Transcripts per million (TPM) single cell RNA-Seq data for 5,902 cells from 18 patients–oral cavity head and neck squamous cell carcinoma (HNSC)– are available from GEO GSE103322. These data are also available as a SingleCellExpression from ExperimentHub.
In the example below, we show how this dataset can be dwnloaded from ExperimentHub.
library(ExperimentHub)## Loading required package: BiocGenerics##
## Attaching package: 'BiocGenerics'## The following objects are masked from 'package:stats':
##
## IQR, mad, sd, var, xtabs## The following objects are masked from 'package:base':
##
## Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
## as.data.frame, basename, cbind, colnames, dirname, do.call,
## duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
## lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
## pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
## tapply, union, unique, unsplit, which.max, which.min## Loading required package: AnnotationHub## Loading required package: BiocFileCache## Loading required package: dbplyrlibrary(SingleCellExperiment)## Loading required package: SummarizedExperiment## Loading required package: MatrixGenerics## Loading required package: matrixStats##
## Attaching package: 'MatrixGenerics'## The following objects are masked from 'package:matrixStats':
##
## colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
## colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
## colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
## colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
## colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
## colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
## colWeightedMeans, colWeightedMedians, colWeightedSds,
## colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
## rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
## rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
## rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
## rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
## rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
## rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
## rowWeightedSds, rowWeightedVars## Loading required package: GenomicRanges## Loading required package: stats4## Loading required package: S4Vectors##
## Attaching package: 'S4Vectors'## The following objects are masked from 'package:base':
##
## I, expand.grid, unname## Loading required package: IRanges## Loading required package: GenomeInfoDb## Loading required package: Biobase## Welcome to Bioconductor
##
## Vignettes contain introductory material; view with
## 'browseVignettes()'. To cite Bioconductor, see
## 'citation("Biobase")', and for packages 'citation("pkgname")'.##
## Attaching package: 'Biobase'## The following object is masked from 'package:MatrixGenerics':
##
## rowMedians## The following objects are masked from 'package:matrixStats':
##
## anyMissing, rowMedians## The following object is masked from 'package:ExperimentHub':
##
## cache## The following object is masked from 'package:AnnotationHub':
##
## cacheeh = ExperimentHub()## snapshotDate(): 2022-10-24dset <- query(eh , "GSE103322")
dset## ExperimentHub with 1 record
## # snapshotDate(): 2022-10-24
## # names(): EH5419
## # package(): GSE103322
## # $dataprovider: GEO
## # $species: Homo sapiens
## # $rdataclass: SingleCellExperiment
## # $rdatadateadded: 2021-03-04
## # $title: Single cell RNA-seq data for human head and neck squamous cell car...
## # $description: scRNA-Sequencing data and metadata for 5902 cells from 18 p...
## # $taxonomyid: 9606
## # $genome: hg19
## # $sourcetype: tar.gz
## # $sourceurl: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE103322
## # $sourcesize: NA
## # $tags: c("CancerData", "DNASeqData", "ExpressionData", "Genome",
## # "GEO", "Homo_sapiens_Data", "RNASeqData", "SingleCellData")
## # retrieve record with 'object[["EH5419"]]'One can then extract the data for this using
sce <- dset[[1]]## see ?GSE103322 and browseVignettes('GSE103322') for documentation## loading from cacheThe metadata is available from the SingleCellExpression object with
