Skip to content

Updated test_muscle_quickbyte.md #255

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
xc1-hub wants to merge 1 commit into
base: test-muscle-quickbyte
Choose a base branch
from
Open

Updated test_muscle_quickbyte.md #255

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
54 changes: 44 additions & 10 deletions test_muscle_quickbyte.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2,11 +2,30 @@

## Software Description

MUSCLE performs multiple sequence alignment: it takes related DNA, RNA, or protein sequences and lines them up so similarities and differences can be compared. Researchers commonly use alignments to inspect conserved regions, prepare phylogenetic analyses, or check whether related sequences contain insertions, deletions, or substitutions. This QuickByte uses a tiny synthetic FASTA file so the full workflow fits in a short debug-partition job.
MUSCLE (Multiple Sequence Comparison by Log-Expectation) is a software program used in bioinformatics to perform multiple sequence alignments of DNA, RNA, and protein sequences. It lines up sequences so that similarities and differences can be compared. Researchers commonly use alignments to inspect conserved regions, prepare phylogenetic analyses, or check whether related sequences contain insertions, deletions, or substitutions. This QuickByte uses a tiny synthetic FASTA file so the full workflow fits in a short debug-partition job.

Below is a guide on how to submit this example job to Slurm.

## Example Slurm Script

Save the following as `slurm-test.sh` in the example directory and submit it with `sbatch slurm-test.sh`.
To run this example, you must be logged into your account on a CARC machine. Open a local terminal and start an ssh session on the cluster of your choice:

'ssh username@cluster.alliance.unm.edu'

Replace "username" and "cluster" with your own username and cluster of choice.

Once logged in, it's best to run the script from an example directory so that the output files do not populate your home directory. From your home directory, create a new subdirectory:

'mkdir example'

To see the contents of your current location, type 'ls'. You should now see a subdirectory called "example". Navigate into that directory:

'cd example'

In the example directory, create a text file with the script below using the text editor of your choice. Nano is a user-friendly option. Type 'nano' to open the program. Copy and paste the script below onto the page.
Exit the program ('ctrl + X'), type 'Y' to save, and name your file 'slurm-test.sh'. After hitting enter, you should be taken back to the terminal. Submit the job to Slurm:

`sbatch slurm-test.sh`

```bash
#!/bin/bash -l
Expand Down Expand Up @@ -56,18 +75,33 @@ test "$(grep -c '^>' aligned.fa)" -eq 3
grep -q "seq2" aligned.fa
```

The important Slurm resource lines are the `#SBATCH` directives near the top of the script. They request the debug partition, a small amount of time, and the CPU, memory, node, or GPU resources needed by this smoke test. The `module load` commands prepare the software environment, and `srun` is used when the application should be launched through Slurm across allocated tasks.
The important Slurm resource lines are the `#SBATCH` directives near the top of the script. They name the file, determine where to save the output and any error messages, and they request the debug partition, a runtime of five minutes, one compute node, one task, one CPU per task, and reserve 1 gigabyte of memory for the job. The `module --ignore-cache load muscle/3.8.1551-nuba' command prepares the software environment, and `muscle -in sequences.fa -out aligned.fa` launches the MUSCLE program while specifying which file to use as input and where to save the output.

Once you've submitted the job to Slurm, you can check the status of your job:

'squeue --me'

If you see no information under the headings, that means your job has finished and you can now examine the output.

## Example output

After the job finishes, Slurm should report a completed job with exit code `0:0`. The job directory under `outputs/` should contain `sequences.fa` and `aligned.fa`; the alignment file should include all three sequence headers.
There should be a new folder within your example directory called "outputs". Navigate into it with 'cd outputs' and view the contents with 'ls'. You should see a subdirectory called "test-muscle-jobID" ("jobID" will be the number assigned to your job). Navigate into it with 'test-muscle-jobID'. It should contain the FASTA files `sequences.fa` and `aligned.fa`; the alignment file should include all three sequence headers.

To view the efficiency of your job and to confirm a successful completion with an exit code of '0', use the command 'seff jobID':

```text
Slurm state: COMPLETED
Exit code: 0:0
Allocated nodes: 1
Allocated CPUs: 1
Expected files: sequences.fa, aligned.fa
>seff jobID
Job ID: ######
Cluster: easley
User/Group: username/groupname
State: COMPLETED (exit code 0)
Cores: 1
CPU Utilized: 00:00:01
CPU Efficiency: 33.33% of 00:00:03 core-walltime
Job Wall-clock time: 00:00:03
Memory Utilized: 68.13 MB
Memory Efficiency: 6.65% of 1.00 GB (1.00 GB/node)
[user@easley test-muscle-jobID]$
```

For a successful run, the Slurm state should be `COMPLETED`, the exit code should be `0:0`, and the checks in the script should pass.
For a successful run, the Slurm state should be `COMPLETED`and the exit code should be `0`.