trims fastas of several sequences/genes using a single known sequence/gene

trimSequences.py

import subprocess
from Bio.Seq import Seq
from Bio import SeqIO

trimal = '/path/to/trimal'
muscle = '/path/to/muscle3.8.31_i86linux64'
# this is the fasta containing the single reference gene we use for trimming all of our seqeunces 
ref_gene = '/path/to/single/ref.fasta'

all_out = open('file_to_fix.Trimmed.fasta', 'w')

# this is the fasta containing all the sequences we want to trim
for s in SeqIO.parse('file_to_fix.fasta', 'fasta'):
    # concatenate with single gene, align using muscle, trim beguinning and endnig gaps with trimAl
    with open('Both.fasta', 'w') as out:
        out.write(s.format('fasta'))

    cmd0 = 'cat %s >> Both.fasta'%ref_gene
    p = subprocess.Popen(cmd0, stdout=subprocess.PIPE, shell=True)
    (output, err) = p.communicate()
    p_status = p.wait()

    cmd1 = '%s -in Both.fasta -out Result.fasta'%muscle
    p = subprocess.Popen(cmd1, stdout=subprocess.PIPE, shell=True)
    (output, err) = p.communicate()
    p_status = p.wait()
    cmd2 = '%s -in Result.fasta -nogaps -keepheader  -terminalonly > Result_Trimmed.fasta'%trimal

    p = subprocess.Popen(cmd2, stdout=subprocess.PIPE, shell=True)
    (output, err) = p.communicate()
    p_status = p.wait()

    x = [y for y in SeqIO.parse('Result_Trimmed.fasta', 'fasta')]
    x = x[0]
    x.seq = Seq(str(x.seq).replace("-", ""))
    all_out.write(x.format('fasta'))
all_out.close()