head(SummarizedExperiment::colData(sce))## DataFrame with 6 rows and 5 columns
## processed.by.Maxima.enzyme Lymph.node
## <character> <character>
## HN28_P15_D06_S330_comb 1 1
## HN28_P6_G05_S173_comb 1 0
## HN26_P14_D11_S239_comb 1 1
## HN26_P14_H05_S281_comb 1 1
## HN26_P25_H09_S189_comb 1 1
## HN26_P14_H06_S282_comb 1 1
## classified..as.cancer.cell
## <character>
## HN28_P15_D06_S330_comb 0
## HN28_P6_G05_S173_comb 0
## HN26_P14_D11_S239_comb 1
## HN26_P14_H05_S281_comb 0
## HN26_P25_H09_S189_comb 1
## HN26_P14_H06_S282_comb 1
## classified.as.non.cancer.cells non.cancer.cell.type
## <character> <character>
## HN28_P15_D06_S330_comb 1 Fibroblast
## HN28_P6_G05_S173_comb 1 Fibroblast
## HN26_P14_D11_S239_comb 0 0
## HN26_P14_H05_S281_comb 1 Fibroblast
## HN26_P25_H09_S189_comb 0 0
## HN26_P14_H06_S282_comb 0 0For example, to obtain the number of cells classified as non-tumor types
table(SummarizedExperiment::colData(sce)$non.cancer.cell.type)##
## -Fibroblast 0 B cell Dendritic Endothelial Fibroblast
## 18 2539 138 51 260 1422
## Macrophage Mast T cell myocyte
## 98 120 1237 19The data can be extracted from the SingleCellExpression object with
dset <- SummarizedExperiment::assays(sce)$TPM
dim(dset)## [1] 21341 5902dset[1:4, 1:3]## HN28_P15_D06_S330_comb HN28_P6_G05_S173_comb HN26_P14_D11_S239_comb
## 401546 0.0000 0.0000 0.42761
## 6205 6.0037 7.3006 7.28850
## 63916 0.0000 0.0000 0.00000
## 90993 0.0000 0.0000 0.00000sessionInfo()## 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] stats4 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] GSE103322_1.4.0 GEOquery_2.66.0
## [3] SingleCellExperiment_1.20.0 SummarizedExperiment_1.28.0
## [5] Biobase_2.58.0 GenomicRanges_1.50.0
## [7] GenomeInfoDb_1.34.0 IRanges_2.32.0
## [9] S4Vectors_0.36.0 MatrixGenerics_1.10.0
## [11] matrixStats_0.62.0 ExperimentHub_2.6.0
## [13] AnnotationHub_3.6.0 BiocFileCache_2.6.0
## [15] dbplyr_2.2.1 BiocGenerics_0.44.0
## [17] BiocStyle_2.26.0
##
## loaded via a namespace (and not attached):
## [1] httr_1.4.4 tidyr_1.2.1
## [3] sass_0.4.2 bit64_4.0.5
## [5] jsonlite_1.8.3 bslib_0.4.0
## [7] shiny_1.7.3 assertthat_0.2.1
## [9] interactiveDisplayBase_1.36.0 BiocManager_1.30.19
## [11] blob_1.2.3 GenomeInfoDbData_1.2.9
## [13] yaml_2.3.6 BiocVersion_3.16.0
## [15] pillar_1.8.1 RSQLite_2.2.18
## [17] lattice_0.20-45 limma_3.54.0
## [19] glue_1.6.2 digest_0.6.30
## [21] promises_1.2.0.1 XVector_0.38.0
## [23] htmltools_0.5.3 httpuv_1.6.6
## [25] Matrix_1.5-1 pkgconfig_2.0.3
## [27] bookdown_0.29 zlibbioc_1.44.0
## [29] purrr_0.3.5 xtable_1.8-4
## [31] later_1.3.0 tzdb_0.3.0
## [33] tibble_3.1.8 KEGGREST_1.38.0
## [35] generics_0.1.3 ellipsis_0.3.2
## [37] withr_2.5.0 cachem_1.0.6
## [39] cli_3.4.1 magrittr_2.0.3
## [41] crayon_1.5.2 mime_0.12
## [43] memoise_2.0.1 evaluate_0.17
## [45] fansi_1.0.3 xml2_1.3.3
## [47] data.table_1.14.4 tools_4.2.1
## [49] hms_1.1.2 lifecycle_1.0.3
## [51] stringr_1.4.1 DelayedArray_0.24.0
## [53] AnnotationDbi_1.60.0 Biostrings_2.66.0
## [55] compiler_4.2.1 jquerylib_0.1.4
## [57] rlang_1.0.6 grid_4.2.1
## [59] RCurl_1.98-1.9 rappdirs_0.3.3
## [61] bitops_1.0-7 rmarkdown_2.17
## [63] DBI_1.1.3 curl_4.3.3
## [65] R6_2.5.1 knitr_1.40
## [67] dplyr_1.0.10 fastmap_1.1.0
## [69] bit_4.0.4 utf8_1.2.2
## [71] filelock_1.0.2 readr_2.1.3
## [73] stringi_1.7.8 Rcpp_1.0.9
## [75] vctrs_0.5.0 png_0.1-7
## [77] tidyselect_1.2.0 xfun_0.34