How to get predicted editing efficiency using only gRNA sequence

[shaicoh3n]

Hello,

Is it possible to get an estimation of the editing efficiency using only the gRNA?
looking at the code I thought it could be done like this:

m_frac_total_del = pickle.load(open('models/fraction_total_deletions_other_cells.p', 'rb'))
m_frac_total_ins = pickle.load(open('models/fraction_total_insertions_other_cells.p', 'rb'))
frac_total_del = 100 * float(m_frac_total_del.predict(sequence_pam_per_gene_grna)[0])
frac_total_ins = 100 * float(m_frac_total_ins.predict(sequence_pam_per_gene_grna)[0])
p_edit_eff = frac_total_ins + frac_total_del

Although i did see there's a commented out line where frac_total_del is calculated like this:
print "Fraction of total reads with deletion \t\t %.0f %%" % (frac_total_ins(100/(frac_mutant_ins) -1))*
where the bold part is frac_total_del.

Can you tell me if the way I calculate the editing efficiency (p_edit_eff ) is correct? or how to do so if it isn't?

Thanks!