def makeMutantFromSequence(target_protein_seq, base_dna_seq): codons = [x for x in translate.codons(base_dna_seq)] base_prot_seq = translate.translate(base_dna_seq) assert len(base_prot_seq) == len(target_protein_seq) mutant_dna_seq = '' for (i, aa) in enumerate(target_protein_seq): if aa == base_prot_seq[i]: mutant_dna_seq += codons[i] else: mutant_dna_seq += translate.randomReverseTranslate(aa) assert translate.translate(mutant_dna_seq) == target_protein_seq return mutant_dna_seq
def test_run(self):
# Here we are trying to test whether ln odds X/Y + ln odds Y/Z = ln odds X/Z.
# Assign reference codons
# Build a dictionary where each codon gets its reference.
random.seed(111)
gc = translate.geneticCode(rna=False)
reference_codon_dict1 = {}
reference_codon_dict2 = {}
for codon in translate.AADNACodons():
aa = gc[codon]
aa_codons = translate.getCodonsForAA(aa, rna=False)
# Sort in alphabetical order by reverse.
aa_codons.sort(key=lambda x: x[::-1])
reference_codon_dict1[codon] = aa_codons[0]
reference_codon_dict2[codon] = aa_codons[-1]
reference_codon_dict1['GCA'] = 'GCC'
reference_codon_dict2['GCA'] = 'GCT'
# Focus on alanine: GCN. Check if GCA->GCC + GCC->GCT = GCA->GCT
#reference_codon_dict[]
species = ['x','y']
prots = {"dmel":'MNKYGMVGVCLLAALGALLLEVTASPSS--AA-SSKVDPSQLGGLSAQFLPPEYRNTNVSIEDIKRIYREKCKKVNGADNATFYEEIERAAAKMSTCISGVVNLTALQEEMDVARPNGDLDTVFSKYCLKAPEAEACVKEFNDKAQHCLTPEEKRHQETVTRIGASVLGFACSRGGDQIALFIAEQGPECLEANKEAISNCLNQSFHQYIPKDGQVPDLMSRPELLFSPTHCVDLQRFEACVIHHLEQCTQITTANIVQSVFRFVKNETDCQAWMQARANEKPILMAASSNNTAPGLA-YS--LAGTL-----LGATILLILPMNKYGMVGVCLLAALGALLLEVTASPSS--AA-SSKVDPSQLGGLSAQFLPPEYRNTNVSIEDIKRIYREKCKKVNGADNATFYEEIERAAAKMSTCISGVVNLTALQEEMDVARPNGDLDTVFSKYCLKAPEAEACVKEFNDKAQHCLTPEEKRHQETVTRIGASVLGFACSRGGDQIALFIAEQGPECLEANKEAISNCLNQSFHQYIPKDGQVPDLMSRPELLFSPTHCVDLQRFEACVIHHLEQCTQITTANIVQSVFRFVKNETDCQAWMQARANEKPILMAASSNNTAPGLA-YS--LAGTL-----LGATILLILP',
#"dere":'MNKYGIVGVCLLAALGALLLEVTADS-----A-SPKLDPSQLGGLSAQFLPPEYRNTNVSIDDMKRIYREKCKKVNGADNATFYAEIERAAAKMSNCLNGVVNLTALQEEMDVAKPNGDLDTVFSKYCQKAPEAVACVKEFNEKAQHCLTAEEKRHQETVTRIGASVLGFACSRGGDQIALFIAEQGPECLEANKEAISNCLNQSFHQYIPKDGQVPDLMSRPELLFSPTHCVDLQRFESCVIHHLEQCTQITTANIVQSVFKFVKNETDCQSWMQARANEKPILLAASSNNTATGLA-YS--LAGPL-----LGATLLLMRP',
