This package can be installed from Bioconductor with the following command:
if (!requireNamespace(BiocManager, quietly = TRUE)) install.packages("BiocManager")
BiocManager::install("SFEData")
library(SFEData)
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
)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")
#> snapshotDate(): 2022-10-24
#> see ?SFEData and browseVignettes('SFEData') for documentation
#> loading from cache
#> require("SpatialFeatureExperiment")
sessionInfo()
#> R version 4.2.1 (2022-06-23)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Ubuntu 20.04.5 LTS
#>
#> Matrix products: default
#> BLAS: /home/biocbuild/bbs-3.16-bioc/R/lib/libRblas.so
#> LAPACK: /home/biocbuild/bbs-3.16-bioc/R/lib/libRlapack.so
#>
#> 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
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] SpatialFeatureExperiment_1.0.0 SFEData_1.0.2
#> [3] BiocStyle_2.26.0
#>
#> loaded via a namespace (and not attached):
#> [1] SpatialExperiment_1.8.0 deldir_1.0-6
#> [3] rjson_0.2.21 ellipsis_0.3.2
#> [5] class_7.3-20 scuttle_1.8.0
#> [7] XVector_0.38.0 GenomicRanges_1.50.0
#> [9] proxy_0.4-27 bit64_4.0.5
#> [11] interactiveDisplayBase_1.36.0 AnnotationDbi_1.60.0
#> [13] fansi_1.0.3 codetools_0.2-18
#> [15] R.methodsS3_1.8.2 sparseMatrixStats_1.10.0
#> [17] cachem_1.0.6 knitr_1.40
#> [19] jsonlite_1.8.3 dbplyr_2.2.1
#> [21] png_0.1-7 R.oo_1.25.0
#> [23] shiny_1.7.3 HDF5Array_1.26.0
#> [25] BiocManager_1.30.19 compiler_4.2.1
#> [27] httr_1.4.4 dqrng_0.3.0
#> [29] assertthat_0.2.1 Matrix_1.5-1
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#> [49] spdep_1.2-7 ExperimentHub_2.6.0
#> [51] DelayedMatrixStats_1.20.0 xfun_0.34
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#> [57] AnnotationHub_3.6.0 edgeR_3.40.0
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#> [61] MatrixGenerics_1.10.0 parallel_4.2.1
#> [63] SummarizedExperiment_1.28.0 rhdf5_2.42.0
#> [65] SingleCellExperiment_1.20.0 yaml_2.3.6
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#> [79] spData_2.2.0 GenomeInfoDb_1.34.0
#> [81] rlang_1.0.6 pkgconfig_2.0.3
#> [83] matrixStats_0.62.0 bitops_1.0-7
#> [85] evaluate_0.17 lattice_0.20-45
#> [87] purrr_0.3.5 Rhdf5lib_1.20.0
#> [89] sf_1.0-8 bit_4.0.4
#> [91] tidyselect_1.2.0 magrittr_2.0.3
#> [93] bookdown_0.29 R6_2.5.1
#> [95] IRanges_2.32.0 magick_2.7.3
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#> [99] DBI_1.1.3 pillar_1.8.1
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#> [103] sp_1.5-0 KEGGREST_1.38.0
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#> [109] KernSmooth_2.23-20 utf8_1.2.2
#> [111] BiocFileCache_2.6.0 rmarkdown_2.17
#> [113] locfit_1.5-9.6 grid_4.2.1
#> [115] blob_1.2.3 digest_0.6.30
#> [117] classInt_0.4-8 xtable_1.8-4
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#> [121] stats4_4.2.1 bslib_0.4.0