# HG changeset patch # User gianmarco_piccinno # Date 1544353692 18000 # Node ID 987ac30b5bb08d046cbce077c6068345a268ee50 # Parent 92d2b0a3708688bcad95e4aa8d15ea8c7229abed Deleted selected files diff -r 92d2b0a37086 -r 987ac30b5bb0 Project_RM/codon_usage2.py --- a/Project_RM/codon_usage2.py Sun Dec 09 06:00:26 2018 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,149 +0,0 @@ -#!/usr/bin/env python - -import Bio as Bio -from Bio import SeqIO -from Bio.Data import CodonTable -import re -from pprint import pprint -import argparse as ap -import sys -import os -import pandas as pd -#from BCBio import GFF - - -def read_input(data = "example.fna", type_ = "fasta"): - - """ - Accepted formats: - - fasta (multifasta) - - gff - - gbk - - """ - - - seqs = "" - - if type_ == "fasta": - with open(data, "rU") as handle: - for record in SeqIO.parse(handle, type_): - seqs = seqs + str(record.seq) - - - #elif type_ == "gff": - # with open(data, "rU") as handle: - # for record in GFF.parse(handle): - # seqs = seqs + str(record.seq) - - elif type_ == "gbk": - with open(data, "rU") as input_handle: - for record in SeqIO.parse(input_handle, "genbank"): - 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()} - - codon_usage_ = pd.DataFrame(pd.Series(tups), columns = ["Count"]) - codon_usage_.index = codon_usage_.index.set_names(["AA", "Codon"]) - 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__': - - parser = ap.ArgumentParser(description= - 'This script takes as input gff, gbk and single or multifasta files and \n' - 'compute the codon usage for a specified codon table.\n' - 'Usage:\n' - 'python codon_usage.py -i example.gbk -t genebank -o gbk_example -c Bacterial\n' - 'python codon_usage.py -i example.ffn -t fasta -o fasta_example -c Bacterial\n' - 'python codon_usage.py -i example.gff -t gff -o gff_example -c Bacterial\n', - formatter_class=ap.RawTextHelpFormatter) - - parser.add_argument('-i','--input', help='The path to the input file',required=True) - parser.add_argument('-t','--type', help= - 'The format of the file [genebank, fasta, gff ...]', required=True) - parser.add_argument('-c','--codonTable', help= - 'The codon table to be used [Standard, Bacterial, Archaeal ...]\n' - 'Alternative Flatworm Mitochondrial,\\n' - 'Alternative Yeast Nuclear,\n' - 'Archaeal,\n' - 'Ascidian Mitochondrial,\n' - 'Bacterial,\n' - 'Blastocrithidia Nuclear,\n' - 'Blepharisma Macronuclear,\n' - 'Candidate Division SR1,\n' - 'Chlorophycean Mitochondrial,\n' - 'Ciliate Nuclear,\n' - 'Coelenterate Mitochondrial,\n' - 'Condylostoma Nuclear,\n' - 'Dasycladacean Nuclear,\n' - 'Echinoderm Mitochondrial,\n' - 'Euplotid Nuclear,\n' - 'Flatworm Mitochondrial,\n' - 'Gracilibacteria,\n' - 'Hexamita Nuclear,\n' - 'Invertebrate Mitochondrial,\n' - 'Karyorelict Nuclear,\n' - 'Mesodinium Nuclear,\n' - 'Mold Mitochondrial,\n' - 'Mycoplasma,\n' - 'Pachysolen tannophilus Nuclear,\n' - 'Peritrich Nuclear,\n' - 'Plant Plastid,\n' - 'Protozoan Mitochondrial,\n' - 'Pterobranchia Mitochondrial,\n' - 'SGC0,\n' - 'SGC1,\n' - 'SGC2,\n' - 'SGC3,\n' - 'SGC4,\n' - 'SGC5,\n' - 'SGC8,\n' - 'SGC9,\n' - 'Scenedesmus obliquus Mitochondrial,\n' - 'Spiroplasma,\n' - 'Standard,\n' - 'Thraustochytrium Mitochondrial,\n' - 'Trematode Mitochondrial,\n' - 'Vertebrate Mitochondrial,\n' - 'Yeast Mitochondrial\n', required=True) - - parser.add_argument('-o','--output', help='Description for bar argument', required=True) - args = vars(parser.parse_args()) - - seqs = read_input(data=args['input'], type_=args['type']) - out = codon_usage(seqs, args['codonTable']) - - with open(args['output'], "w") as outf: - out["Table"].to_csv(outf, sep="\t", index_label=["AA", "Codon"]) - - \ No newline at end of file diff -r 92d2b0a37086 -r 987ac30b5bb0 Project_RM/codon_usage_complete.xml --- a/Project_RM/codon_usage_complete.xml Sun Dec 09 06:00:26 2018 -0500 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,39 +0,0 @@ - - for each sequence in a file - - biopython - pandas - - - codon_usage2.py python -i $input -t $input_type -o $output -c $codon_table - - - - - - - - - - - - - - - - - - - - - - - - - - - - -This tool compute codon usage of an annotated genome [preferably Prokaryotes]. - -