Last updated: 2019-03-15

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Main Steps for Hook dataset

Gene level expression

Citation: Hook, Paul W., Sarah A. McClymont, Gabrielle H. Cannon, William D. Law, A. Jennifer Morton, Loyal A. Goff, and Andrew S. McCallion. 2018. “Single-Cell RNA-Seq of Mouse Dopaminergic Neurons Informs Candidate Gene Selection for Sporadic Parkinson Disease.” American Journal of Human Genetics 102 (3): 427–46.

1. Obtain the data

473 single cell RNA-Seq samples from sorted mouse Th-eGFP+ dopaminergic neurons collected at two timepoints from three distinct brain regions.
#wget ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE108nnn/GSE108020/suppl/GSE108020_fpkm_table.txt.gz
#unzip GSE108020_fpkm_table.txt.gz

After downloading the data, unzip the file of FPKM matrix for further analysis.

2. Filtration

  • Filter out cells that are found to be low quality in the Hook et al. resulting in 396 cells for downstream analysis.

  • Filtered mitchondrial, ribosomal, and Gm-xxx genes as well as genes expressed less than 20 cells (same filtration applied in the paper).

Isoform level expression

2. Download raw fastq files from SRA

Using sratoolkit.

Genome alignment of raw reads for expression quantifiation

Using Rsem-STAR pipeline, I aligned the reads to reference transcriptome and quantified isoforms (count, TPM).

For the processing details, please follow

Code

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sessionInfo()
R version 3.5.0 (2018-04-23)
Platform: x86_64-apple-darwin17.5.0 (64-bit)
Running under: macOS  10.14.3

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libLAPACK.dylib

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

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

other attached packages:
 [1] forcats_0.4.0   stringr_1.4.0   purrr_0.3.1     readr_1.3.1    
 [5] tidyr_0.8.3     tibble_2.0.1    tidyverse_1.2.1 dplyr_0.8.0.1  
 [9] Seurat_2.3.4    Matrix_1.2-14   cowplot_0.9.4   here_0.1       
[13] DT_0.5          plotly_4.8.0    ggplot2_3.1.0  

loaded via a namespace (and not attached):
  [1] readxl_1.3.1        snow_0.4-3          backports_1.1.2    
  [4] Hmisc_4.2-0         workflowr_1.2.0     plyr_1.8.4         
  [7] igraph_1.2.4        lazyeval_0.2.1      splines_3.5.0      
 [10] digest_0.6.18       foreach_1.4.4       htmltools_0.3.6    
 [13] lars_1.2            gdata_2.18.0        magrittr_1.5       
 [16] checkmate_1.9.1     cluster_2.0.7-1     mixtools_1.1.0     
 [19] ROCR_1.0-7          modelr_0.1.4        R.utils_2.8.0      
 [22] colorspace_1.4-0    rvest_0.3.2         haven_2.1.0        
 [25] crayon_1.3.4        jsonlite_1.6        survival_2.42-6    
 [28] zoo_1.8-4           iterators_1.0.10    ape_5.2            
 [31] glue_1.3.1          gtable_0.2.0        kernlab_0.9-27     
 [34] prabclus_2.2-7      DEoptimR_1.0-8      scales_1.0.0       
 [37] mvtnorm_1.0-10      bibtex_0.4.2        Rcpp_1.0.0         
 [40] metap_1.1           dtw_1.20-1          viridisLite_0.3.0  
 [43] htmlTable_1.13.1    reticulate_1.11.1   foreign_0.8-70     
 [46] bit_1.1-14          proxy_0.4-23        mclust_5.4.3       
 [49] SDMTools_1.1-221    Formula_1.2-3       stats4_3.5.0       
 [52] tsne_0.1-3          htmlwidgets_1.3     httr_1.4.0         
 [55] gplots_3.0.1.1      RColorBrewer_1.1-2  fpc_2.1-11.1       
 [58] acepack_1.4.1       modeltools_0.2-22   ica_1.0-2          
 [61] pkgconfig_2.0.2     R.methodsS3_1.7.1   flexmix_2.3-15     
 [64] nnet_7.3-12         tidyselect_0.2.5    rlang_0.3.1        
 [67] reshape2_1.4.3      munsell_0.5.0       cellranger_1.1.0   
 [70] tools_3.5.0         cli_1.0.1           generics_0.0.2     
 [73] broom_0.5.1         ggridges_0.5.1      evaluate_0.10.1    
 [76] yaml_2.2.0          npsurv_0.4-0        knitr_1.20         
 [79] bit64_0.9-7         fs_1.2.6            fitdistrplus_1.0-14
 [82] robustbase_0.93-3   caTools_1.17.1.2    RANN_2.6.1         
 [85] pbapply_1.4-0       nlme_3.1-137        whisker_0.3-2      
 [88] R.oo_1.22.0         xml2_1.2.0          hdf5r_1.0.1        
 [91] compiler_3.5.0      rstudioapi_0.9.0    png_0.1-7          
 [94] lsei_1.2-0          stringi_1.2.4       lattice_0.20-35    
 [97] trimcluster_0.1-2.1 pillar_1.3.1        Rdpack_0.10-1      
[100] lmtest_0.9-36       data.table_1.12.0   bitops_1.0-6       
[103] irlba_2.3.3         gbRd_0.4-11         R6_2.4.0           
[106] latticeExtra_0.6-28 KernSmooth_2.23-15  gridExtra_2.3      
[109] codetools_0.2-15    MASS_7.3-50         gtools_3.8.1       
[112] assertthat_0.2.0    rprojroot_1.3-2     withr_2.1.2        
[115] diptest_0.75-7      parallel_3.5.0      doSNOW_1.0.16      
[118] hms_0.4.2           grid_3.5.0          rpart_4.1-13       
[121] class_7.3-14        rmarkdown_1.10      segmented_0.5-3.0  
[124] Rtsne_0.15          git2r_0.24.0        lubridate_1.7.4    
[127] base64enc_0.1-3