sid = random.randint(0,1080)
dg = -2
gene = folder.getSequenceForStructure(sid, dg)
(new_sid, new_dg) = folder.fold(translate.Translate(gene))
assert(sid == new_sid and new_dg <= dg)
if False:
print "\n****\nTesting misfold module with compact lattice folder"
side_length = 5
struct_id = 599
target_fraction_accurate = 0.85
ca_cost = 5
max_free_energy = -5
prot_length = side_length*side_length
misfold.init(folder, prot_length, struct_id, max_free_energy, ca_cost, target_fraction_accurate, 111)
err_rate = misfold.getErrorRate()
gene = "ATTATTGTCTCGAAGGGTGCTATCTCCGCCGTCAGTTCCTTCGCAAAGTACATCTTCTTGCTTCTAACTAAAGAC"
(facc, frob, ftrunc, ffold) = misfold.calcOutcomes(gene);
print "%s\t%1.4f\t%1.4f\t%1.4f\t%1.4f" % ("calcOutcomes ", facc, frob, ftrunc, ffold)
(facc, frob, ftrunc, ffold) = misfold.countOutcomes(gene, 10000);
print "%s\t%d\t%d\t%d\t%d" % ("countOutcomes ", facc, frob, ftrunc, ffold)
(facc, frob, ftrunc, ffold) = misfold.countOutcomeFractions(gene, 10000);
print "%s\t%1.4f\t%1.4f\t%1.4f\t%1.4f" % ("countOutcomeFractions", facc, frob, ftrunc, ffold)
if False:
print "\n****\nTesting decoyfolder module"
sid = 1
prot_length = 300
log_nconf = 10*math.log(10)
map_file = os.path.abspath("test/data/williams_contact_maps/maps.txt")
map_dir = os.path.abspath("test/data/rand_contact_maps/")+"/"
decoyfolder.init(prot_length, log_nconf, map_file, map_dir)
print "sid dg"
p = "PRPEEEKKKREREEKRRKEDKLERIRDLPRKILKMIVEPKRRKKGETEDDDEKESKRREEMEKFKREFFTICIKLLECEEEMARRREKRREEEDIDSLRELMKDCRRFIDDPRRVEQQSQRLDFRSRRKLEDEKDDEDKRKPDFLFEFEMCEEDMRRRPLDRVKDICRVCCEMDEEEEIREEEEFFRPEEEDMKLKSFRESFKDVRRCILRKFEKSRREKSAEFLRHEIPMFSSEDEEDRKKKDRRRQRPMMRHFMKRIKEKEEERKKREFKEQEEPKPKSFKWKTEEEMEELGEQEKRV"
(sid, dg) = decoyfolder.fold(p)
print sid, dg
if True:
side_length = 5
struct_id = 599
target_fraction_accurate = 0.1
ca_cost = 4
max_free_energy = -5
misfold.init(side_length, struct_id, max_free_energy, ca_cost, target_fraction_accurate)
#print misfold.getErrorRate()
gene = "CCCCTGTACCGTACGACGAAATCTAACACTGGATCATGGCCTTCTGATTGGAAACCCCTACCTTATGAGTCAAAG"
#(facc, frob, ftrunc, ffold) = misfold.calcOutcomes(gene);
#print "%s\t%1.4f\t%1.4f\t%1.4f\t%1.4f" % ("mis", facc, frob, ftrunc, ffold)
if True:
f = file(os.path.expanduser('~/research/trsim/data/trs599ca4nmut-genes.txt'),'r')
for line in f.readlines()[2:]:
flds = line.strip().split('\t')
gene = flds[-1]
# print gene
#(facc, frob, ftrunc, ffold) = misfold.calcOutcomes(gene);
#print "%s\t%1.4f\t%1.4f\t%1.4f\t%1.4f" % (flds[0], facc, frob, ftrunc, ffold)
(facc, frob, ftrunc, ffold) = misfold.countOutcomes(gene, 1000);
