Last updated: 2019-04-23

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Knit directory: Harvard-RosenbrockLab/

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Main Steps for Hook dataset

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.

SRA raw fastq files:

Using sratoolkit, downloaded raw fastq files from SRA

Expression table deposited to GEO:

For sanity check and quality control.

#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).

In the analysis, I excluded E15.5 cells as requested by CNSDR and done the rest of analysis with only P7 mice cells.

Gene & Isoform level expression

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 Gene-level: Code Isoform-level: 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  10.14.4

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_0.3.2     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_1.1.4    
  [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_1.0.1         
 [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_0.3.4        
 [67] reshape2_1.4.3      munsell_0.5.0       cellranger_1.1.0   
 [70] tools_3.5.0         cli_1.1.0           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_1.2.7            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_0.10     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_0.2.1    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_0.25.2        lubridate_1.7.4    
[127] base64enc_0.1-3