As an alternative, here a bash solution, based on your initial attempt:

for f in $(ls your-input-dir/vbro*.fasta); do
  muscle -in $f -out ${f%.fasta}.afa -maxiters 1 -diags1 -sv;
done

If you want to run things in parallel, then you could simply echo the muscle commands, redirect into a file and then use xargs to use the amount of processors you like. For example if your Muscle commands are listed in cmd.txt and you want to run four jobs in parallel:

cat cmd.txt | xargs -I cmd --max-procs=4 bash -c cmd &

Andreas

Maybe this:

#!/usr/bin/env python

import glob, os

muscle_options = " -maxiters 1 -diags1 -sv "

for fasta_file in glob.glob("vbro*.fasta"):
    afa_file = fasta_file[:-5] + "afa"
    command = "muscle -in %s -out %s %s" % (fasta_file, afa_file, muscle_options)
    print "executing: " + command
    os.system(command)

Muscle is quite fast. If you need to split your muscle jobs you may tweak "vbro.fasta" and submit 10 jobs ("vbro0.fasta", "vbro*1.fasta" etc.) as a quick and dirty solution.

Hi, I have 366 RNAseq samples, reads for each sample are located in individual folders with the following name structure:SAME-DIFFERENT. I would like to write a loop to align all samples using the STAR aligner. Any help is deeply appreciated.