#"dana":'MHKYTLMGLCLMAALGAVLLEVNASPAG--VAIPTKLDPSQLGGLSAQFLPPEYRNTNVTVDDLKRLYREKCKKVTGADNSSFYEEIERAAAKMSNCISGVANLTAIQEEMEQAKPQGELDTVFHKYCQKAPEAEACVKEFNTKMQVCLTAEEKRHQETIARIGASLLGFACSRGGDQIALFVAEQGPECLDANKEAIANCLNQSFHNYIPKDGQVPDLMSAPELLFSPTHCVDLQRFESCVLHHLEQCSEITPANIVQSIFKFVKNETDCQAYMTARANEKPILMAAAGNSTGGGATGLTSHFGSLLAGIFASGLVLILNRY',
#"dyak":'MNKYGMVGVCLLAALGALLLEVTASPSSTGSA-STKLDPSQLGGLSAQFLPPEYRNTNVSIEDVKRIYREKCKKVNGADNATFYEEIERAAAKMSTCISGVVNLTALQEEMDVAKPNGDLDMVFSKYCQKAPQAEACVKEFNAKAQHCLTAEEKRHQETVTRIGASVLGFACSHGGDQI-------GPECLEANKEAISNCLNQSFHQYIPKDGQVPDLMSRPELLFSPTHCVDLQRFEACVVHHLEQCTQITTANIVQSVFRFVKNETDCQAWMQARANEKPILLAASGNNTATGLA-YS--LAGPL-----LGATMLLMRP'}
"dyak":'XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXQHCLTAEEKRHQETVTRIGASVLGFACSHGGDQI-------GPECLEANKEAISNCLNQSFHQYIPKDGQVPDLMSRPELLFSPTHCVDLQRFEACVVHHLEQCTQITTANIVQSVFRFVKNETDCQAWMQARANEKPILLAASGNNTATGLA-YS--LAGPL-----LGATMLLMRPMNKYGMVGVCLLAALGALLLEVTASPSS--AA-SSKVDPSQLGGLSAQFLPPEYRNTNVSIEDIKRIYREKCKKVNGADNATFYEEIERAAAKMSTCISGVVNLTALQEEMDVARPNGDLDTVFSKYCLKAPEAEACVKEFNDKAQHCLTPEEKRHQETVTRXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX-XX--XXXXX-----XXXXXXXXXX'}
genes = {"dmel":"ATGAACAAGTACGGGATGGTCGGCGTCTGCCTACTGGCTGCTCTGGGCGCTCTGCTCCTGGAGGTCACTGCCTCTCCTTCGTCCGCCGCCTCGTCTAAGGTGGATCCTAGCCAACTTGGCGGACTTTCAGCTCAGTTCTTGCCACCCGAGTACCGCAACACGAACGTTAGCATCGAGGATATAAAAAGAATATATCGTGAAAAATGCAAGAAGGTAAATGGAGCGGACAACGCAACCTTCTACGAAGAAATCGAGCGGGCGGCAGCCAAGATGAGCACCTGCATCAGCGGGGTGGTCAATCTGACGGCTCTGCAGGAGGAGATGGATGTGGCGAGGCCGAACGGCGACTTGGACACCGTGTTTAGCAAATACTGTCTCAAGGCACCGGAGGCAGAGGCCTGCGTCAAGGAGTTCAACGACAAGGCGCAGCATTGCTTGACCCCCGAGGAGAAGCGCCACCAGGAGACGGTTACCCGAATTGGAGCGTCCGTTTTGGGATTCGCCTGTTCGCGTGGCGGCGATCAGATTGCCCTCTTCATTGCCGAGCAGGGACCCGAGTGCCTGGAGGCCAACAAGGAAGCCATTAGCAATTGCCTCAATCAATCCTTTCATCAGTACATTCCCAAGGATGGCCAAGTTCCGGACCTGATGAGCCGCCCAGAGCTCCTTTTCTCACCCACCCACTGCGTGGACCTGCAGCGCTTCGAGGCCTGTGTCATCCATCATTTGGAGCAGTGCACGCAGATCACCACCGCTAATATCGTTCAGTCCGTCTTCCGTTTCGTGAAGAACGAGACCGACTGCCAGGCTTGGATGCAGGCACGTGCGAACGAGAAGCCCATTCTGATGGCCGCCTCCAGCAACAACACAGCCCCTGGACTCGCCTACTCCCTGGCCGGCACTCTTTTGGGCGCCACAATACTCCTGATACTCCCCTGAATGAACAAGTACGGGATGGTCGGCGTCTGCCTACTGGCTGCTCTGGGCGCTCTGCTCCTGGAGGTCACTGCCTCTCCTTCGTCCGCCGCCTCGTCTAAGGTGGATCCTAGCCAACTTGGCGGACTTTCAGCTCAGTTCTTGCCACCCGAGTACCGCAACACGAACGTTAGCATCGAGGATATAAAAAGAATATATCGTGAAAAATGCAAGAAGGTAAATGGAGCGGACAACGCAACCTTCTACGAAGAAATCGAGCGGGCGGCAGCCAAGATGAGCACCTGCATCAGCGGGGTGGTCAATCTGACGGCTCTGCAGGAGGAGATGGATGTGGCGAGGCCGAACGGCGACTTGGACACCGTGTTTAGCAAATACTGTCTCAAGGCACCGGAGGCAGAGGCCTGCGTCAAGGAGTTCAACGACAAGGCGCAGCATTGCTTGACCCCCGAGGAGAAGCGCCACCAGGAGACGGTTACCCGAATTGGAGCGTCCGTTTTGGGATTCGCCTGTTCGCGTGGCGGCGATCAGATTGCCCTCTTCATTGCCGAGCAGGGACCCGAGTGCCTGGAGGCCAACAAGGAAGCCATTAGCAATTGCCTCAATCAATCCTTTCATCAGTACATTCCCAAGGATGGCCAAGTTCCGGACCTGATGAGCCGCCCAGAGCTCCTTTTCTCACCCACCCACTGCGTGGACCTGCAGCGCTTCGAGGCCTGTGTCATCCATCATTTGGAGCAGTGCACGCAGATCACCACCGCTAATATCGTTCAGTCCGTCTTCCGTTTCGTGAAGAACGAGACCGACTGCCAGGCTTGGATGCAGGCACGTGCGAACGAGAAGCCCATTCTGATGGCCGCCTCCAGCAACAACACAGCCCCTGGACTCGCCTACTCCCTGGCCGGCACTCTTTTGGGCGCCACAATACTCCTGATACTCCCCTGA",
"dyak":"ATGAACAAGTACGGGATGGTTGGCGTTTGCCTACTGGCTGCTCTGGGCGCTCTGCTCCTGGAGGTCACCGCCTCTCCTTCGTCCACCGGCTCGGCGAGTACCAAGCTGGATCCCAGCCAGCTAGGCGGACTTTCGGCCCAGTTCTTACCGCCCGAGTACCGCAACACGAACGTTAGCATCGAGGACGTTAAAAGAATATATCGTGAAAAATGCAAGAAGGTTAATGGAGCGGACAACGCGACCTTCTACGAGGAAATCGAGCGGGCGGCCGCGAAGATGAGCACCTGCATCAGCGGAGTGGTCAACCTGACGGCTCTGCAGGAGGAGATGGATGTGGCCAAGCCGAACGGCGACCTGGACATGGTGTTTAGCAAGTACTGCCAGAAGGCACCGCAGGCGGAGGCCTGTGTCAAGGAGTTCAACGCCAAGGCCCAGCATTGCTTGACCGCCGAGGAGAAGCGCCACCAGGAGACGGTCACCCGCATTGGAGCGTCCGTTCTGGGCTTCGCCTGCTCGCATGGTGGCGATCAGATTGGACCCGAGTGCCTGGAGGCCAACAAGGAGGCCATAAGCAATTGCCTCAACCAATCCTTCCATCAGTACATTCCCAAGGATGGCCAAGTTCCGGACCTGATGAGCCGCCCAGAACTCCTGTTCTCGCCCACCCACTGCGTGGACCTGCAGCGCTTCGAGGCGTGTGTCGTCCATCATTTGGAACAGTGCACCCAGATCACAACCGCCAACATCGTTCAGTCCGTCTTCCGCTTCGTGAAGAACGAGACCGACTGCCAGGCTTGGATGCAGGCTCGTGCCAACGAGAAGCCCATCCTGCTGGCCGCCTCCGGCAACAATACAGCCACTGGACTCGCCTACTCTCTGGCCGGCCCTCTCTTGGGCGCCACAATGCTCCTGATGCGCCCCTGAATGAACAAGTACGGGATGGTTGGCGTTTGCCTACTGGCTGCTCTGGGCGCTCTGCTCCTGGAGGTCACCGCCTCTCCTTCGTCCACCGGCTCGGCGAGTACCAAGCTGGATCCCAGCCAGCTAGGCGGACTTTCGGCCCAGTTCTTACCGCCCGAGTACCGCAACACGAACGTTAGCATCGAGGACGTTAAAAGAATATATCGTGAAAAATGCAAGAAGGTTAATGGAGCGGACAACGCGACCTTCTACGAGGAAATCGAGCGGGCGGCCGCGAAGATGAGCACCTGCATCAGCGGAGTGGTCAACCTGACGGCTCTGCAGGAGGAGATGGATGTGGCCAAGCCGAACGGCGACCTGGACATGGTGTTTAGCAAGTACTGCCAGAAGGCACCGCAGGCGGAGGCCTGTGTCAAGGAGTTCAACGCCAAGGCCCAGCATTGCTTGACCGCCGAGGAGAAGCGCCACCAGGAGACGGTCACCCGCATTGGAGCGTCCGTTCTGGGCTTCGCCTGCTCGCATGGTGGCGATCAGATTGGACCCGAGTGCCTGGAGGCCAACAAGGAGGCCATAAGCAATTGCCTCAACCAATCCTTCCATCAGTACATTCCCAAGGATGGCCAAGTTCCGGACCTGATGAGCCGCCCAGAACTCCTGTTCTCGCCCACCCACTGCGTGGACCTGCAGCGCTTCGAGGCGTGTGTCGTCCATCATTTGGAACAGTGCACCCAGATCACAACCGCCAACATCGTTCAGTCCGTCTTCCGCTTCGTGAAGAACGAGACCGACTGCCAGGCTTGGATGCAGGCTCGTGCCAACGAGAAGCCCATCCTGCTGGCCGCCTCCGGCAACAATACAGCCACTGGACTCGCCTACTCTCTGGCCGGCCCTCTCTTGGGCGCCACAATGCTCCTGATGCGCCCCTGA"}
#algenes = dict([(s,muscle.alignGeneFromProtein(genes[s], prots[s])) for s in species])
species = ['x','y']
prot1 = randomProtein(1000)
prot2 = mutProtein(prot1)
prots = {"x":prot1, "y":prot2}
algenes = dict([(s,translate.randomReverseTranslate(prots[s],bad_codon='---')) for s in species])
#print algenes
gene_codon_tables1 = cai.getAkashi2x2TablesForORFRefCodon(cai.conservedAA, reference_codon_dict1, algenes['x'], prots['x'], [algenes['y']], [prots['y']], pseudocount=0, n_terminal_start=0)
gene_codon_tables2 = cai.getAkashi2x2TablesForORFRefCodon(cai.conservedAA, reference_codon_dict2, algenes['x'], prots['x'], [algenes['y']], [prots['y']], pseudocount=0, n_terminal_start=0)
#print gene_codon_tables1
eps = 1e-6
#for aa in translate.degenerateAAs():
# for codon in translate.getCodonsForAA(aa):
for codon in ['GCA']:
ref_codon1 = reference_codon_dict1[codon]
ref_codon2 = reference_codon_dict2[codon]
self.assertTrue(gc[codon] == gc[ref_codon1])
self.assertTrue(gc[codon] == gc[ref_codon2])
# codon to ref_codon1
mh_res1 = stats.MantelHaenszelOddsRatioVariance(gene_codon_tables1[codon])
sc_1_to_r1 = -mh_res1.ln_odds_ratio
# ref_codon1 to ref_codon2
mh_res2 = stats.MantelHaenszelOddsRatioVariance(gene_codon_tables2[ref_codon1])
sc_r1_to_r2 = -mh_res2.ln_odds_ratio
# codon to ref_codon2
mh_res3 = stats.MantelHaenszelOddsRatioVariance(gene_codon_tables2[codon])
sc_1_to_r2 = -mh_res3.ln_odds_ratio
# prediction from additivity
pred_sc_1_to_r2 = sc_1_to_r1 + sc_r1_to_r2
#print "{0}->{1} = {2}".format(codon, ref_codon1, sc_1_to_r1)
#print "{0}->{1} = {2}".format(ref_codon1, ref_codon2, sc_r1_to_r2)
#print "{0}->{1} = {2}".format(codon, ref_codon2, sc_1_to_r2)
#, ref_codon2, sc_1_to_r1, sc_r1_to_r2, sc_1_to_r2, pred_sc_1_to_r2
self.assertTrue(abs(sc_1_to_r2-pred_sc_1_to_r2) < eps)
def test_run(self):
