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psl.py
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psl.py
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# Copyright 2022 by Michiel de Hoon. All rights reserved.
#
# This file is part of the Biopython distribution and governed by your
# choice of the "Biopython License Agreement" or the "BSD 3-Clause License".
# Please see the LICENSE file that should have been included as part of this
# package.
"""Bio.Align support for the "psl" pairwise alignment format.
The Pattern Space Layout (PSL) format, described by UCSC, stores a series
of pairwise alignments in a single file. Typically they are used for
transcript to genome alignments. PSL files store the alignment positions
and alignment scores, but do not store the aligned sequences.
See http://genome.ucsc.edu/FAQ/FAQformat.html#format2
You are expected to use this module via the Bio.Align functions.
Coordinates in the PSL format are defined in terms of zero-based start
positions (like Python) and aligning region sizes.
A minimal aligned region of length one and starting at first position in the
source sequence would have ``start == 0`` and ``size == 1``.
As we can see in this example, ``start + size`` will give one more than the
zero-based end position. We can therefore manipulate ``start`` and
``start + size`` as python list slice boundaries.
"""
from itertools import chain
import numpy as np
from Bio.Align import Alignment
from Bio.Align import interfaces
from Bio.Seq import Seq, reverse_complement, UndefinedSequenceError
from Bio.SeqRecord import SeqRecord
from Bio.SeqFeature import SeqFeature, ExactPosition, SimpleLocation, CompoundLocation
class AlignmentWriter(interfaces.AlignmentWriter):
"""Alignment file writer for the Pattern Space Layout (PSL) file format."""
fmt = "PSL"
def __init__(self, target, header=True, mask=None, wildcard="N"):
"""Create an AlignmentWriter object.
Arguments:
- target - output stream or file name
- header - If True (default), write the PSL header consisting of
five lines containing the PSL format version and a
header for each column.
If False, suppress the PSL header, resulting in a simple
tab-delimited file.
- mask - Specify if repeat regions in the target sequence are
masked and should be reported in the `repMatches` field
of the PSL file instead of in the `matches` field.
Acceptable values are
None : no masking (default);
"lower": masking by lower-case characters;
"upper": masking by upper-case characters.
- wildcard - Report alignments to the wildcard character in the
target or query sequence in the `nCount` field of the
PSL file instead of in the `matches`, `misMatches`, or
`repMatches` fields.
Default value is 'N'.
"""
super().__init__(target)
self.header = header
if wildcard is not None:
if mask == "upper":
wildcard = ord(wildcard.lower())
else:
wildcard = ord(wildcard.upper())
self.wildcard = wildcard
self.mask = mask
def write_header(self, stream, alignments):
"""Write the PSL header."""
if not self.header:
return
try:
metadata = alignments.metadata
except AttributeError:
version = "3"
else:
version = metadata.get("psLayout version", "3")
# fmt: off
stream.write(
f"""\
psLayout version {version}
match mis- rep. N's Q gap Q gap T gap T gap strand Q Q Q Q T T T T block blockSizes qStarts tStarts
match match count bases count bases name size start end name size start end count
---------------------------------------------------------------------------------------------------------------------------------------------------------------
""" # noqa: W191, E101
)
# fmt: on
def format_alignment(self, alignment):
"""Return a string with a single alignment formatted as one PSL line."""
