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Introduction

You can use the docker image of case study to repeat all the analysis and results in tidymass manuscript.

Download and install docker

Please refer to the official website to download and install docker. And then run docker.

Pull the tidymass-case-study image

Open you terminal and then type code below:

docker pull jaspershen/tidymass-case-study:latest

Run tidymass-case-study docker image

In you terminal, run the code below:

docker run -e PASSWORD=tidymass -p 8787:8787 jaspershen/tidymass-case-study:latest

Then open the browser and visit http://localhost:8787 to power on RStudio server. The user name is rstudio and the password is tidymass.

Run case study code

Open the tidymass_case_study.Rmd, and then click Knit.

Session information

sessionInfo()
#> R version 4.1.2 (2021-11-01)
#> Platform: x86_64-apple-darwin17.0 (64-bit)
#> Running under: macOS Big Sur 10.16
#> 
#> Matrix products: default
#> BLAS:   /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRblas.0.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.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     
#> 
#> loaded via a namespace (and not attached):
#>  [1] rstudioapi_0.13   knitr_1.37        magrittr_2.0.2    R6_2.5.1         
#>  [5] ragg_1.2.1        rlang_1.0.1       fastmap_1.1.0     stringr_1.4.0    
#>  [9] tools_4.1.2       xfun_0.29         cli_3.2.0         jquerylib_0.1.4  
#> [13] htmltools_0.5.2   systemfonts_1.0.3 yaml_2.3.4        digest_0.6.29    
#> [17] rprojroot_2.0.2   pkgdown_2.0.2     crayon_1.5.0      textshaping_0.3.6
#> [21] purrr_0.3.4       sass_0.4.0        fs_1.5.2          memoise_2.0.1    
#> [25] cachem_1.0.6      evaluate_0.15     rmarkdown_2.11    stringi_1.7.6    
#> [29] compiler_4.1.2    bslib_0.3.1       desc_1.4.0        jsonlite_1.7.3