# Here we are trying to test whether ln odds X/Y + ln odds Y/Z = ln odds X/Z.
# Assign reference codons
# Build a dictionary where each codon gets its reference.
random.seed(111)
gc = translate.geneticCode(rna=False)
reference_codon_dict1 = {}
reference_codon_dict2 = {}
for codon in translate.AADNACodons():
aa = gc[codon]
aa_codons = translate.getCodonsForAA(aa, rna=False)
# Sort in alphabetical order by reverse.
aa_codons.sort(key=lambda x: x[::-1])
reference_codon_dict1[codon] = aa_codons[0]
reference_codon_dict2[codon] = aa_codons[-1]
reference_codon_dict1['GCA'] = 'GCC'
reference_codon_dict2['GCA'] = 'GCT'
# Focus on alanine: GCN. Check if GCA->GCC + GCC->GCT = GCA->GCT
#reference_codon_dict[]
species = ['x', 'y']
prots = {
"dmel":
'MNKYGMVGVCLLAALGALLLEVTASPSS--AA-SSKVDPSQLGGLSAQFLPPEYRNTNVSIEDIKRIYREKCKKVNGADNATFYEEIERAAAKMSTCISGVVNLTALQEEMDVARPNGDLDTVFSKYCLKAPEAEACVKEFNDKAQHCLTPEEKRHQETVTRIGASVLGFACSRGGDQIALFIAEQGPECLEANKEAISNCLNQSFHQYIPKDGQVPDLMSRPELLFSPTHCVDLQRFEACVIHHLEQCTQITTANIVQSVFRFVKNETDCQAWMQARANEKPILMAASSNNTAPGLA-YS--LAGTL-----LGATILLILPMNKYGMVGVCLLAALGALLLEVTASPSS--AA-SSKVDPSQLGGLSAQFLPPEYRNTNVSIEDIKRIYREKCKKVNGADNATFYEEIERAAAKMSTCISGVVNLTALQEEMDVARPNGDLDTVFSKYCLKAPEAEACVKEFNDKAQHCLTPEEKRHQETVTRIGASVLGFACSRGGDQIALFIAEQGPECLEANKEAISNCLNQSFHQYIPKDGQVPDLMSRPELLFSPTHCVDLQRFEACVIHHLEQCTQITTANIVQSVFRFVKNETDCQAWMQARANEKPILMAASSNNTAPGLA-YS--LAGTL-----LGATILLILP',
#"dere":'MNKYGIVGVCLLAALGALLLEVTADS-----A-SPKLDPSQLGGLSAQFLPPEYRNTNVSIDDMKRIYREKCKKVNGADNATFYAEIERAAAKMSNCLNGVVNLTALQEEMDVAKPNGDLDTVFSKYCQKAPEAVACVKEFNEKAQHCLTAEEKRHQETVTRIGASVLGFACSRGGDQIALFIAEQGPECLEANKEAISNCLNQSFHQYIPKDGQVPDLMSRPELLFSPTHCVDLQRFESCVIHHLEQCTQITTANIVQSVFKFVKNETDCQSWMQARANEKPILLAASSNNTATGLA-YS--LAGPL-----LGATLLLMRP',
#"dana":'MHKYTLMGLCLMAALGAVLLEVNASPAG--VAIPTKLDPSQLGGLSAQFLPPEYRNTNVTVDDLKRLYREKCKKVTGADNSSFYEEIERAAAKMSNCISGVANLTAIQEEMEQAKPQGELDTVFHKYCQKAPEAEACVKEFNTKMQVCLTAEEKRHQETIARIGASLLGFACSRGGDQIALFVAEQGPECLDANKEAIANCLNQSFHNYIPKDGQVPDLMSAPELLFSPTHCVDLQRFESCVLHHLEQCSEITPANIVQSIFKFVKNETDCQAYMTARANEKPILMAAAGNSTGGGATGLTSHFGSLLAGIFASGLVLILNRY',
#"dyak":'MNKYGMVGVCLLAALGALLLEVTASPSSTGSA-STKLDPSQLGGLSAQFLPPEYRNTNVSIEDVKRIYREKCKKVNGADNATFYEEIERAAAKMSTCISGVVNLTALQEEMDVAKPNGDLDMVFSKYCQKAPQAEACVKEFNAKAQHCLTAEEKRHQETVTRIGASVLGFACSHGGDQI-------GPECLEANKEAISNCLNQSFHQYIPKDGQVPDLMSRPELLFSPTHCVDLQRFEACVVHHLEQCTQITTANIVQSVFRFVKNETDCQAWMQARANEKPILLAASGNNTATGLA-YS--LAGPL-----LGATMLLMRP'}
