qc_assess

Author

Affiliation

Griffen Wakelin

Dalhousie University

Barcode ranks

(a) Uninjured barcodes.

(b) 7 days post-cardiotoxin (injured) barcodes.

Figure 1: Barcode rank plots.

:::

Ambient RNA Contamination

Figure 2: Estimate of fraction of total reads due to ambient RNA contamination. Left panel = uninjured dataset, center panel = 7 days post-cardiotoxin (injured) dataset, right panel = 10X Genomics PBMC4k dataset.

Percent Mitochondrial Reads

Total

(a) Uninjured dataset.

(b) 7 days post-cardiotoxin (injured) dataset.

Figure 3: Percent mitochondrial reads (total).

By cluster

(a) Uninjured dataset.

(b) 7 days post-cardiotoxin (injured) dataset.

Figure 4: Percent mitochondrial reads by cluster, vs. total UMIs detected.

Myonucleus and tdTomato-negative cell contamination

Figure 5: Expression of tdTomato (tdT) (we sorted for tdT+ cells, so all cells should be tdT+) and myosin heavy chain 4 (marker of myonuclei, which should not be present in a normal muscle digestion prep–no cells should be Myh4+). Note the large amount of tdT- cells and high amount of Myh4+ cells.

sessionInfo()

R version 4.4.1 (2024-06-14)
Platform: aarch64-apple-darwin20
Running under: macOS 15.1

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRblas.0.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.0

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: America/Halifax
tzcode source: internal

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

other attached packages:
 [1] BiocParallel_1.40.0         ggridges_0.5.6             
 [3] ggpubr_0.6.0                lubridate_1.9.3            
 [5] forcats_1.0.0               stringr_1.5.1              
 [7] dplyr_1.1.4                 purrr_1.0.2                
 [9] readr_2.1.5                 tidyr_1.3.1                
[11] tibble_3.2.1                tidyverse_2.0.0            
[13] DropletUtils_1.24.0         scran_1.32.0               
[15] scater_1.34.0               ggplot2_3.5.1              
[17] scuttle_1.16.0              SingleCellExperiment_1.28.1
[19] SummarizedExperiment_1.36.0 Biobase_2.66.0             
[21] GenomicRanges_1.58.0        GenomeInfoDb_1.42.0        
[23] IRanges_2.40.0              S4Vectors_0.44.0           
[25] BiocGenerics_0.52.0         MatrixGenerics_1.18.0      
[27] matrixStats_1.4.1          

loaded via a namespace (and not attached):
 [1] gridExtra_2.3             rlang_1.1.4              
 [3] magrittr_2.0.3            compiler_4.4.1           
 [5] DelayedMatrixStats_1.26.0 vctrs_0.6.5              
 [7] pkgconfig_2.0.3           crayon_1.5.3             
 [9] fastmap_1.2.0             backports_1.5.0          
[11] XVector_0.46.0            utf8_1.2.4               
[13] rmarkdown_2.27            tzdb_0.4.0               
[15] UCSC.utils_1.2.0          ggbeeswarm_0.7.2         
[17] xfun_0.45                 bluster_1.14.0           
[19] zlibbioc_1.52.0           beachmat_2.22.0          
[21] jsonlite_1.8.9            rhdf5filters_1.18.0      
[23] DelayedArray_0.32.0       Rhdf5lib_1.28.0          
[25] broom_1.0.6               irlba_2.3.5.1            
[27] parallel_4.4.1            cluster_2.1.6            
[29] R6_2.5.1                  stringi_1.8.4            
[31] limma_3.62.1              car_3.1-2                
[33] Rcpp_1.0.13-1             knitr_1.47               
[35] R.utils_2.12.3            timechange_0.3.0         
[37] Matrix_1.7-1              igraph_2.0.3             
[39] tidyselect_1.2.1          rstudioapi_0.16.0        
[41] abind_1.4-8               yaml_2.3.8               
[43] viridis_0.6.5             codetools_0.2-20         
[45] lattice_0.22-6            withr_3.0.2              
[47] evaluate_0.24.0           pillar_1.9.0             
[49] carData_3.0-5             generics_0.1.3           
[51] hms_1.1.3                 sparseMatrixStats_1.16.0 
[53] munsell_0.5.1             scales_1.3.0             
[55] glue_1.8.0                metapod_1.12.0           
[57] tools_4.4.1               BiocNeighbors_2.0.0      
[59] ScaledMatrix_1.14.0       ggsignif_0.6.4           
[61] locfit_1.5-9.9            rhdf5_2.50.0             
[63] grid_4.4.1                edgeR_4.2.0              
[65] colorspace_2.1-1          GenomeInfoDbData_1.2.13  
[67] beeswarm_0.4.0            BiocSingular_1.22.0      
[69] HDF5Array_1.34.0          vipor_0.4.7              
[71] cli_3.6.3                 rsvd_1.0.5               
[73] fansi_1.0.6               S4Arrays_1.6.0           
[75] viridisLite_0.4.2         gtable_0.3.6             
[77] rstatix_0.7.2             R.methodsS3_1.8.2        
[79] digest_0.6.35             SparseArray_1.6.0        
[81] ggrepel_0.9.6             dqrng_0.4.1              
[83] htmlwidgets_1.6.4         htmltools_0.5.8.1        
[85] R.oo_1.26.0               lifecycle_1.0.4          
[87] httr_1.4.7                statmod_1.5.0            

Figure 1 (a): Uninjured barcodes. Figure 1 (b): 7 days post-cardiotoxin (injured) barcodes. Figure 2: Estimate of fraction of total reads due to ambient RNA contamination. Left panel = uninjured dataset, center panel = 7 days post-cardiotoxin (injured) dataset, right panel = 10X Genomics PBMC4k dataset. Figure 3 (a): Uninjured dataset. Figure 3 (b): 7 days post-cardiotoxin (injured) dataset. Figure 4 (a): Uninjured dataset. Figure 4 (b): 7 days post-cardiotoxin (injured) dataset. Figure 5: Expression of tdTomato (tdT) (we sorted for tdT+ cells, so all cells should be tdT+) and myosin heavy chain 4 (marker of myonuclei, which should not be present in a normal muscle digestion prep–no cells should be Myh4+). Note the large amount of tdT- cells and high amount of Myh4+ cells.