/usr/share/pyshared/cogent/parse/flowgram.py is in python-cogent 1.5.1-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 | #!/usr/bin/env python
"""A Flowgram object for 454 sequencing data."""
__author__ = "Jens Reeder, Julia Goodrich"
__copyright__ = "Copyright 2007-2011, The Cogent Project"
__credits__ = ["Jens Reeder","Julia Goodrich"]
__license__ = "GPL"
__version__ = "1.5.1"
__maintainer__ = "Jens Reeder"
__email__ = "jreeder@colorado.edu"
__status__ = "Development"
from copy import copy
from cogent.util.unit_test import FakeRandom
from cogent.core.sequence import Sequence
DEFAULT_FLOWORDER = "TACG"
DEFAULT_KEYSEQ = "TCAG"
class Flowgram(object):
"""Holds a 454 flowgram object"""
HeaderInfo = ["Run Prefix", "Region #","XY Location","Run Name",
"Analysis Name", "Full Path","Read Header Len","Name Length",
"# of Bases","Clip Qual Left","Clip Qual Right",
"Clip Adap Left","Clip Adap Right"]
FlowgramInfo = ['Flow Indexes','Bases','Quality Scores']
def __init__(self, flowgram = '', Name = None, KeySeq = DEFAULT_KEYSEQ,
floworder = DEFAULT_FLOWORDER, header_info = None):
"""Initialize a flowgram.
Arguments:
flowgram: the raw flowgram string, or list, no other type
guarenteed to work
as expected, default is ''
Name: the flowgram name
KeySeq: the 454 key sequence
floworder: flow sequence used to transform flowgram to sequence
"""
if Name is None and hasattr(flowgram, 'Name'):
Name = flowgram.Name
if Name is None and hasattr(flowgram, 'header_info'):
header_info = flowgram.header_info
self.Name = Name
if hasattr(flowgram, '_flowgram'):
flowgram = flowgram._flowgram
if isinstance(flowgram, str):
self._flowgram = ' '.join(flowgram.split())
if isinstance(flowgram, list):
self._flowgram = ' '.join(map(str, flowgram))
else:
self._flowgram = str(flowgram)
self.flowgram = map(float,self._flowgram.split())
self.keySeq = KeySeq
self.floworder = floworder
if header_info is not None:
for i in header_info:
setattr(self,i,header_info[i])
#Why do we store the information twice, once as attribute and once in header_info?
self.header_info = header_info
def __str__(self):
"""__str__ returns self._flowgram unmodified."""
return '\t'.join(self._flowgram.split())
def __len__(self):
"""returns the length of the flowgram"""
return len(self.flowgram)
def cmpSeqToString(self, other):
"""compares the flowgram's sequence to other which is a string
will first try to compare by self.Bases, then by self.toSeq"""
if hasattr(self,'Bases') and self.Bases == other:
return True
else:
return self.toSeq() == other
def cmpByName(self, other):
"""compares based on the name, other must also be a flowgram object"""
if self is other:
return 0
try:
return cmp(self.Name, other.Name)
except AttributeError:
return cmp(type(self), type(other))
def cmpBySeqs(self, other):
"""compares by the sequences they represent
other must also be a flowgram object
"""
if self is other:
return 0
try:
return cmp(self.Bases,other.Bases)
except AttributeError:
return cmp(self.toSeq(), other.toSeq())
def hasProperKey(self, keyseq=DEFAULT_KEYSEQ):
"""Checks for the proper key sequence"""
keylen = len(keyseq)
keyseq_from_flow = self.toSeq(truncate=False,
Bases=False)[:keylen]
return (keyseq_from_flow == keyseq)
def __cmp__(self, other):
"""compares flowgram to other which is a string or another flowgram"""
if isinstance(other, Flowgram):
other = other._flowgram
return cmp(self._flowgram, other)
def __iter__(self):
"""yields successive floats in flowgram"""
for f in self.flowgram:
yield f
def __hash__(self):
"""__hash__ behaves like the flowgram string for dict lookup."""
return hash(self._flowgram)
def __contains__(self, other):
"""__contains__ checks whether other is in the flowgram string."""