if not isinstance(alignment, Alignment):
raise TypeError("Expected an Alignment object")
coordinates = alignment.coordinates
if not coordinates.size: # alignment consists of gaps only
return ""
target, query = alignment.sequences
try:
qName = query.id
except AttributeError:
qName = "query"
try:
query = query.seq
except AttributeError:
pass
try:
tName = target.id
except AttributeError:
tName = "target"
try:
target = target.seq
except AttributeError:
pass
tSize = len(target)
qSize = len(query)
steps = abs(np.diff(coordinates, 1))
aligned = steps.min(0) > 0
tCount, qCount = steps[:, aligned].sum(1)
if tCount == qCount:
dnax = False
if coordinates[0, 0] > coordinates[0, -1]:
coordinates = coordinates[:, ::-1]
if coordinates[1, 0] > coordinates[1, -1]:
# DNA/RNA mapped to reverse strand of DNA/RNA
strand = "-"
query = reverse_complement(query)
coordinates = coordinates.copy()
coordinates[1, :] = qSize - coordinates[1, :]
else:
# mapped to forward strand
strand = "+"
elif tCount == 3 * qCount:
dnax = True
if coordinates[0, 0] > coordinates[0, -1]:
# protein mapped to reverse strand of DNA
strand = "-"
target = reverse_complement(target)
coordinates = coordinates.copy()
coordinates[0, :] = tSize - coordinates[0, :]
else:
# mapped to forward strand
strand = "+"
else:
raise ValueError("inconsistent step sizes %d, %d" % (tCount, qCount))
# fmt: on
wildcard = self.wildcard
mask = self.mask
# variable names follow those in the PSL file format specification
matches = 0
misMatches = 0
repMatches = 0
nCount = 0
qNumInsert = 0
qBaseInsert = 0
tNumInsert = 0
tBaseInsert = 0
blockSizes = []
qStarts = []
tStarts = []
tStart, qStart = coordinates[:, 0]
for tEnd, qEnd in coordinates[:, 1:].transpose():
if tStart == tEnd:
if qStart > 0 and qEnd < qSize:
qNumInsert += 1
qBaseInsert += qEnd - qStart
qStart = qEnd
elif qStart == qEnd:
if tStart > 0 and tEnd < tSize:
tNumInsert += 1
tBaseInsert += tEnd - tStart
tStart = tEnd
else:
tCount = tEnd - tStart
qCount = qEnd - qStart
tStarts.append(tStart)
qStarts.append(qStart)
blockSizes.append(qCount)
if tCount == qCount:
assert dnax is False
else:
# translated DNA aligned to protein, typically generated by
# blat -t=dnax -q=prot
assert tCount == 3 * qCount
assert dnax is True
tSeq = target[tStart:tEnd]
qSeq = query[qStart:qEnd]
try:
tSeq = bytes(tSeq)
except TypeError: # string
tSeq = bytes(tSeq, "ASCII")
except UndefinedSequenceError: # sequence contents is unknown
tSeq = None
try:
qSeq = bytes(qSeq)
except TypeError: # string
qSeq = bytes(qSeq, "ASCII")
except UndefinedSequenceError: # sequence contents is unknown
qSeq = None
if tSeq is None or qSeq is None:
# contents of at least one sequence is unknown;
# count all aligned letters as matches:
matches += qCount
else:
if mask == "lower":
for u1, u2, c1 in zip(tSeq.upper(), qSeq.upper(), tSeq):
if u1 == wildcard or u2 == wildcard:
nCount += 1
elif u1 == u2:
if u1 == c1:
matches += 1
else:
repMatches += 1
else:
misMatches += 1
elif mask == "upper":
for u1, u2, c1 in zip(tSeq.lower(), qSeq.lower(), tSeq):
if u1 == wildcard or u2 == wildcard:
nCount += 1
elif u1 == u2:
if u1 == c1:
matches += 1
else:
repMatches += 1
else:
misMatches += 1
else:
for u1, u2 in zip(tSeq.upper(), qSeq.upper()):
if u1 == wildcard or u2 == wildcard:
nCount += 1
elif u1 == u2:
matches += 1
else:
misMatches += 1
tStart = tEnd
qStart = qEnd
try:
matches = alignment.matches
except AttributeError:
pass
try:
misMatches = alignment.misMatches
except AttributeError:
pass
try:
repMatches = alignment.repMatches
except AttributeError:
pass
try:
nCount = alignment.nCount
except AttributeError:
pass
tStart = tStarts[0] # start of alignment in target
qStart = qStarts[0] # start of alignment in query
tEnd = tStarts[-1] + tCount # end of alignment in target
qEnd = qStarts[-1] + qCount # end of alignment in query
if strand == "-":
if dnax is True:
tStart, tEnd = tSize - tEnd, tSize - tStart
else:
qStart, qEnd = qSize - qEnd, qSize - qStart
blockCount = len(blockSizes)
blockSizes = ",".join(map(str, blockSizes)) + ","
qStarts = ",".join(map(str, qStarts)) + ","
tStarts = ",".join(map(str, tStarts)) + ","
if dnax:
strand = "+" + strand
words = [
str(matches),
str(misMatches),
str(repMatches),
str(nCount),
str(qNumInsert),
str(qBaseInsert),
str(tNumInsert),
str(tBaseInsert),
strand,
qName,
str(qSize),
str(qStart),
str(qEnd),
tName,
str(tSize),
str(tStart),
str(tEnd),
str(blockCount),
blockSizes,
qStarts,
tStarts,
]
line = "\t".join(words) + "\n"
return line
class AlignmentIterator(interfaces.AlignmentIterator):
"""Alignment iterator for Pattern Space Layout (PSL) files.