print "%s\t%d\t%d\t%d\t%d" % (flds[0], facc, frob, ftrunc, ffold)
#print line,
sid = random.randint(0, 1080)
dg = -2
gene = folder.getSequenceForStructure(sid, dg)
(new_sid, new_dg) = folder.fold(translate.Translate(gene))
assert (sid == new_sid and new_dg <= dg)
if False:
print "\n****\nTesting misfold module with compact lattice folder"
side_length = 5
struct_id = 599
target_fraction_accurate = 0.85
ca_cost = 5
max_free_energy = -5
prot_length = side_length * side_length
misfold.init(folder, prot_length, struct_id, max_free_energy, ca_cost,
target_fraction_accurate, 111)
err_rate = misfold.getErrorRate()
gene = "ATTATTGTCTCGAAGGGTGCTATCTCCGCCGTCAGTTCCTTCGCAAAGTACATCTTCTTGCTTCTAACTAAAGAC"
(facc, frob, ftrunc, ffold) = misfold.calcOutcomes(gene)
print "%s\t%1.4f\t%1.4f\t%1.4f\t%1.4f" % ("calcOutcomes ", facc, frob,
ftrunc, ffold)
(facc, frob, ftrunc, ffold) = misfold.countOutcomes(gene, 10000)
print "%s\t%d\t%d\t%d\t%d" % ("countOutcomes ", facc, frob, ftrunc,
ffold)
(facc, frob, ftrunc, ffold) = misfold.countOutcomeFractions(gene, 10000)
print "%s\t%1.4f\t%1.4f\t%1.4f\t%1.4f" % ("countOutcomeFractions", facc,
frob, ftrunc, ffold)
if False:
print "\n****\nTesting decoyfolder module"
sid = 1
map_dir = os.path.abspath("test/data/rand_contact_maps/") + "/"
decoyfolder.init(prot_length, log_nconf, map_file, map_dir)
print "sid dg"
p = "PRPEEEKKKREREEKRRKEDKLERIRDLPRKILKMIVEPKRRKKGETEDDDEKESKRREEMEKFKREFFTICIKLLECEEEMARRREKRREEEDIDSLRELMKDCRRFIDDPRRVEQQSQRLDFRSRRKLEDEKDDEDKRKPDFLFEFEMCEEDMRRRPLDRVKDICRVCCEMDEEEEIREEEEFFRPEEEDMKLKSFRESFKDVRRCILRKFEKSRREKSAEFLRHEIPMFSSEDEEDRKKKDRRRQRPMMRHFMKRIKEKEEERKKREFKEQEEPKPKSFKWKTEEEMEELGEQEKRV"
(sid, dg) = decoyfolder.fold(p)
print sid, dg
if True:
side_length = 5
struct_id = 599
target_fraction_accurate = 0.1
ca_cost = 4
max_free_energy = -5
misfold.init(side_length, struct_id, max_free_energy, ca_cost,
target_fraction_accurate)
#print misfold.getErrorRate()
gene = "CCCCTGTACCGTACGACGAAATCTAACACTGGATCATGGCCTTCTGATTGGAAACCCCTACCTTATGAGTCAAAG"
#(facc, frob, ftrunc, ffold) = misfold.calcOutcomes(gene);
#print "%s\t%1.4f\t%1.4f\t%1.4f\t%1.4f" % ("mis", facc, frob, ftrunc, ffold)
if True:
f = file(
os.path.expanduser(
'~/research/trsim/data/trs599ca4nmut-genes.txt'), 'r')
for line in f.readlines()[2:]:
flds = line.strip().split('\t')
gene = flds[-1]
# print gene
#(facc, frob, ftrunc, ffold) = misfold.calcOutcomes(gene);
#print "%s\t%1.4f\t%1.4f\t%1.4f\t%1.4f" % (flds[0], facc, frob, ftrunc, ffold)
(facc, frob, ftrunc, ffold) = misfold.countOutcomes(gene, 1000)
