little)

    ## class: RangedSummarizedExperiment
    ## dim: 353 445
    ## metadata(0):
    ## assays(1): genotypes
    ## rownames(353): chr18_10644_C_G_b38 chr18_10847_C_A_b38 ...
    ##   chr18_99977_C_T_b38 chr18_99998_G_A_b38
    ## rowData names(0):
    ## colnames(445): HG00096 HG00097 ... NA20826 NA20828
    ## colData names(5): Sex Population.code Population.name
    ##   Superpopulation.code Superpopulation.name

# Session information

    sessionInfo()

    ## R version 4.6.0 (2026-04-24)
    ## Platform: x86_64-pc-linux-gnu
    ## Running under: Ubuntu 24.04.4 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=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: Etc/UTC
    ## tzcode source: system (glibc)
    ##
    ## attached base packages:
    ## [1] stats4    stats     graphics  grDevices utils     datasets  methods
    ## [8] base
    ##
    ## other attached packages:
    ##  [1] irlba_2.3.7                 PlinkMatrix_1.0.0
    ##  [3] SummarizedExperiment_1.42.0 Biobase_2.72.0
    ##  [5] GenomicRanges_1.64.0        Seqinfo_1.2.0
    ##  [7] DelayedArray_0.38.1         SparseArray_1.12.0
    ##  [9] S4Arrays_1.12.0             abind_1.4-8
    ## [11] IRanges_2.46.0              S4Vectors_0.50.0
    ## [13] MatrixGenerics_1.24.0       matrixStats_1.5.0
    ## [15] BiocGenerics_0.58.0         generics_0.1.4
    ## [17] Matrix_1.7-5                Rcpp_1.1.1-1.1
    ## [19] BiocStyle_2.40.0
    ##
    ## loaded via a namespace (and not attached):
    ##  [1] rappdirs_0.3.4      sass_0.4.10         RSQLite_2.4.6
    ##  [4] lattice_0.22-9      magrittr_2.0.5      digest_0.6.39
    ##  [7] evaluate_1.0.5      grid_4.6.0          fastmap_1.2.0
    ## [10] blob_1.3.0          jsonlite_2.0.0      DBI_1.3.0
    ## [13] BiocManager_1.30.27 purrr_1.2.2         httr2_1.2.2
    ## [16] jquerylib_0.1.4     cli_3.6.6           rlang_1.2.0
    ## [19] dbplyr_2.5.2        XVector_0.52.0      bit64_4.8.0
    ## [22] withr_3.0.2         cachem_1.1.0        yaml_2.3.12
    ## [25] tools_4.6.0         memoise_2.0.1       dplyr_1.2.1
    ## [28] filelock_1.0.3      curl_7.1.0          buildtools_1.0.0
    ## [31] vctrs_0.7.3         R6_2.6.1            lifecycle_1.0.5
    ## [34] BiocFileCache_3.2.0 bit_4.6.0           pkgconfig_2.0.3
    ## [37] pillar_1.11.1       bslib_0.10.0        glue_1.8.1
    ## [40] tidyselect_1.2.1    tibble_3.3.1        xfun_0.57
    ## [43] sys_3.4.3           knitr_1.51          htmltools_0.5.9
    ## [46] rmarkdown_2.31      maketools_1.3.2     compiler_4.6.0