FazalLabPipelines

Download Raw Data

  1. Visit https://sra-explorer.info/.
  2. Search for PRJNA476786 (this is the accession number for the APEX-seq data).
  3. Select the files you would like to download (they should be highlighted in green with a blue checkbox once they are selected).
  4. Click the blue button at the top of the results that says “Add # to collection”.
  5. Click the blue button at the top of the page with the shopping cart icon that says “# saved datasets”.
  6. Select the link “Bash script for downloading FastQ files”.
  7. Press the “Copy” button.
  8. Open your SSH client file viewer (WinSCP or FileZilla) and sign in to the TACO cluster.
  9. Create a new file called download.sh, paste the copied content into the file, and save.
  10. Right click on the file, select “Properties”, check all of the Execute (or X) boxes under “Permissions” (this will give the computer permission to run the code), and click “OK”.
  11. Open your command prompt (Windows) or terminal (Mac) and sign in to the TACO cluster.
  12. Make sure you are in the same folder as the file you just created (you should see “download.sh” listed when you run the ls command).
  13. Run the command sbatch --time=UNLIMITED download.sh (it will submit a batch job for the computer to run the code and download your data files).
  14. Run the command squeue --me (it will show you the status of all the jobs you have submitted). The ouput will look something like this: 
     JOBID PARTITION     NAME     USER ST       TIME  NODES NODELIST(REASON)
######     mhgcp download   userID  R      00:42      1 mhgcp-m00

    Note: This example shows that 42 seconds have elapsed since the job started, but batch jobs don’t always start immediately. Sometimes your job has to wait in the queue for computational resources to become available. You can sign out of the cluster (with the exit command) while your job is running or in the queue.

  15. You will know that your download job is finished once you run squeue --me and see that your job is no longer listed. Make sure that all of your files are now on the cluster before returning to the main page to run the pipelines.