Получение списка сайтов рестрикции

import pandas as pd
with open('restr_sites.txt', 'w') as out:
    t = pd.read_csv('TypeII_REs.tsv', sep='\t', header=0)
    sites = list(t['Recognition site'].unique())
    for site in sites:
        if len(site) <= 2:
            sites.remove(site)
    print(' '.join([site for site in sites]), file=out)

Отбор недопредставленных сайтов в геноме

import pandas as pd
with open('most_underepr_sites.txt', 'w') as out:
    t = pd.read_csv('output.tsv', sep='\t', header=0)
    t = t[t['O/E ratio (BCK)'] < 0.8]
    print('\n'.join([site for site in list(t['Site'])]), file = out)
    unrep_sites = list(t['Site'])
print(unrep_sites)

['GGATCC', 'CTAG', 'CCTAGG']

Отбор экспериментально проверенных эндонуклеаз, соответствующих недопредставленным сайтам

t = pd.read_csv('endon_ex_heads.tsv', sep='\t', header=0)
unrep_sites = ['GGATCC', 'CTAG', 'CCTAGG']
u = t.loc[t['Recognition site'].isin(unrep_sites)]
u.to_csv('endon_underepr_ex.tsv', sep='\t', index=False)

!jupyter nbconvert --to html 'signals and motifs 3.ipynb'

[NbConvertApp] Converting notebook signals and motifs 3.ipynb to html
[NbConvertApp] Writing 574203 bytes to signals and motifs 3.html