Chapter 32 Lawlor human pancreas (SMARTer)

32.1 Introduction

This performs an analysis of the Lawlor et al. (2017) dataset, consisting of human pancreas cells from various donors.

32.3 Quality control

Distribution of each QC metric across cells from each donor of the Lawlor pancreas dataset. Each point represents a cell and is colored according to whether that cell was discarded.

Figure 32.1: Distribution of each QC metric across cells from each donor of the Lawlor pancreas dataset. Each point represents a cell and is colored according to whether that cell was discarded.

Percentage of mitochondrial reads in each cell in the 416B dataset compared to the total count. Each point represents a cell and is colored according to whether that cell was discarded.

Figure 32.2: Percentage of mitochondrial reads in each cell in the 416B dataset compared to the total count. Each point represents a cell and is colored according to whether that cell was discarded.

##              low_lib_size            low_n_features high_subsets_Mito_percent 
##                         9                         5                        25 
##                   discard 
##                        34

32.4 Normalization

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   0.295   0.781   0.963   1.000   1.182   2.629
Relationship between the library size factors and the deconvolution size factors in the Lawlor pancreas dataset.

Figure 32.3: Relationship between the library size factors and the deconvolution size factors in the Lawlor pancreas dataset.

32.7 Clustering

##    
##     Acinar Alpha Beta Delta Ductal Gamma/PP None/Other Stellate
##   1      1     0    0    13      2       16          2        0
##   2      0     1   76     1      0        0          0        0
##   3      0   161    1     0      0        1          2        0
##   4      0     1    0     1      0        0          5       19
##   5      0     0  175     4      1        0          1        0
##   6     22     0    0     0      0        0          0        0
##   7      0    75    0     0      0        0          0        0
##   8      0     0    0     1     20        0          2        0
##    
##     ACCG268 ACCR015A ACEK420A ACEL337 ACHY057 ACIB065 ACIW009 ACJV399
##   1       8        2        2       4       4       4       9       1
##   2      14        3        2      33       3       2       4      17
##   3      36       23       14      13      14      14      21      30
##   4       7        1        0       1       0       4       9       4
##   5      34       10        4      39       7      23      24      40
##   6       0        2       13       0       0       0       5       2
##   7      32       12        0       5       6       7       4       9
##   8       1        1        2       1       2       1      12       3
Obligatory $t$-SNE plots of the Lawlor pancreas dataset. Each point represents a cell that is colored by cluster (left) or batch (right).

Figure 30.3: Obligatory \(t\)-SNE plots of the Lawlor pancreas dataset. Each point represents a cell that is colored by cluster (left) or batch (right).

Session Info

R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.1 LTS

Matrix products: default
BLAS:   /home/biocbuild/bbs-3.12-bioc/R/lib/libRblas.so
LAPACK: /home/biocbuild/bbs-3.12-bioc/R/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] BiocSingular_1.6.0          scran_1.18.0               
 [3] scater_1.18.0               ggplot2_3.3.2              
 [5] ensembldb_2.14.0            AnnotationFilter_1.14.0    
 [7] GenomicFeatures_1.42.0      AnnotationDbi_1.52.0       
 [9] AnnotationHub_2.22.0        BiocFileCache_1.14.0       
[11] dbplyr_1.4.4                scRNAseq_2.4.0             
[13] SingleCellExperiment_1.12.0 SummarizedExperiment_1.20.0
[15] Biobase_2.50.0              GenomicRanges_1.42.0       
[17] GenomeInfoDb_1.26.0         IRanges_2.24.0             
[19] S4Vectors_0.28.0            BiocGenerics_0.36.0        
[21] MatrixGenerics_1.2.0        matrixStats_0.57.0         
[23] BiocStyle_2.18.0            rebook_1.0.0               

