I don't know if it is the right platform to ask this question. But, I could not find any better place than this to ask this question.
I am trying to do some single-cell analysis for a group project. I have about 500 MB of data (count matrixes). I am not able to run any analysis on my PC where I have 8GB RAM. Then I tried to use rstudio.connect. I could not even upload all the files there. The session gets disconnected within a few minutes. Then, I bought a Rstudio Droplet from Digital Ocean. It is worse than rstudio cloud. I could use HPC from my university then I won't be able to run any Rmd files. I tried to use docker on HPC, but I don't have permission to create a docker image. So, my question is what other options are available for working with moderate size data on R Studio. I would not mind paying a few bucks?
You can render
.Rmdfiles on your university's HPC. I create the
.Rmdfile locally, and send it to the cluster. I have a script there called
render.Rthat looks like this:
I then submit a job calling that script (my uni uses
slurm, your job-submission protocol might be different):
I make sure to save my single cell objects at the end of the analysis, and you get a nice
.htmloutput with plots / whatever else you want which you can then send back to your local machine and view.
You could look at Cyverse it maintains VICE which have Rstudio image. You have to have free cyverse account, it provide you also with some disk space for your files in Discovery Environment. However I don't know more, I use it only for data sharing.