return other in self._flowgram
def toSeq(self, Bases=True, truncate=True):
"""Translates flowgram to sequence and returns sequence object
if Bases is True then a sequence object will be made using
self.Bases instead of translating the flowgram
truncate: if True strip off lowercase chars (low quality bases)
"""
if Bases and hasattr(self, "Bases"):
seq = self.Bases
else:
seq = []
if self.floworder is None:
raise ValueError, "must have self.floworder set"
key = FakeRandom(self.floworder,True)
flows_since_last = 0
for n in self.flowgram:
signal = int(round(n))
seq.extend([key()]* signal)
if (signal>0):
flows_since_last = 0
else:
flows_since_last += 1
if(flows_since_last ==4):
seq.extend('N')
flows_since_last=0
seq = ''.join(seq)
#cache the result for next time
self.Bases = seq
if(truncate):
seq = str(seq)
seq = seq.rstrip("acgtn")
seq = seq.lstrip("actgn")
return Sequence(seq, Name = self.Name)
def toFasta(self, make_seqlabel=None, LineWrap = 80):
"""Return string in FASTA format, no trailing newline
Will use self.Bases if it is set otherwise it will translate the
flowgram
Arguments:
- make_seqlabel: callback function that takes the seq object and
returns a label str
"""
if hasattr(self,'Bases'):
seq = self.toSeq(Bases = True)
else:
seq = self.toSeq()
seq.LineWrap = LineWrap
return seq.toFasta(make_seqlabel = make_seqlabel)
def getQualityTrimmedFlowgram(self):
"""Returns trimmed flowgram according to Clip Qual Right"""
flow_copy = copy(self)
if (hasattr(self, "Clip Qual Right") and hasattr(self, "Flow Indexes")):
clip_right = int(getattr(self, "Clip Qual Right"))
flow_indices = getattr(self, "Flow Indexes")
flow_indices = [int(k) for k in flow_indices.split('\t') if k != '']
clip_right_flowgram = flow_indices[clip_right-1]
#Truncate flowgram
flow_copy.flowgram = self.flowgram[:clip_right_flowgram]
flow_copy._flowgram =\
"\t".join(self._flowgram.split()[:clip_right_flowgram])
#Update attributes
if hasattr(flow_copy, "Quality Scores"):
qual_scores = getattr(flow_copy,"Quality Scores").split('\t')
setattr(flow_copy, "Quality Scores",
"\t".join(qual_scores[:clip_right]))
if hasattr(flow_copy, "Flow Indexes"):
setattr(flow_copy, "Flow Indexes",
"\t".join(map(str, flow_indices[:clip_right])))
if hasattr(flow_copy, "Bases"):
flow_copy.Bases = self.Bases[:clip_right]
if hasattr(flow_copy, "# of Bases"):
setattr(flow_copy, "# of Bases", clip_right)
return flow_copy
def getPrimerTrimmedFlowgram(self, primerseq):
"""Cuts the key and primer sequences of a flowgram.
primerseq: the primer seq to be truncated from flowgram
"""
if(primerseq==""):
return self
else:
flow_copy = copy(self)
#Key currently not reliable set by FlowgramCollection
#instead pass key as part of primer
#key = flow_copy.keySeq or ""
flow_indices = getattr(self, "Flow Indexes")
flow_indices = [int(k) for k in flow_indices.split('\t') if k != '']
#position of last primer char in flowgram
primer_len = len(primerseq)
pos = flow_indices[primer_len-1]
signal = flow_copy.flowgram[pos-1]
if (signal < 0.5):
#Flowgram is not consistent with primerseq
return None
elif (signal < 1.5):
pad_num = pos % 4
#we can simply cut off
flow_copy.flowgram = flow_copy.flowgram[pos:]
# and pad flowgram to the left to sync with floworder
flow_copy.flowgram[:0] = pad_num*[0.00]
#check that first 4 flows not are all zero
else:
pad_num = (pos-1)%4
# we are cutting within a signal, need to do some flowgram arithmetic
lastchar = primerseq[-1]
#get the position in the homopolyemer
pos_in_homopoly = len(primerseq) - len(primerseq.rstrip(lastchar))
flow_copy.flowgram = flow_copy.flowgram[pos-1:]
