本文整理汇总了Python中TAMO.seq.Fasta.delN方法的典型用法代码示例。如果您正苦于以下问题：Python Fasta.delN方法的具体用法？Python Fasta.delN怎么用？Python Fasta.delN使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类TAMO.seq.Fasta的用法示例。
在下文中一共展示了Fasta.delN方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: __init__
# 需要导入模块: from TAMO.seq import Fasta [as 别名]
# 或者: from TAMO.seq.Fasta import delN [as 别名]
def __init__(self, fg_file, bg_file, cv_level, markov_file):
self.cv_level = cv_level
self.randomize = 0
self.beta = 0.0
self.delta = 0.001
self.refine = 1
self.motif_file = 'dummy.out'
self.dump = 0
self.family = ''
self.datafiles = (fg_file,bg_file)
MAX_FG = 2000
#LOAD MARKOV BACKGROUND#
print "Loading Markov background file from %s"%markov_file
EM.loadMarkovBackground(markov_file)
##################################################################################
#divide input sequences into groups according to the desired cross-validation level
###################################################################################
print "Processing input sequences...."
self.fg_seqs = Fasta.load(fg_file) #load foreground sequences
for key in self.fg_seqs.keys():
fseq = self.fg_seqs[key]
self.fg_seqs[key] = fseq.split()[0]
self.all_probes = Fasta.load(bg_file) #load background sequences
Fasta.delN(self.fg_seqs)
Fasta.delN(self.all_probes)
#first delete any sequences from background that are present in foreground
for key in self.fg_seqs.keys():
if (self.all_probes.has_key(key)):
del self.all_probes[key]
for key in self.all_probes.keys():
if ((len(self.all_probes[key])==0) or (re.search('[SWMKRY]', self.all_probes[key]))):
del self.all_probes[key]
print "deleting %s"%key
while (len(self.fg_seqs.keys())>MAX_FG):
del self.fg_seqs[self.fg_seqs.keys()[random.randint(0,(len(self.fg_seqs.keys())-1))]]示例2: main
# 需要导入模块: from TAMO.seq import Fasta [as 别名]
# 或者: from TAMO.seq.Fasta import delN [as 别名]
#.........这里部分代码省略.........
elif tok == '-gapweight':gapweight = float(sys.argv[i+1])
elif tok == '-enrichfact':enrichfact= float(sys.argv[i+1])
elif tok == '-pmax' : pmax = 1
elif tok == '-Y2K' : species = "YEAST_2000_UP"
elif tok == '-Y5C' : species = "YEAST_500_UP"
elif tok == '-B' : species = "BAC_ORF"
elif tok == '-Ch22' : species = "Ch22"
elif tok == '-genome': species = sys.argv[i+1]
elif tok == '-pad' : pad = "TRUE"
elif tok == '-bgfile': bgfile = sys.argv[i+1]
elif tok == '-TF' : #NOT USED (TRANSFAC NOT SUPPLIED WITH DISTRIBUTION)
TFSEEDS = 1
for j in range(i+1,len(sys.argv)):
if re.match('M0',sys.argv[j]):
TFMids.append(sys.argv[j])
else:
break
elif tok == '-human' :
_s = ''
if sys.argv[i+1].isdigit(): _s = '_'+sys.argv[i+1]
else: _s = ''
species = 'HUMAN'+_s
if infofile: infofile = fastafile
if bgfile:
EM.loadMarkovBackground(bgfile)
elif not ('-random_background' in sys.argv or '-nomarkov' in sys.argv):
EM.loadMarkovBackground(species)
else:
EM.theMarkovBackground = EM.Zeroth()
fsaD = Fasta.load(fastafile)
Fasta.delN(fsaD)
seqs = fsaD.values()
probes = fsaD.keys()
all_seqs = seqs
seed_s.extend(seqs[0:min(seed_count,len(seqs))])
if infofile and width=='info':
width = info2width(infofile)
elif width != None:
width = int(width)
#Alternate source of seeds
if infofile:
if 1 or width:
seedmodels.extend(info2seeds(width,infofile,fastafile,species))
else:
print 'Error: need to specify motif width w/ .info file'
#Any -prior pointers to motifs in other files?
(seed_s, motifs) = parse_priors(seed_s)
seedmodels.extend(motifs)
#Should we get seeds from TRANSFAC?
if TFSEEDS: #NOT USED
tf = []
D = tfmats()
if not TFMids:
keys = D.keys()
else:
keys = []
for TFMid in TFMids:
for key in D.keys():
if key[0:6] == TFMid: