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Rna.py
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Rna.py
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from Fasta import Fasta
import networkx as nx
import numpy as np
import math
import itertools
import Solutions as sols
from matplotlib import pyplot as plt
from tqdm import tqdm
codon_map = {
"UUU": "F",
"CUU": "L",
"AUU": "I",
"GUU": "V",
"UUC": "F",
"CUC": "L",
"AUC": "I",
"GUC": "V",
"UUA": "L",
"CUA": "L",
"AUA": "I",
"GUA": "V",
"UUG": "L",
"CUG": "L",
"AUG": "M",
"GUG": "V",
"UCU": "S",
"CCU": "P",
"ACU": "T",
"GCU": "A",
"UCC": "S",
"CCC": "P",
"ACC": "T",
"GCC": "A",
"UCA": "S",
"CCA": "P",
"ACA": "T",
"GCA": "A",
"UCG": "S",
"CCG": "P",
"ACG": "T",
"GCG": "A",
"UAU": "Y",
"CAU": "H",
"AAU": "N",
"GAU": "D",
"UAC": "Y",
"CAC": "H",
"AAC": "N",
"GAC": "D",
"UAA": "Stop",
"CAA": "Q",
"AAA": "K",
"GAA": "E",
"UAG": "Stop",
"CAG": "Q",
"AAG": "K",
"GAG": "E",
"UGU": "C",
"CGU": "R",
"AGU": "S",
"GGU": "G",
"UGC": "C",
"CGC": "R",
"AGC": "S",
"GGC": "G",
"UGA": "Stop",
"CGA": "R",
"AGA": "R",
"GGA": "G",
"UGG": "W",
"CGG": "R",
"AGG": "R",
"GGG": "G",
}
class Rna(Fasta):
def __init__(self, lines):
super().__init__(lines)
def count_acgu(self):
"""Counts the appearance of each letter in the DNA string
Returns:
tuple: (num of As, num of Cs, num of Gs, num of Ts)
"""
acgt = [0, 0, 0, 0]
for char in self.string:
if char in {"A", 'a'}:
acgt[0] += 1
elif char in {'C', 'c'}:
acgt[1] += 1
elif char in {'G', 'g'}:
acgt[2] += 1
elif char in {'U', 'u'}:
acgt[3] += 1
return acgt[0], acgt[1], acgt[2], acgt[3]
def to_protein_string(self):
amino_acid_string = ""
codons = [self.string[i:i+3] for i in range(0,len(self.string),3)]
for codon in codons[:-1]:
try:
amino_acid_string += codon_map[codon]
except:
return ""
return amino_acid_string
def codon_combinations(self, modulus):
reverse_codon_count = dict()
for acid in codon_map.values():
if acid in reverse_codon_count:
reverse_codon_count[acid] += 1
else:
reverse_codon_count[acid] = 1
total = 1
for char in self.string:
total *= reverse_codon_count[char]
total *= reverse_codon_count['Stop']
return total % 1_000_000
def num_max_matchings(self):
ACGU = self.count_acgu()
return math.perm(max(ACGU[0], ACGU[3]), min(ACGU[0], ACGU[3])) * math.perm(max(ACGU[1], ACGU[2]), min(ACGU[1], ACGU[2]))