Contents

1 Accessing human HNSC scRNASeq data using Bioconductor’s ExperimentHub

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
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## Attaching package: 'BiocGenerics'
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##     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: dbplyr
library(SingleCellExperiment)
## Loading required package: SummarizedExperiment
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## Attaching package: 'S4Vectors'
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eh = ExperimentHub()
## snapshotDate(): 2021-11-15
dset <- query(eh , "GSE103322")
dset
## ExperimentHub with 1 record
## # snapshotDate(): 2021-11-15
## # 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 cache

1.1 Exploring the metadata

The 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                    0

For 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          19

1.2 Extracting the data

The data can be extracted from the SingleCellExpression object with

dset <- SummarizedExperiment::assays(sce)$TPM
dim(dset)
## [1] 21341  5902
dset[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                0.00000

2 sessionInfo()

sessionInfo()
## R Under development (unstable) (2021-11-16 r81199)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.3 LTS
## 
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.15-data-experiment/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.15-data-experiment/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_1.1.0             GEOquery_2.63.1            
##  [3] SingleCellExperiment_1.17.2 SummarizedExperiment_1.25.2
##  [5] Biobase_2.55.0              GenomicRanges_1.47.5       
##  [7] GenomeInfoDb_1.31.1         IRanges_2.29.1             
##  [9] S4Vectors_0.33.4            MatrixGenerics_1.7.0       
## [11] matrixStats_0.61.0          ExperimentHub_2.3.4        
## [13] AnnotationHub_3.3.6         BiocFileCache_2.3.0        
## [15] dbplyr_2.1.1                BiocGenerics_0.41.2        
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## [31] later_1.3.0                   tzdb_0.2.0                   
## [33] tibble_3.1.6                  KEGGREST_1.35.0              
## [35] generics_0.1.1                ellipsis_0.3.2               
## [37] cachem_1.0.6                  withr_2.4.2                  
## [39] magrittr_2.0.1                crayon_1.4.2                 
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## [43] evaluate_0.14                 fansi_0.5.0                  
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## [51] DelayedArray_0.21.2           AnnotationDbi_1.57.1         
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