loaded via a namespace (and not attached):
  [1] Rtsne_0.15                    ggbeeswarm_0.6.0             
  [3] colorspace_1.4-1              ellipsis_0.3.1               
  [5] scuttle_1.0.0                 bluster_1.0.0                
  [7] XVector_0.30.0                BiocNeighbors_1.8.0          
  [9] farver_2.0.3                  bit64_4.0.5                  
 [11] interactiveDisplayBase_1.28.0 xml2_1.3.2                   
 [13] codetools_0.2-16              sparseMatrixStats_1.2.0      
 [15] knitr_1.30                    Rsamtools_2.6.0              
 [17] graph_1.68.0                  shiny_1.5.0                  
 [19] BiocManager_1.30.10           compiler_4.0.3               
 [21] httr_1.4.2                    dqrng_0.2.1                  
 [23] assertthat_0.2.1              Matrix_1.2-18                
 [25] fastmap_1.0.1                 lazyeval_0.2.2               
 [27] limma_3.46.0                  later_1.1.0.1                
 [29] htmltools_0.5.0               prettyunits_1.1.1            
 [31] tools_4.0.3                   igraph_1.2.6                 
 [33] rsvd_1.0.3                    gtable_0.3.0                 
 [35] glue_1.4.2                    GenomeInfoDbData_1.2.4       
 [37] dplyr_1.0.2                   rappdirs_0.3.1               
 [39] Rcpp_1.0.5                    vctrs_0.3.4                  
 [41] Biostrings_2.58.0             ExperimentHub_1.16.0         
 [43] rtracklayer_1.50.0            DelayedMatrixStats_1.12.0    
 [45] xfun_0.19                     stringr_1.4.0                
 [47] ps_1.4.0                      beachmat_2.6.0               
 [49] mime_0.9                      lifecycle_0.2.0              
 [51] irlba_2.3.3                   statmod_1.4.35               
 [53] XML_3.99-0.5                  edgeR_3.32.0                 
 [55] zlibbioc_1.36.0               scales_1.1.1                 
 [57] hms_0.5.3                     promises_1.1.1               
 [59] ProtGenerics_1.22.0           yaml_2.2.1                   
 [61] curl_4.3                      gridExtra_2.3                
 [63] memoise_1.1.0                 biomaRt_2.46.0               
 [65] stringi_1.5.3                 RSQLite_2.2.1                
 [67] highr_0.8                     BiocVersion_3.12.0           
 [69] BiocParallel_1.24.0           rlang_0.4.8                  
 [71] pkgconfig_2.0.3               bitops_1.0-6                 
 [73] evaluate_0.14                 lattice_0.20-41              
 [75] purrr_0.3.4                   labeling_0.4.2               
 [77] GenomicAlignments_1.26.0      CodeDepends_0.6.5            
 [79] cowplot_1.1.0                 bit_4.0.4                    
 [81] processx_3.4.4                tidyselect_1.1.0             
 [83] magrittr_1.5                  bookdown_0.21                
 [85] R6_2.5.0                      generics_0.1.0               
 [87] DelayedArray_0.16.0           DBI_1.1.0                    
 [89] pillar_1.4.6                  withr_2.3.0                  
 [91] RCurl_1.98-1.2                tibble_3.0.4                 
 [93] crayon_1.3.4                  rmarkdown_2.5                
 [95] viridis_0.5.1                 progress_1.2.2               
 [97] locfit_1.5-9.4                grid_4.0.3                   
 [99] blob_1.2.1                    callr_3.5.1                  
[101] digest_0.6.27                 xtable_1.8-4                 
[103] httpuv_1.5.4                  openssl_1.4.3                
[105] munsell_0.5.0                 viridisLite_0.3.0            
[107] beeswarm_0.2.3                vipor_0.4.5                  
[109] askpass_1.1                  

Bibliography

Lawlor, N., J. George, M. Bolisetty, R. Kursawe, L. Sun, V. Sivakamasundari, I. Kycia, P. Robson, and M. L. Stitzel. 2017. “Single-cell transcriptomes identify human islet cell signatures and reveal cell-type-specific expression changes in type 2 diabetes.” Genome Res. 27 (2): 208–22.