"dyak":
'XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXQHCLTAEEKRHQETVTRIGASVLGFACSHGGDQI-------GPECLEANKEAISNCLNQSFHQYIPKDGQVPDLMSRPELLFSPTHCVDLQRFEACVVHHLEQCTQITTANIVQSVFRFVKNETDCQAWMQARANEKPILLAASGNNTATGLA-YS--LAGPL-----LGATMLLMRPMNKYGMVGVCLLAALGALLLEVTASPSS--AA-SSKVDPSQLGGLSAQFLPPEYRNTNVSIEDIKRIYREKCKKVNGADNATFYEEIERAAAKMSTCISGVVNLTALQEEMDVARPNGDLDTVFSKYCLKAPEAEACVKEFNDKAQHCLTPEEKRHQETVTRXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX-XX--XXXXX-----XXXXXXXXXX'
}
genes = {
"dmel":
"ATGAACAAGTACGGGATGGTCGGCGTCTGCCTACTGGCTGCTCTGGGCGCTCTGCTCCTGGAGGTCACTGCCTCTCCTTCGTCCGCCGCCTCGTCTAAGGTGGATCCTAGCCAACTTGGCGGACTTTCAGCTCAGTTCTTGCCACCCGAGTACCGCAACACGAACGTTAGCATCGAGGATATAAAAAGAATATATCGTGAAAAATGCAAGAAGGTAAATGGAGCGGACAACGCAACCTTCTACGAAGAAATCGAGCGGGCGGCAGCCAAGATGAGCACCTGCATCAGCGGGGTGGTCAATCTGACGGCTCTGCAGGAGGAGATGGATGTGGCGAGGCCGAACGGCGACTTGGACACCGTGTTTAGCAAATACTGTCTCAAGGCACCGGAGGCAGAGGCCTGCGTCAAGGAGTTCAACGACAAGGCGCAGCATTGCTTGACCCCCGAGGAGAAGCGCCACCAGGAGACGGTTACCCGAATTGGAGCGTCCGTTTTGGGATTCGCCTGTTCGCGTGGCGGCGATCAGATTGCCCTCTTCATTGCCGAGCAGGGACCCGAGTGCCTGGAGGCCAACAAGGAAGCCATTAGCAATTGCCTCAATCAATCCTTTCATCAGTACATTCCCAAGGATGGCCAAGTTCCGGACCTGATGAGCCGCCCAGAGCTCCTTTTCTCACCCACCCACTGCGTGGACCTGCAGCGCTTCGAGGCCTGTGTCATCCATCATTTGGAGCAGTGCACGCAGATCACCACCGCTAATATCGTTCAGTCCGTCTTCCGTTTCGTGAAGAACGAGACCGACTGCCAGGCTTGGATGCAGGCACGTGCGAACGAGAAGCCCATTCTGATGGCCGCCTCCAGCAACAACACAGCCCCTGGACTCGCCTACTCCCTGGCCGGCACTCTTTTGGGCGCCACAATACTCCTGATACTCCCCTGAATGAACAAGTACGGGATGGTCGGCGTCTGCCTACTGGCTGCTCTGGGCGCTCTGCTCCTGGAGGTCACTGCCTCTCCTTCGTCCGCCGCCTCGTCTAAGGTGGATCCTAGCCAACTTGGCGGACTTTCAGCTCAGTTCTTGCCACCCGAGTACCGCAACACGAACGTTAGCATCGAGGATATAAAAAGAATATATCGTGAAAAATGCAAGAAGGTAAATGGAGCGGACAACGCAACCTTCTACGAAGAAATCGAGCGGGCGGCAGCCAAGATGAGCACCTGCATCAGCGGGGTGGTCAATCTGACGGCTCTGCAGGAGGAGATGGATGTGGCGAGGCCGAACGGCGACTTGGACACCGTGTTTAGCAAATACTGTCTCAAGGCACCGGAGGCAGAGGCCTGCGTCAAGGAGTTCAACGACAAGGCGCAGCATTGCTTGACCCCCGAGGAGAAGCGCCACCAGGAGACGGTTACCCGAATTGGAGCGTCCGTTTTGGGATTCGCCTGTTCGCGTGGCGGCGATCAGATTGCCCTCTTCATTGCCGAGCAGGGACCCGAGTGCCTGGAGGCCAACAAGGAAGCCATTAGCAATTGCCTCAATCAATCCTTTCATCAGTACATTCCCAAGGATGGCCAAGTTCCGGACCTGATGAGCCGCCCAGAGCTCCTTTTCTCACCCACCCACTGCGTGGACCTGCAGCGCTTCGAGGCCTGTGTCATCCATCATTTGGAGCAGTGCACGCAGATCACCACCGCTAATATCGTTCAGTCCGTCTTCCGTTTCGTGAAGAACGAGACCGACTGCCAGGCTTGGATGCAGGCACGTGCGAACGAGAAGCCCATTCTGATGGCCGCCTCCAGCAACAACACAGCCCCTGGACTCGCCTACTCCCTGGCCGGCACTCTTTTGGGCGCCACAATACTCCTGATACTCCCCTGA",
