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Project_RM/codon_usage.py Project_RM/codon_usage.xml |
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| diff -r fb16cdb5f2e2 -r 39401213c7a2 Project_RM/codon_usage.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/Project_RM/codon_usage.py Sun Dec 09 06:11:53 2018 -0500 |
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| @@ -0,0 +1,75 @@ +#!/home/gianmarco/galaxy-python/python + +import Bio +from Bio import SeqIO +from Bio.Data import CodonTable +import re +import sys +import os +import pandas as pd + +def read_input(data = "example.fna"): + + seqs = "" + with open(data, "rU") as handle: + for record in SeqIO.parse(handle, "fasta"): + seqs = seqs + str(record.seq) + + return seqs + +def codon_usage(seqs, codonTable): + + codon_usage = {} + tmp = [x for x in re.split(r'(\w{3})', seqs) if x != ""] + + b_cod_table = CodonTable.unambiguous_dna_by_name[codonTable].forward_table + + + for cod in CodonTable.unambiguous_dna_by_name[codonTable].stop_codons: + b_cod_table[cod] = "_Stop" + + for cod in CodonTable.unambiguous_dna_by_name[codonTable].start_codons: + b_cod_table[cod + " Start"] = b_cod_table[cod] + b_cod_table.pop(cod) + + aas = set(b_cod_table.values()) + + + for aa in aas: + codon_usage[aa] = {} + for codon in b_cod_table.keys(): + if b_cod_table[codon] == aa: + codon_usage[aa][codon] = tmp.count(codon.split(" ")[0]) + + + tups = {(outerKey, innerKey): values for outerKey, innerDict in codon_usage.iteritems() for innerKey, values in innerDict.iteritems()} + + #aas_ = set(tups.keys()) + + #stops_ = {el for el in aas_ if el[0] == "Stop"} + #aas_ = list(aas_.difference(stops_)) + #stops_ = list(stops_) + #aas_.sort() + #stops_.sort() + + codon_usage_ = pd.DataFrame(pd.Series(tups), columns = ["Count"]) + codon_usage_.index = codon_usage_.index.set_names(["AA", "Codon"]) + #codon_usage_.index.reindex(pd.MultiIndex.from_tuples([aas_, stops_], names=('AA', 'Codon')), level=[0,1]) + + + codon_usage_['Proportion'] = codon_usage_.groupby(level=0).transform(lambda x: (x / x.sum()).round(2)) + + return {"Dictionary": codon_usage, "Tuples": tups, "Table": codon_usage_} + + + +if __name__ == '__main__': + + + seqs = read_input(data=sys.argv[1]) + out = codon_usage(seqs,"Bacterial") + + + with open(sys.argv[2], "w") as outf: + out["Table"].to_csv(outf, sep="\t") + #sys.stdout.write(out['Table']) \ No newline at end of file |
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| diff -r fb16cdb5f2e2 -r 39401213c7a2 Project_RM/codon_usage.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/Project_RM/codon_usage.xml Sun Dec 09 06:11:53 2018 -0500 |
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| @@ -0,0 +1,44 @@ +<tool id="codon_usage" name="Codon Usage" version="0.1.0"> + <description>for each sequence in a file</description> + <requirements> + <requirement type="python module">biopython</requirement> + <requirement type="python module">pandas</requirement> + </requirements> + + <command interpreter="python">codon_usage2.py -i $input -t $input_type -o $output -c $codon_table</command> + <inputs> + <param name="input" format="fasta" type="data" label="Source file"/> + + <param name="input_type" type="select" format="text"> + <label>Indicate the input file format</label> + <option value="fasta">Fasta</option> + <option value="gbk">gbk</option> + </param> + + <param name="codon_table" type="select" format="text"> + <label>Choose the proper codon table for your organism)</label> + <option value="Archaeal"> Archaeal</option> + <option value="Bacterial">Bacterial</option> + <option value="Standard">Standard</option> + + </param> + + </inputs> + + + + <outputs> + <data format="tabular" name="output" /> + </outputs> + + <tests> + <test> + <param name="input" value="fa_gc_content_input.fa"/> + <output name="out_file1" file="fa_gc_content_output.txt"/> + </test> + </tests> + + <help> +This tool compute codon usage of an annotated genome [preferably Prokaryotes]. + </help> +</tool> |