Chapter 26 PBMC 4k 10X dataset (filtered)

26.1 Introduction

This performs an analysis of the public PBMC 4k dataset generated by 10X Genomics (Zheng et al. 2017), starting from the filtered count matrix.

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/
LAPACK: /home/ramezqui/Rbuild/danbuild/R-3.6.1/lib/

 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8       
 [4] LC_COLLATE=C               LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                  LC_ADDRESS=C              

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] scran_1.14.3                scater_1.14.3               ggplot2_3.2.1              
 [4] TENxPBMCData_1.4.0          HDF5Array_1.14.0            rhdf5_2.30.0               
 [7] SingleCellExperiment_1.8.0  SummarizedExperiment_1.16.0 DelayedArray_0.12.0        
[10] BiocParallel_1.20.0         matrixStats_0.55.0          Biobase_2.46.0             
[13] GenomicRanges_1.38.0        GenomeInfoDb_1.22.0         IRanges_2.20.0             
[16] S4Vectors_0.24.0            BiocGenerics_0.32.0         Cairo_1.5-10               
[19] BiocStyle_2.14.0            OSCAUtils_0.0.1            

loaded via a namespace (and not attached):
 [1] bitops_1.0-6                  bit64_0.9-7                   RcppAnnoy_0.0.14             
 [4] httr_1.4.1                    tools_3.6.1                   backports_1.1.5              
 [7] R6_2.4.1                      irlba_2.3.3                   vipor_0.4.5                  
[10] uwot_0.1.4                    DBI_1.0.0                     lazyeval_0.2.2               
[13] colorspace_1.4-1              withr_2.1.2                   gridExtra_2.3                
[16] tidyselect_0.2.5              bit_1.1-14                    curl_4.2                     
[19] compiler_3.6.1                BiocNeighbors_1.4.0           labeling_0.3                 
[22] bookdown_0.15                 scales_1.0.0                  rappdirs_0.3.1               
[25] stringr_1.4.0                 digest_0.6.22                 rmarkdown_1.17               
[28] XVector_0.26.0                pkgconfig_2.0.3               htmltools_0.4.0              
[31] limma_3.42.0                  dbplyr_1.4.2                  fastmap_1.0.1                
[34] rlang_0.4.1                   RSQLite_2.1.2                 shiny_1.4.0                  
[37] DelayedMatrixStats_1.8.0      dplyr_0.8.3                   RCurl_1.95-4.12              
[40] magrittr_1.5                  BiocSingular_1.2.0            GenomeInfoDbData_1.2.2       
[43] Matrix_1.2-17                 Rcpp_1.0.3                    ggbeeswarm_0.6.0             
[46] munsell_0.5.0                 Rhdf5lib_1.8.0                viridis_0.5.1                
[49] edgeR_3.28.0                  stringi_1.4.3                 yaml_2.2.0                   
[52] zlibbioc_1.32.0               Rtsne_0.15                    BiocFileCache_1.10.2         
[55] AnnotationHub_2.18.0          grid_3.6.1                    blob_1.2.0                   
[58] dqrng_0.2.1                   promises_1.1.0                ExperimentHub_1.12.0         
[61] crayon_1.3.4                  lattice_0.20-38               cowplot_1.0.0                
[64] beachmat_2.2.0                locfit_1.5-9.1                zeallot_0.1.0                
[67] knitr_1.26                    pillar_1.4.2                  igraph_1.2.4.1               
[70] codetools_0.2-16              glue_1.3.1                    BiocVersion_3.10.1           
[73] evaluate_0.14                 RcppParallel_4.4.4            BiocManager_1.30.9           
[76] vctrs_0.2.0                   httpuv_1.5.2                  gtable_0.3.0                 
[79] purrr_0.3.3                   assertthat_0.2.1              xfun_0.11                    
[82] rsvd_1.0.2                    mime_0.7                      xtable_1.8-4                 
[85] RSpectra_0.15-0               later_1.0.0                   viridisLite_0.3.0            
[88] tibble_2.1.3                  beeswarm_0.2.3                AnnotationDbi_1.48.0         
[91] memoise_1.1.0                 statmod_1.4.32                interactiveDisplayBase_1.24.0


Zheng, G. X., J. M. Terry, P. Belgrader, P. Ryvkin, Z. W. Bent, R. Wilson, S. B. Ziraldo, et al. 2017. “Massively parallel digital transcriptional profiling of single cells.” Nat Commun 8 (January):14049.