Chapter 28 Human pancreas dataset (Muraro)

28.1 Introduction

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

28.2 Analysis code

28.3 Results

28.3.4 Data integration

##           D28      D29      D30     D31
## [1,] 0.061236 0.024182 0.000000 0.00000
## [2,] 0.002639 0.003242 0.062255 0.00000
## [3,] 0.003409 0.002588 0.002575 0.08063

28.3.5 Clustering

##        CellType
## Cluster acinar alpha beta delta duct endothelial epsilon mesenchymal  pp
##      1     217     1    3     0    8           0       0           0   2
##      2       0     5    5     0  212           0       0           1   0
##      3       0     0    0   186    0           0       0           0   0
##      4       0    17  385     3    0           0       0           0   0
##      5       0   778    2     1    0           0       3           0   0
##      6       1     0    2     0    6           1       0          79   0
##      7       0     0    1     0   13           0       0           0   0
##      8       0     1   42     1    3           0       0           0   0
##      9       0     1    6     0    0           0       0           0  97
##      10      0     0    0     0    0          19       0           0   0
##        CellType
## Cluster unclear
##      1        0
##      2        4
##      3        0
##      4        0
##      5        0
##      6        0
##      7        0
##      8        0
##      9        0
##      10       0
##        Donor
## Cluster D28 D29 D30 D31
##      1  108   6  57 113
##      2   57  21  79  97
##      3   13  75  65  43
##      4   28 148 129 121
##      5   88 263 281 222
##      6   22   7  54  26
##      7    7   6   6   6
##      8    1   6   7  38
##      9   11  70   6  38
##      10   5   2   5   9

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] ensembldb_2.10.0            AnnotationFilter_1.10.0    
 [7] GenomicFeatures_1.38.0      AnnotationDbi_1.48.0       
 [9] AnnotationHub_2.18.0        BiocFileCache_1.10.0       
[11] dbplyr_1.4.2                scRNAseq_1.99.8            
[13] SingleCellExperiment_1.8.0  SummarizedExperiment_1.16.0
[15] DelayedArray_0.12.0         BiocParallel_1.20.0        
[17] matrixStats_0.55.0          Biobase_2.46.0             
[19] GenomicRanges_1.38.0        GenomeInfoDb_1.22.0        
[21] IRanges_2.20.0              S4Vectors_0.24.0           
[23] BiocGenerics_0.32.0         Cairo_1.5-10               
[25] BiocStyle_2.14.0            OSCAUtils_0.0.1            

loaded via a namespace (and not attached):
 [1] Rtsne_0.15                    ggbeeswarm_0.6.0             
 [3] colorspace_1.4-1              XVector_0.26.0               
 [5] BiocNeighbors_1.4.0           bit64_0.9-7                  
 [7] interactiveDisplayBase_1.24.0 codetools_0.2-16             
 [9] knitr_1.25                    zeallot_0.1.0                
[11] Rsamtools_2.2.0               shiny_1.4.0                  
[13] BiocManager_1.30.9            compiler_3.6.1               
[15] httr_1.4.1                    dqrng_0.2.1                  
[17] backports_1.1.5               assertthat_0.2.1             
[19] Matrix_1.2-17                 fastmap_1.0.1                
[21] lazyeval_0.2.2                limma_3.42.0                 
[23] later_1.0.0                   BiocSingular_1.2.0           
[25] htmltools_0.4.0               prettyunits_1.0.2            
[27] tools_3.6.1                   rsvd_1.0.2                   
[29] igraph_1.2.4.1                gtable_0.3.0                 
[31] glue_1.3.1                    GenomeInfoDbData_1.2.2       
[33] dplyr_0.8.3                   rappdirs_0.3.1               
[35] Rcpp_1.0.2                    vctrs_0.2.0                  
[37] Biostrings_2.54.0             ExperimentHub_1.12.0         
[39] rtracklayer_1.46.0            DelayedMatrixStats_1.8.0     
[41] xfun_0.10                     stringr_1.4.0                
[43] mime_0.7                      irlba_2.3.3                  
[45] statmod_1.4.32                XML_3.98-1.20                
[47] edgeR_3.28.0                  zlibbioc_1.32.0              
[49] scales_1.0.0                  hms_0.5.2                    
[51] promises_1.1.0                ProtGenerics_1.18.0          
[53] yaml_2.2.0                    curl_4.2                     
[55] memoise_1.1.0                 gridExtra_2.3                
[57] biomaRt_2.42.0                stringi_1.4.3                
[59] RSQLite_2.1.2                 BiocVersion_3.10.1           
[61] rlang_0.4.1                   pkgconfig_2.0.3              
[63] bitops_1.0-6                  evaluate_0.14                
[65] lattice_0.20-38               purrr_0.3.3                  
[67] labeling_0.3                  GenomicAlignments_1.22.0     
[69] cowplot_1.0.0                 bit_1.1-14                   
[71] tidyselect_0.2.5              magrittr_1.5                 
[73] bookdown_0.14                 R6_2.4.0                     
[75] DBI_1.0.0                     pillar_1.4.2                 
[77] withr_2.1.2                   RCurl_1.95-4.12              
[79] tibble_2.1.3                  crayon_1.3.4                 
[81] rmarkdown_1.16                viridis_0.5.1                
[83] progress_1.2.2                locfit_1.5-9.1               
[85] grid_3.6.1                    blob_1.2.0                   
[87] digest_0.6.22                 xtable_1.8-4                 
[89] httpuv_1.5.2                  openssl_1.4.1                
[91] munsell_0.5.0                 beeswarm_0.2.3               
[93] viridisLite_0.3.0             vipor_0.4.5                  
[95] askpass_1.1                  

Bibliography

Muraro, M. J., G. Dharmadhikari, D. Grun, N. Groen, T. Dielen, E. Jansen, L. van Gurp, et al. 2016. “A Single-Cell Transcriptome Atlas of the Human Pancreas.” Cell Syst 3 (4):385–94.