"dyak":
"ATGAACAAGTACGGGATGGTTGGCGTTTGCCTACTGGCTGCTCTGGGCGCTCTGCTCCTGGAGGTCACCGCCTCTCCTTCGTCCACCGGCTCGGCGAGTACCAAGCTGGATCCCAGCCAGCTAGGCGGACTTTCGGCCCAGTTCTTACCGCCCGAGTACCGCAACACGAACGTTAGCATCGAGGACGTTAAAAGAATATATCGTGAAAAATGCAAGAAGGTTAATGGAGCGGACAACGCGACCTTCTACGAGGAAATCGAGCGGGCGGCCGCGAAGATGAGCACCTGCATCAGCGGAGTGGTCAACCTGACGGCTCTGCAGGAGGAGATGGATGTGGCCAAGCCGAACGGCGACCTGGACATGGTGTTTAGCAAGTACTGCCAGAAGGCACCGCAGGCGGAGGCCTGTGTCAAGGAGTTCAACGCCAAGGCCCAGCATTGCTTGACCGCCGAGGAGAAGCGCCACCAGGAGACGGTCACCCGCATTGGAGCGTCCGTTCTGGGCTTCGCCTGCTCGCATGGTGGCGATCAGATTGGACCCGAGTGCCTGGAGGCCAACAAGGAGGCCATAAGCAATTGCCTCAACCAATCCTTCCATCAGTACATTCCCAAGGATGGCCAAGTTCCGGACCTGATGAGCCGCCCAGAACTCCTGTTCTCGCCCACCCACTGCGTGGACCTGCAGCGCTTCGAGGCGTGTGTCGTCCATCATTTGGAACAGTGCACCCAGATCACAACCGCCAACATCGTTCAGTCCGTCTTCCGCTTCGTGAAGAACGAGACCGACTGCCAGGCTTGGATGCAGGCTCGTGCCAACGAGAAGCCCATCCTGCTGGCCGCCTCCGGCAACAATACAGCCACTGGACTCGCCTACTCTCTGGCCGGCCCTCTCTTGGGCGCCACAATGCTCCTGATGCGCCCCTGAATGAACAAGTACGGGATGGTTGGCGTTTGCCTACTGGCTGCTCTGGGCGCTCTGCTCCTGGAGGTCACCGCCTCTCCTTCGTCCACCGGCTCGGCGAGTACCAAGCTGGATCCCAGCCAGCTAGGCGGACTTTCGGCCCAGTTCTTACCGCCCGAGTACCGCAACACGAACGTTAGCATCGAGGACGTTAAAAGAATATATCGTGAAAAATGCAAGAAGGTTAATGGAGCGGACAACGCGACCTTCTACGAGGAAATCGAGCGGGCGGCCGCGAAGATGAGCACCTGCATCAGCGGAGTGGTCAACCTGACGGCTCTGCAGGAGGAGATGGATGTGGCCAAGCCGAACGGCGACCTGGACATGGTGTTTAGCAAGTACTGCCAGAAGGCACCGCAGGCGGAGGCCTGTGTCAAGGAGTTCAACGCCAAGGCCCAGCATTGCTTGACCGCCGAGGAGAAGCGCCACCAGGAGACGGTCACCCGCATTGGAGCGTCCGTTCTGGGCTTCGCCTGCTCGCATGGTGGCGATCAGATTGGACCCGAGTGCCTGGAGGCCAACAAGGAGGCCATAAGCAATTGCCTCAACCAATCCTTCCATCAGTACATTCCCAAGGATGGCCAAGTTCCGGACCTGATGAGCCGCCCAGAACTCCTGTTCTCGCCCACCCACTGCGTGGACCTGCAGCGCTTCGAGGCGTGTGTCGTCCATCATTTGGAACAGTGCACCCAGATCACAACCGCCAACATCGTTCAGTCCGTCTTCCGCTTCGTGAAGAACGAGACCGACTGCCAGGCTTGGATGCAGGCTCGTGCCAACGAGAAGCCCATCCTGCTGGCCGCCTCCGGCAACAATACAGCCACTGGACTCGCCTACTCTCTGGCCGGCCCTCTCTTGGGCGCCACAATGCTCCTGATGCGCCCCTGA"
}
#algenes = dict([(s,muscle.alignGeneFromProtein(genes[s], prots[s])) for s in species])
species = ['x', 'y']
prot1 = randomProtein(1000)
prot2 = mutProtein(prot1)
prots = {"x": prot1, "y": prot2}
algenes = dict([(s,
translate.randomReverseTranslate(prots[s],
bad_codon='---'))
for s in species])
#print algenes
gene_codon_tables1 = cai.getAkashi2x2TablesForORFRefCodon(
cai.conservedAA,
reference_codon_dict1,
algenes['x'],
prots['x'], [algenes['y']], [prots['y']],
pseudocount=0,
n_terminal_start=0)