flow_copy.flowgram[0] = max(0.00, flow_copy.flowgram[0] - pos_in_homopoly)
#pad flowgram to the left to sync with floworder
flow_copy.flowgram[:0] = (pad_num)*[0.00]
# delete first flow cycle if all <0.5 (otherwise an N would be called)
if(any([sign>=0.5 for sign in flow_copy.flowgram[:4]])):
#We are ok
extra_shift=0
pass
else:
#we truncate the first 4 flows
flow_copy.flowgram = flow_copy.flowgram[4:]
extra_shift=4
#Update "Flow Indexes" attribute
#shift all flow indices by the deleted amount
# WARNING: this sets wrong flow indexes, so better set to nothing
# setattr(flow_copy, "Flow Indexes",
# "\t".join([ str(a-(pos+extra_shift)+pad_num) for a in\
# flow_indices[primer_len:]]))
setattr(flow_copy, "Flow Indexes", "")
#Update flowgram string representation
flow_copy._flowgram = "\t".join(map(lambda a:"%.2f"%a,
flow_copy.flowgram))
#Update "Quality Scores" attribute
if hasattr(self, "Quality Scores"):
qual_scores = getattr(flow_copy,"Quality Scores").split('\t')
setattr(flow_copy, "Quality Scores", "\t".join(qual_scores[primer_len:]))
#Update Bases attribute
if hasattr(flow_copy, "Bases"):
flow_copy.Bases = flow_copy.Bases[primer_len:]
#Update "# of Bases" attribute
if hasattr(flow_copy, "# of Bases"):
setattr(flow_copy, "# of Bases",
str(int(getattr(flow_copy, "# of Bases")) - (primer_len)))
if hasattr(flow_copy, "Clip Qual Left"):
setattr(flow_copy, "Clip Qual Left", str(max(0, int(getattr(flow_copy, "Clip Qual Left")) - primer_len)))
if hasattr(flow_copy, "Clip Qual Right"):
setattr(flow_copy, "Clip Qual Right", str(max(0, int(getattr(flow_copy, "Clip Qual Right")) - primer_len)))
if hasattr(flow_copy, "Clip Adap Left"):
setattr(flow_copy, "Clip Adap Left", str(max(0, int(getattr(flow_copy, "Clip Adap Left")) - primer_len)))
if hasattr(flow_copy, "Clip Adap Right"):
setattr(flow_copy, "Clip Adap Right", str(max(0, int(getattr(flow_copy, "Clip Adap Right")) - primer_len)))
return flow_copy
def createFlowHeader(self):
"""header_info dict turned into flowgram header"""
lines = [">%s\n"%self.Name]
flow_info = []
head_info = []
for i in self.FlowgramInfo:
if hasattr(self,i):
flow_info.append('%s:\t%s\n' %
(i, getattr(self, i)))
for i in self.HeaderInfo:
if hasattr(self,i):
head_info.append(' %s:\t%s\n' %
(i, getattr(self, i)))
lines.extend(head_info)
lines.extend(flow_info)
lines.append("Flowgram:\t%s" % str(self))
return (''.join(lines)+"\n")
def seq_to_flow(seq, id = None, keyseq = None, floworder = DEFAULT_FLOWORDER):
""" Transform a sequence into an ideal flow.
seq: sequence to transform to flowgram
id: identifier
keyseq
"""
complete_flow = floworder * len(seq) # worst case length
i = 0 # iterates over seq
j = 0 # iterates over the flow sequence tcagtcagtcag...
mask = ""
while (j < len(complete_flow) and i<len(seq)):
if(seq[i] == 'N'):
mask+="0.00 0.00 0.00 0.00"
i+=1
j+=4
continue
if (complete_flow[j] == seq[i]):
#check for more than one of this nuc
c = 1
i += 1
while(i < len(seq) and j < len(complete_flow)\
and complete_flow[j]==seq[i]):
i += 1
c += 1
mask += "%d" % c
if (i >= len(seq)):
break
j += 1
else:
mask += "0"
j += 1
# pad mask to finish the last flow to a multiple of the floworder length
if (len(mask) % len(floworder) != 0):
right_missing = len(floworder) - (len(mask) % len(floworder))
mask += "0" * right_missing
return Flowgram(map(float, mask), id, keyseq, floworder)
def build_averaged_flowgram(flowgrams):
"""Builds an averaged flowgram from a list of raw signals."""
result=[]
if(len(flowgrams)==1):
return flowgrams[0]
for tuple in map(None, *flowgrams):
k=0
sum=0
for element in tuple:
if (element!=None):
k+=1
sum +=element
result.append(round(sum/k,2))
return result
|