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/
utils.py
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/
utils.py
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#################################################################################
# Copyright (c) 2011-2013, Pacific Biosciences of California, Inc.
#
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of Pacific Biosciences nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY
# THIS LICENSE. THIS SOFTWARE IS PROVIDED BY PACIFIC BIOSCIENCES AND ITS
# CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
# PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL PACIFIC BIOSCIENCES OR
# ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
# BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
# IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
#################################################################################
# Author: David Alexander
from __future__ import absolute_import
import math, numpy as np, os.path, sys, itertools
def die(msg):
print msg
sys.exit(-1)
class CommonEqualityMixin(object):
def __eq__(self, other):
return (isinstance(other, self.__class__)
and self.__dict__ == other.__dict__)
def __ne__(self, other):
return not self.__eq__(other)
# An exception for incompatible cmp.h5 files
class IncompatibleDataException(Exception):
pass
# We truncate QVs at 93 because the FASTQ format downstream can only
# support QVs in the range [0, 93] without lossage.
def error_probability_to_qv(error_probability, cap=93):
"""
Convert an error probability to a phred-scaled QV.
"""
if error_probability==0:
return cap
else:
return min(cap, int(round(-10*math.log10(error_probability))))
_complement = { "A" : "T",
"C" : "G",
"G" : "C",
"T" : "A",
"-" : "-" }
def complement(s):
cStr = "".join(_complement[c] for c in s)
if type(s) == str:
return cStr
else:
return np.fromstring(cStr, "S1")
def reverseComplement(s):
return complement(s)[::-1]
def fileFormat(filename):
if filename.endswith(".gz"):
ext = os.path.splitext(filename[:-3])[1]
else:
ext = os.path.splitext(filename)[1]
ext = ext.lower()
if ext in [".fa", ".fasta"]: return "FASTA"
elif ext in [".fq", ".fastq"]: return "FASTQ"
elif ext in [".gff" ]: return "GFF"
elif ext in [".csv" ]: return "CSV"
else: raise Exception, "Unrecognized file format"
def rowNumberIsInReadStratum(readStratum, rowNumber):
n, N = readStratum
return (rowNumber % N) == n
def readsInWindow(cmpH5, window, depthLimit=None,
minMapQV=0, strategy="fileorder",
stratum=None, barcode=None):
"""
Return up to `depthLimit` reads (as row numbers integers) where
the mapped reference intersects the window. If depthLimit is None,
return all the reads meeting the criteria.
`strategy` can be:
- "longest" --- get the reads with the longest length in the window
- "spanning" --- get only the reads spanning the window
- "fileorder" --- get the reads in file order
"""
assert strategy in {"longest", "spanning", "fileorder"}
if stratum is not None:
raise ValueError, "stratum needs to be reimplemented"
def depthCap(iter):
if depthLimit is not None:
return list(itertools.islice(iter, 0, depthLimit))
else:
return list(iter)
def lengthInWindow(hit):
return min(hit.tEnd, winEnd) - max(hit.tStart, winStart)
winId, winStart, winEnd = window
if barcode == None:
alnHits = ( hit
for hit in cmpH5.readsInRange(winId, winStart, winEnd)
if hit.MapQV >= minMapQV )
else:
alnHits = ( hit
for hit in cmpH5.readsInRange(winId, winStart, winEnd)
if ((hit.MapQV >= minMapQV) and
(hit.barcode == barcode)) )
if strategy == "fileorder":
return depthCap(alnHits)
elif strategy == "spanning":
winLen = winEnd - winStart
return depthCap( hit for hit in alnHits
if lengthInWindow(hit) == winLen )
elif strategy == "longest":
# Well, this defeats the iterable/laziness, performs poorly if
# deep coverage. sorted is stable.
return depthCap(sorted(alnHits, key=lengthInWindow, reverse=True))
def datasetCountExceedsThreshold(cmpH5, threshold):
"""
Does the file contain more than `threshold` datasets? This
impacts whether or not we should disable the chunk cache.
"""
total = 0
for i in np.unique(cmpH5.AlnGroupID):
total += len(cmpH5._alignmentGroup(i))
if total > threshold:
return True
return False
#
# Some lisp functions we want
#
fst = lambda t: t[0]
snd = lambda t: t[1]
third = lambda t: t[2]
def nub(it):
"""
Unique entries in an iterable, preserving order
"""
seen = set()
for x in it:
if x not in seen: yield(x)
seen.add(x)