gene_codon_tables2 = cai.getAkashi2x2TablesForORFRefCodon(
cai.conservedAA,
reference_codon_dict2,
algenes['x'],
prots['x'], [algenes['y']], [prots['y']],
pseudocount=0,
n_terminal_start=0)
#print gene_codon_tables1
eps = 1e-6
#for aa in translate.degenerateAAs():
# for codon in translate.getCodonsForAA(aa):
for codon in ['GCA']:
ref_codon1 = reference_codon_dict1[codon]
ref_codon2 = reference_codon_dict2[codon]
self.assertTrue(gc[codon] == gc[ref_codon1])
self.assertTrue(gc[codon] == gc[ref_codon2])
# codon to ref_codon1
mh_res1 = stats.MantelHaenszelOddsRatioVariance(
gene_codon_tables1[codon])
sc_1_to_r1 = -mh_res1.ln_odds_ratio
# ref_codon1 to ref_codon2
mh_res2 = stats.MantelHaenszelOddsRatioVariance(
gene_codon_tables2[ref_codon1])
sc_r1_to_r2 = -mh_res2.ln_odds_ratio
# codon to ref_codon2
mh_res3 = stats.MantelHaenszelOddsRatioVariance(
gene_codon_tables2[codon])
sc_1_to_r2 = -mh_res3.ln_odds_ratio
# prediction from additivity
pred_sc_1_to_r2 = sc_1_to_r1 + sc_r1_to_r2
#print "{0}->{1} = {2}".format(codon, ref_codon1, sc_1_to_r1)
#print "{0}->{1} = {2}".format(ref_codon1, ref_codon2, sc_r1_to_r2)
#print "{0}->{1} = {2}".format(codon, ref_codon2, sc_1_to_r2)
#, ref_codon2, sc_1_to_r1, sc_r1_to_r2, sc_1_to_r2, pred_sc_1_to_r2
self.assertTrue(abs(sc_1_to_r2 - pred_sc_1_to_r2) < eps)
for (hdr,seq) in zip(headers,seqs):
seq = seq.replace(' ','')
seq = seq.replace('-','')
(name, props) = parseHeader(hdr)
mutantof = None
try:
mutantof = props['mutant.of']
baseseq = sug_dict[mutantof]
dnaseq = makeMutantFromSequence(seq, baseseq)
#print "Used suggestion"
except KeyError:
if not mutantof is None:
raise Exception, "Asked to make mutant of {} but sequence not found in suggestions".format(mutantof)
dnaseq = translate.randomReverseTranslate(seq)
#dnaseq = translate.reverseTranslate(seq)
assert(translate.translate(dnaseq)==seq)
fullseq = options.prefix + dnaseq + options.suffix
mutant_seqs[name] = (dnaseq, fullseq)
#name = biofile.firstField(hdr)
line = "{name:s}\t{dna:s}\tL={length:d}bp, {desc:s}\n".format(name=name, dna=fullseq, length=len(fullseq), desc=hdr)
data_outs.write(line)
n_written += 1
data_outs.write("\n\n# Confirmation details:\n")
for (hdr,seq) in zip(headers,seqs):
(name, props) = parseHeader(hdr)
(mutant_seq, fullseq) = mutant_seqs[name]
prot = translate.translate(mutant_seq)
fullprots = [translate.translateRaw(fullseq[i:]) for i in range(3)]
