Example usage

The main goal of codino is to convert amino acid (AA) frequencies to codon design (CD), and vice versa.

import codino

print(codino.__version__)

0.1.1

Users should initialise a Converter.

from codino.process import Converter

c = Converter()

The two useful methods within a Converter are cd_to_aa() and aa_to_cd(), which converts a CD to AA frequencies and vice versa.

# input the expected nucleotide frequencies at each position
c.cd_to_aa(first={"A": 1}, second={"T": 1}, third={"G": 1})

# input the desired AA frequencies
first, second, third = c.aa_to_cd(aa={'D': 0.4, 'N': 0.6})

# you can check the output by converting the codon design back to AA frequencies
c.cd_to_aa(first, second, third) == {'D': 0.4, 'N': 0.6}

True

For more complex examples, the conversion of the AA frequencies to a CD will be an estimate.

exp_aa = {'A': 0.1771,
          'D': 0.208131,
          'E': 0.18456899999999998,
          'I': 0.031694,
          'K': 0.055131,
          'M': 0.028106000000000003,
          'N': 0.062169,
          'T': 0.0529,
          'V': 0.2002}

first, second, third = c.aa_to_cd(aa=exp_aa)
pred_aa = c.cd_to_aa(first, second, third)

pred_aa == exp_aa

False

In this case, it can be helpful to obtain the error between the expected and predicted AA frequencies.

errors = [abs(pred_aa[a] - exp_aa[a]) for a in exp_aa]

print(f'Average error per AA ==> {sum(errors)/len(errors)}')

print(f'Total error across AAs ==> {sum(errors)}')

Average error per AA ==> 0.0055103958222222325
Total error across AAs ==> 0.049593562400000096