Chapter 27 Human pancreas dataset (Grun)

27.1 Introduction

This performs an analysis of the Grun et al. (2016) CEL-seq2 dataset, consisting of human pancreas cells from various donors.

27.2 Analysis code

27.3 Results

27.3.4 Data integration

##           D10      D17       D2      D3      D7
## [1,] 0.063990 0.046806 0.000000 0.00000 0.00000
## [2,] 0.004310 0.012395 0.037910 0.00000 0.00000
## [3,] 0.006735 0.008700 0.006976 0.06123 0.00000
## [4,] 0.005845 0.009381 0.007911 0.01107 0.05828

27.3.5 Clustering

##        Donor
## Cluster D10 D17  D2  D3  D7
##      1   34  73  32 122  28
##      2   17  39   9  17  16
##      3   10  51   0   3  11
##      4   11 112   0  10  55
##      5   12  68  27  13  77
##      6   14  36   3  12  67
##      7   32   5   4  13   3
##      8    6  14   0   4  10
##      9   16  34  15  25  45
##      10   4  14   0   3   1
##      11   6  17   0   7  33

Session Info

R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 14.04.5 LTS

Matrix products: default
BLAS:   /home/ramezqui/Rbuild/danbuild/R-3.6.1/lib/libRblas.so
LAPACK: /home/ramezqui/Rbuild/danbuild/R-3.6.1/lib/libRlapack.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        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] parallel  stats4    stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] batchelor_1.2.1             scran_1.14.0               
 [3] scater_1.14.0               ggplot2_3.2.1              
 [5] org.Hs.eg.db_3.10.0         AnnotationDbi_1.48.0       
 [7] scRNAseq_1.99.8             SingleCellExperiment_1.8.0 
 [9] SummarizedExperiment_1.16.0 DelayedArray_0.12.0        
[11] BiocParallel_1.20.0         matrixStats_0.55.0         
[13] Biobase_2.46.0              GenomicRanges_1.38.0       
[15] GenomeInfoDb_1.22.0         IRanges_2.20.0             
[17] S4Vectors_0.24.0            BiocGenerics_0.32.0        
[19] Cairo_1.5-10                BiocStyle_2.14.0           
[21] OSCAUtils_0.0.1            

loaded via a namespace (and not attached):
 [1] bitops_1.0-6                  bit64_0.9-7                  
 [3] httr_1.4.1                    tools_3.6.1                  
 [5] backports_1.1.5               R6_2.4.0                     
 [7] irlba_2.3.3                   vipor_0.4.5                  
 [9] DBI_1.0.0                     lazyeval_0.2.2               
[11] colorspace_1.4-1              withr_2.1.2                  
[13] tidyselect_0.2.5              gridExtra_2.3                
[15] bit_1.1-14                    curl_4.2                     
[17] compiler_3.6.1                BiocNeighbors_1.4.0          
[19] labeling_0.3                  bookdown_0.14                
[21] scales_1.0.0                  rappdirs_0.3.1               
[23] stringr_1.4.0                 digest_0.6.22                
[25] rmarkdown_1.16                XVector_0.26.0               
[27] pkgconfig_2.0.3               htmltools_0.4.0              
[29] limma_3.42.0                  dbplyr_1.4.2                 
[31] fastmap_1.0.1                 rlang_0.4.1                  
[33] RSQLite_2.1.2                 shiny_1.4.0                  
[35] DelayedMatrixStats_1.8.0      dplyr_0.8.3                  
[37] RCurl_1.95-4.12               magrittr_1.5                 
[39] BiocSingular_1.2.0            GenomeInfoDbData_1.2.2       
[41] Matrix_1.2-17                 Rcpp_1.0.2                   
[43] ggbeeswarm_0.6.0              munsell_0.5.0                
[45] viridis_0.5.1                 edgeR_3.28.0                 
[47] stringi_1.4.3                 yaml_2.2.0                   
[49] zlibbioc_1.32.0               Rtsne_0.15                   
[51] BiocFileCache_1.10.0          AnnotationHub_2.18.0         
[53] grid_3.6.1                    blob_1.2.0                   
[55] dqrng_0.2.1                   promises_1.1.0               
[57] ExperimentHub_1.12.0          crayon_1.3.4                 
[59] lattice_0.20-38               cowplot_1.0.0                
[61] locfit_1.5-9.1                zeallot_0.1.0                
[63] knitr_1.25                    pillar_1.4.2                 
[65] igraph_1.2.4.1                codetools_0.2-16             
[67] glue_1.3.1                    BiocVersion_3.10.1           
[69] evaluate_0.14                 BiocManager_1.30.9           
[71] vctrs_0.2.0                   httpuv_1.5.2                 
[73] gtable_0.3.0                  purrr_0.3.3                  
[75] assertthat_0.2.1              xfun_0.10                    
[77] rsvd_1.0.2                    mime_0.7                     
[79] xtable_1.8-4                  later_1.0.0                  
[81] viridisLite_0.3.0             tibble_2.1.3                 
[83] beeswarm_0.2.3                memoise_1.1.0                
[85] statmod_1.4.32                interactiveDisplayBase_1.24.0

Bibliography

Grun, D., M. J. Muraro, J. C. Boisset, K. Wiebrands, A. Lyubimova, G. Dharmadhikari, M. van den Born, et al. 2016. “De Novo Prediction of Stem Cell Identity using Single-Cell Transcriptome Data.” Cell Stem Cell 19 (2):266–77.