Using the online server

Last updated: 2023-06-29

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Knit directory: SISG2023_Association_Mapping/

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First time login

We will be using an online server to run the module exercises.

To get setup:

Login to the server using the email name you used to register for the course (i.e. the part before the @). On your terminal, run: ssh <username>@<server_address>
Enter password : <default_password>
Change the password using passwd after you login

(Note: the server adress and default password were posted on the Slack channel)

Please make sure you are able to access the server prior to us starting the class on Monday July 25th. Let us know on Slack if you have any issues with the above steps.

Note for Windows users

If you run into issues accessing the server, we recommend Mobaxterm with X11 forwarding or Windows Subsystem for Linux as an SSH client to access the server.

Data sets

We have loaded data sets needed for the class exercises onto the server at /data/SISG2023M15/data/. We recommend to create a symbolic link in your home directory (i.e. default directory when you ssh into the server) to this folder for easier use during the module. To do that, run the following command in the terminal from your home directory:

ln -s /data/SISG2023M15/data/ data

You should now see the class datasets by just using ls data/ (note that you only have read access to these files).

Template R code

Template R code is available for some of the exercises to get your started; these are available in /data/SISG2023M15/code/. We recommend you copy this folder over to your home directory so you will be able to modify the files when you try out the exercises.

To do that, run the following command in the terminal from your home directory:

cp -r /data/SISG2023M15/code/ code/

You should now see the R files using ls code/ (note that you have read/write access to these files).

Using RStudio Server

We have started a RStudio server so you can start a Rstudio session from your web browser which will run on the online server. To connect your browser to the online server:

Enter the following command from your local terminal (i.e. you should be logged out of the server):

ssh -fNL 1235:localhost:8787 <username>@<server_address>

After you have entered your password, the ssh session should close.

Go to your web browser and enter localhost:1235. You should be re-directed to the RStudio login page where you can enter your username/password (same credentials you use when ssh-ing into the server).

Once logged in, the working directory will be your home directory so you can easily access the template R scripts in code/ as well as the class datasets in data/.

You can use pkill ssh to terminate the ssh session (so you won’t be able to access RStudio server from your browser anymore); until then it will remain accessible unless you restart your computer (or log out).

We strongly encourage you to use this when doing the class exercises so it will be easier to run scripts from RStudio, load datasets as well as visualize plots.

Notes

If you cannot setup Rstudio server on your browser, you can use X11 forwarding (if installed on your system) when ssh’ing into the server. This will enable for plots to be displayed on your screen during the ssh session.
To do that, run the following command when ssh’ing into the server:

ssh -XY <username>@<server_address>

Datasets and R template code are all available in the Github repository (under the data/ and code/ subdirectories, respectively).

sessionInfo()

R version 4.3.0 (2023-04-21)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Ventura 13.4

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRblas.0.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.11.0

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: Australia/Brisbane
tzcode source: internal

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

loaded via a namespace (and not attached):
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 [9] workflowr_1.7.0  glue_1.6.2       rprojroot_2.0.3  git2r_0.32.0    
[13] htmltools_0.5.5  httpuv_1.6.11    sass_0.4.6       fansi_1.0.4     
[17] rmarkdown_2.22   evaluate_0.21    jquerylib_0.1.4  tibble_3.2.1    
[21] fastmap_1.1.1    yaml_2.3.7       lifecycle_1.0.3  whisker_0.4.1   
[25] stringr_1.5.0    compiler_4.3.0   fs_1.6.2         Rcpp_1.0.10     
[29] pkgconfig_2.0.3  rstudioapi_0.14  later_1.3.1      digest_0.6.31   
[33] R6_2.5.1         utf8_1.2.3       pillar_1.9.0     magrittr_2.0.3  
[37] bslib_0.5.0      tools_4.3.0      cachem_1.0.8