comparison tools/protein_analysis/tmhmm2.py @ 2:6901298ac16c

Migrated tool version 0.0.5 from old tool shed archive to new tool shed repository

1:3ff1dcbb9440

This script takes exactly two command line arguments - an input protein FASTA
filename and an output tabular filename. It then calls the standalone TMHMM
v2.0 program (not the webservice) requesting the short output (one line per
protein).

First major feature is cleaning up the tabular output. The raw output from
TMHMM v2.0 looks like this (six columns tab separated):

 gi|2781234|pdb|1JLY|B	len=304 ExpAA=0.01	First60=0.00	PredHel=0	Topology=o
 gi|4959044|gb|AAD34209.1|AF069992_1	len=600	ExpAA=0.00	First60=0.00	PredHel=0	Topology=o
 gi|671626|emb|CAA85685.1|	len=473 ExpAA=0.19	First60=0.00 PredHel=0	Topology=o
 gi|3298468|dbj|BAA31520.1|	len=107	ExpAA=59.37	First60=31.17	PredHel=3	Topology=o23-45i52-74o89-106i

In order to make it easier to use in Galaxy, this wrapper script simplifies
this to remove the redundant tags, and instead adds a comment line at the
top with the column names:

def clean_tabular(raw_handle, out_handle):
    """Clean up tabular TMHMM output, returns output line count."""
    count = 0
    for line in raw_handle:
        if not line:
            continue
        parts = line.rstrip("\r\n").split("\t")
        try:
            identifier, length, expAA, first60, predhel, topology = parts
        except:

#Note that if the input FASTA file contains no sequences,
#split_fasta returns an empty list (i.e. zero temp files).
fasta_files = split_fasta(fasta_file, tabular_file, FASTA_CHUNK)
temp_files = [f+".out" for f in fasta_files]
jobs = ["tmhmm %s > %s" % (fasta, temp)
        for fasta, temp in zip(fasta_files, temp_files)]

def clean_up(file_list):
    for f in file_list:
        if os.path.isfile(f):

2:6901298ac16c

This script takes exactly two command line arguments - an input protein FASTA
filename and an output tabular filename. It then calls the standalone TMHMM
v2.0 program (not the webservice) requesting the short output (one line per
protein).

The first major feature is cleaning up the tabular output. The short form raw
output from TMHMM v2.0 looks like this (six columns tab separated):

 gi|2781234|pdb|1JLY|B	len=304 ExpAA=0.01	First60=0.00	PredHel=0	Topology=o
 gi|4959044|gb|AAD34209.1|AF069992_1	len=600	ExpAA=0.00	First60=0.00	PredHel=0	Topology=o
 gi|671626|emb|CAA85685.1|	len=473 ExpAA=0.19	First60=0.00 PredHel=0	Topology=o
 gi|3298468|dbj|BAA31520.1|	len=107	ExpAA=59.37	First60=31.17	PredHel=3	Topology=o23-45i52-74o89-106i

If there are any additional 'comment' lines starting with the hash (#)
character these are ignored by this script.

In order to make it easier to use in Galaxy, this wrapper script simplifies
this to remove the redundant tags, and instead adds a comment line at the
top with the column names:

def clean_tabular(raw_handle, out_handle):
    """Clean up tabular TMHMM output, returns output line count."""
    count = 0
    for line in raw_handle:
        if not line.strip() or line.startswith("#"):
            #Ignore any blank lines or comment lines
            continue
        parts = line.rstrip("\r\n").split("\t")
        try:
            identifier, length, expAA, first60, predhel, topology = parts
        except:

#Note that if the input FASTA file contains no sequences,
#split_fasta returns an empty list (i.e. zero temp files).
fasta_files = split_fasta(fasta_file, tabular_file, FASTA_CHUNK)
temp_files = [f+".out" for f in fasta_files]
jobs = ["tmhmm -short %s > %s" % (fasta, temp)
        for fasta, temp in zip(fasta_files, temp_files)]

def clean_up(file_list):
    for f in file_list:
        if os.path.isfile(f):