This package can be installed from Bioconductor with the following command:
if (!requireNamespace(BiocManager, quietly = TRUE)) install.packages("BiocManager")
BiocManager::install("SFEData")library(SFEData)
#> Warning: replacing previous import 'utils::findMatches' by
#> 'S4Vectors::findMatches' when loading 'AnnotationDbi'Example spatial transcriptomics datasets with Simple Features annotations as SpatialFeatureExperiment objects. These are the datasets available from this package and functions to download the datasets:
Visium:
McKellarMuscleData())McKellarMuscleData())sample_id used for function examples involving multiple samples (McKellarMuscleData())Slide-seq2:
BiermannMelaMetasData())BiermannMelaMetasData())Xenium:
JanesickBreastData())CosMX:
HeNSCLCData())MERFISH:
VizgenLiverData())seqFISH:
LohoffGastrulationData())This package is used extensively in examples and vignettes of the SpatialFeatureExperiment and Voyager packages. The same function is used for different samples from the same study, and the dataset argument determines which sample is downloaded:
sfe <- McKellarMuscleData(dataset = "small")
#> see ?SFEData and browseVignettes('SFEData') for documentation
#> loading from cache
#> require("SpatialFeatureExperiment")sessionInfo()
#> R version 4.3.0 RC (2023-04-13 r84269)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Ubuntu 22.04.2 LTS
#>
#> Matrix products: default
#> BLAS: /home/biocbuild/bbs-3.17-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_GB 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: America/New_York
#> tzcode source: system (glibc)
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] SpatialFeatureExperiment_1.2.0 SFEData_1.2.0
#> [3] BiocStyle_2.28.0
#>
#> loaded via a namespace (and not attached):
#> [1] DBI_1.1.3 bitops_1.0-7
#> [3] deldir_1.0-6 s2_1.1.2
#> [5] rlang_1.1.0 magrittr_2.0.3
#> [7] e1071_1.7-13 matrixStats_0.63.0
#> [9] compiler_4.3.0 RSQLite_2.3.1
#> [11] DelayedMatrixStats_1.22.0 png_0.1-8
#> [13] vctrs_0.6.2 wk_0.7.2
#> [15] pkgconfig_2.0.3 SpatialExperiment_1.10.0
#> [17] crayon_1.5.2 fastmap_1.1.1
#> [19] magick_2.7.4 dbplyr_2.3.2
#> [21] XVector_0.40.0 ellipsis_0.3.2
#> [23] scuttle_1.10.0 utf8_1.2.3
#> [25] promises_1.2.0.1 rmarkdown_2.21
#> [27] purrr_1.0.1 bit_4.0.5
#> [29] xfun_0.39 zlibbioc_1.46.0
#> [31] cachem_1.0.7 beachmat_2.16.0
#> [33] GenomeInfoDb_1.36.0 jsonlite_1.8.4
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#> [39] Rhdf5lib_1.22.0 BiocParallel_1.34.0
#> [41] interactiveDisplayBase_1.38.0 terra_1.7-29
#> [43] parallel_4.3.0 R6_2.5.1
#> [45] bslib_0.4.2 limma_3.56.0
#> [47] boot_1.3-28.1 GenomicRanges_1.52.0
#> [49] jquerylib_0.1.4 Rcpp_1.0.10
#> [51] bookdown_0.33 SummarizedExperiment_1.30.0
#> [53] knitr_1.42 R.utils_2.12.2
#> [55] IRanges_2.34.0 httpuv_1.6.9
#> [57] Matrix_1.5-4 tidyselect_1.2.0
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#> [61] curl_5.0.0 lattice_0.21-8
#> [63] tibble_3.2.1 Biobase_2.60.0
#> [65] shiny_1.7.4 withr_2.5.0
#> [67] KEGGREST_1.40.0 evaluate_0.20
#> [69] sf_1.0-12 spData_2.2.2
#> [71] units_0.8-1 proxy_0.4-27
#> [73] BiocFileCache_2.8.0 ExperimentHub_2.8.0
#> [75] Biostrings_2.68.0 pillar_1.9.0
#> [77] BiocManager_1.30.20 filelock_1.0.2
#> [79] MatrixGenerics_1.12.0 KernSmooth_2.23-20
#> [81] stats4_4.3.0 generics_0.1.3
#> [83] sp_1.6-0 RCurl_1.98-1.12
#> [85] BiocVersion_3.17.1 S4Vectors_0.38.0
#> [87] sparseMatrixStats_1.12.0 xtable_1.8-4
#> [89] class_7.3-21 glue_1.6.2
#> [91] tools_4.3.0 AnnotationHub_3.8.0
#> [93] BiocNeighbors_1.18.0 locfit_1.5-9.7
#> [95] rhdf5_2.44.0 grid_4.3.0
#> [97] spdep_1.2-8 DropletUtils_1.20.0
#> [99] AnnotationDbi_1.62.0 edgeR_3.42.0
#> [101] SingleCellExperiment_1.22.0 GenomeInfoDbData_1.2.10
#> [103] HDF5Array_1.28.0 cli_3.6.1
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#> [111] classInt_0.4-9 BiocGenerics_0.46.0
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