<jupyter_start><jupyter_text>TM Sequence analysisA workbook to analyse the TM sequences of TM annotated Swissprot proteins from the 3 domains.  All TM domains were annotated again using TMHMM and the sequences +/- 3 residues and orientations pulled outfrom TMHMM output using a trivial script<jupyter_code>ls 
def get_seqs_only(filename):
    """
    Func to read file and strip out accesions data
    returns a list of seqs
    """
    
    seqs = []
    with open(filename, 'r') as fh:
        for line in fh.readlines():
            if not line.startswith(">"):
                seqs.append(line.strip())
    return seqs
seqs = {}
for fn in sorted(glob.glob("*.fasta")):
    name = fn.split('_')
    name = name[0] + '_' + name[-3]
    seqs.update({name: get_seqs_only(fn)})
seqs['archaea_ii'][]<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11124546553808948, 'fraction_numerical': 0.0048367593712212815, 'mean_word_length': 3.290155440414508, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 6, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '594725', 'license': 'Apache-2.0', 'n_tokens_mistral': 285, 'n_tokens_neox': 262, 'n_words': 86, 'path': 'analysis/data_exploration/TM Sequences Analysis Across Domains.ipynb', 'repo_name': 'fmaguire/volution', 'size': '827'}