Chapter 32 Chimeric embryo 10X dataset

32.1 Introduction

This performs an analysis of the Pijuan-Sala et al. (2019) dataset on mouse gastrulation. Here, we examine chimeric embryos at the E7.5 stage of development where td-Tomato-positive embryonic stem cells (ESCs) were injected into a wild-type blastocyst.

32.2 Analysis code

32.2.1 Data loading

## class: SingleCellExperiment 
## dim: 29453 20935 
## metadata(0):
## assays(1): counts
## rownames(29453): ENSMUSG00000051951 ENSMUSG00000089699 ...
##   ENSMUSG00000095742 tomato-td
## rowData names(2): ENSEMBL SYMBOL
## colnames(20935): cell_9769 cell_9770 ... cell_30702 cell_30703
## colData names(10): cell barcode ... closest.cell doub.density
## reducedDimNames(2): pca.corrected.E7.5 pca.corrected.E8.5
## spikeNames(0):
## altExpNames(0):

32.2.3 Quality control

Quality control on the cells has already been performed by the authors, so we will not repeat it here. We additionally remove cells that are labelled as stripped nuclei or doublets.

32.2.4 Normalization

We use the pre-computed size factors in sce.chimera.

32.2.5 Variance modelling

We retain all genes with any positive biological component, to preserve as much signal as possible across a very heterogeneous dataset.

32.2.8 Dimensionality reduction

We use an external algorithm to compute nearest neighbors for greater speed.

32.3 Results

32.3.2 Batch correction

##              5         6         7         8        9       10
## [1,] 0.000e+00 0.0204433 0.000e+00 0.0169567 0.000000 0.000000
## [2,] 0.000e+00 0.0007389 0.000e+00 0.0004409 0.000000 0.015474
## [3,] 3.090e-02 0.0000000 2.012e-02 0.0000000 0.000000 0.000000
## [4,] 9.024e-05 0.0000000 8.272e-05 0.0000000 0.018047 0.000000
## [5,] 4.321e-03 0.0072518 4.124e-03 0.0078280 0.003831 0.007786

32.3.3 Clustering

##        Sample
## Cluster   5   6   7   8   9  10
##      1  152  72  85  88 164 386
##      2   19   7  13  17  20  36
##      3  130  96 109  63 159 311
##      4   43  35  81  81  87 353
##      5   68  31 120 107  83 197
##      6  122  65  64  52  63 141
##      7  187 113 322 587 458 541
##      8   47  22  84  50  90 131
##      9  182  47 231 192 216 391
##      10  95  19  36  18  50  34
##      11   9   7  18  13  30  27
##      12 110  69  73  96 127 252
##      13   0   2   0  51   0   5
##      14  38  39  50  47 126 123
##      15  98  16 164 125 368 273
##      16 146  37 132 110 231 216
##      17 114  43  44  37  40 154
##      18  78  45 189 119 340 493
##      19  86  20  64  54 153  77
##      20 159  77 137 101 147 401
##      21   2   1   7   3  65 133
##      22  11  16  20   9  47  57
##      23   1   5   0  84   0  66
##      24 170  47 282 173 426 542
##      25 109  23 117  55 271 285
##      26 122  72 298 572 296 776

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] MouseGastrulationData_0.99.12 SingleCellExperiment_1.8.0   
 [7] SummarizedExperiment_1.16.0   DelayedArray_0.12.0          
 [9] BiocParallel_1.20.0           matrixStats_0.55.0           
[11] Biobase_2.46.0                GenomicRanges_1.38.0         
[13] GenomeInfoDb_1.22.0           IRanges_2.20.0               
[15] S4Vectors_0.24.0              BiocGenerics_0.32.0          
[17] Cairo_1.5-10                  BiocStyle_2.14.0             
[19] 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] uwot_0.1.4                    DBI_1.0.0                    
[11] lazyeval_0.2.2                colorspace_1.4-1             
[13] withr_2.1.2                   tidyselect_0.2.5             
[15] gridExtra_2.3                 bit_1.1-14                   
[17] curl_4.2                      compiler_3.6.1               
[19] BiocNeighbors_1.4.0           labeling_0.3                 
[21] bookdown_0.14                 scales_1.0.0                 
[23] rappdirs_0.3.1                stringr_1.4.0                
[25] digest_0.6.22                 rmarkdown_1.16               
[27] XVector_0.26.0                pkgconfig_2.0.3              
[29] htmltools_0.4.0               limma_3.42.0                 
[31] dbplyr_1.4.2                  fastmap_1.0.1                
[33] rlang_0.4.1                   RSQLite_2.1.2                
[35] shiny_1.4.0                   DelayedMatrixStats_1.8.0     
[37] dplyr_0.8.3                   RCurl_1.95-4.12              
[39] magrittr_1.5                  BiocSingular_1.2.0           
[41] GenomeInfoDbData_1.2.2        Matrix_1.2-17                
[43] Rcpp_1.0.2                    ggbeeswarm_0.6.0             
[45] munsell_0.5.0                 viridis_0.5.1                
[47] edgeR_3.28.0                  stringi_1.4.3                
[49] yaml_2.2.0                    zlibbioc_1.32.0              
[51] Rtsne_0.15                    BiocFileCache_1.10.0         
[53] AnnotationHub_2.18.0          grid_3.6.1                   
[55] blob_1.2.0                    dqrng_0.2.1                  
[57] promises_1.1.0                ExperimentHub_1.12.0         
[59] crayon_1.3.4                  lattice_0.20-38              
[61] cowplot_1.0.0                 locfit_1.5-9.1               
[63] zeallot_0.1.0                 knitr_1.25                   
[65] pillar_1.4.2                  igraph_1.2.4.1               
[67] codetools_0.2-16              glue_1.3.1                   
[69] BiocVersion_3.10.1            evaluate_0.14                
[71] RcppParallel_4.4.4            BiocManager_1.30.9           
[73] vctrs_0.2.0                   httpuv_1.5.2                 
[75] gtable_0.3.0                  purrr_0.3.3                  
[77] assertthat_0.2.1              xfun_0.10                    
[79] rsvd_1.0.2                    mime_0.7                     
[81] xtable_1.8-4                  later_1.0.0                  
[83] viridisLite_0.3.0             tibble_2.1.3                 
[85] AnnotationDbi_1.48.0          beeswarm_0.2.3               
[87] memoise_1.1.0                 statmod_1.4.32               
[89] interactiveDisplayBase_1.24.0

Bibliography

Pijuan-Sala, B., J. A. Griffiths, C. Guibentif, T. W. Hiscock, W. Jawaid, F. J. Calero-Nieto, C. Mulas, et al. 2019. “A Single-Cell Molecular Map of Mouse Gastrulation and Early Organogenesis.” Nature 566 (7745):490–95.