Each line in the file contains one pairwise alignment, which are loaded
and returned incrementally. Alignment score information such as the number
of matches and mismatches are stored as attributes of each alignment.
"""
fmt = "PSL"
def _read_header(self, stream):
line = next(stream)
if line.startswith("psLayout "):
words = line.split()
if words[1] != "version":
raise ValueError("Unexpected word '%s' in header line" % words[1])
self.metadata = {"psLayout version": words[2]}
line = next(stream)
line = next(stream)
line = next(stream)
line = next(stream)
if line.lstrip("-").strip() != "":
raise ValueError("End of header not found")
else:
self._line = line
def _read_next_alignment(self, stream):
try:
line = self._line
except AttributeError:
lines = stream
else:
del self._line
lines = chain([line], stream)
for line in lines:
words = line.split()
if len(words) == 23:
pslx = True
elif len(words) == 21:
pslx = False
else:
raise ValueError("line has %d columns; expected 21 or 23" % len(words))
strand = words[8]
qName = words[9]
qSize = int(words[10])
tName = words[13]
tSize = int(words[14])
blockCount = int(words[17])
blockSizes = [
int(blockSize) for blockSize in words[18].rstrip(",").split(",")
]
qStarts = [int(start) for start in words[19].rstrip(",").split(",")]
tStarts = [int(start) for start in words[20].rstrip(",").split(",")]
if len(blockSizes) != blockCount:
raise ValueError(
"Inconsistent number of blocks (%d found, expected %d)"
% (len(blockSizes), blockCount)
)
if len(qStarts) != blockCount:
raise ValueError(
"Inconsistent number of query start positions (%d found, expected %d)"
% (len(qStarts), blockCount)
)
if len(tStarts) != blockCount:
raise ValueError(
"Inconsistent number of target start positions (%d found, expected %d)"
% (len(tStarts), blockCount)
)
qStarts = np.array(qStarts)
tStarts = np.array(tStarts)
qBlockSizes = np.array(blockSizes)
if strand in ("++", "+-"):
# protein sequence aligned against translated DNA sequence
tBlockSizes = 3 * qBlockSizes
else:
tBlockSizes = qBlockSizes
qPosition = qStarts[0]
tPosition = tStarts[0]
coordinates = [[tPosition, qPosition]]
for tBlockSize, qBlockSize, tStart, qStart in zip(
tBlockSizes, qBlockSizes, tStarts, qStarts
):
if tStart != tPosition:
coordinates.append([tStart, qPosition])
tPosition = tStart
if qStart != qPosition:
coordinates.append([tPosition, qStart])
qPosition = qStart
tPosition += tBlockSize
qPosition += qBlockSize
coordinates.append([tPosition, qPosition])
coordinates = np.array(coordinates).transpose()
qNumInsert = 0
qBaseInsert = 0
tNumInsert = 0
tBaseInsert = 0
tStart, qStart = coordinates[:, 0]
for tEnd, qEnd in coordinates[:, 1:].transpose():
tCount = tEnd - tStart
qCount = qEnd - qStart
if tCount == 0:
if qStart > 0 and qEnd < qSize:
qNumInsert += 1
qBaseInsert += qCount
qStart = qEnd
elif qCount == 0:
if tStart > 0 and tEnd < tSize:
tNumInsert += 1
tBaseInsert += tCount
tStart = tEnd
else:
tStart = tEnd
qStart = qEnd
if qNumInsert != int(words[4]):
raise ValueError(
"Inconsistent qNumInsert found (%s, expected %d)"
% (words[4], qNumInsert)
)
if qBaseInsert != int(words[5]):
raise ValueError(
"Inconsistent qBaseInsert found (%s, expected %d)"
% (words[5], qBaseInsert)
)
if tNumInsert != int(words[6]):
raise ValueError(
"Inconsistent tNumInsert found (%s, expected %d)"
% (words[6], tNumInsert)
)
if tBaseInsert != int(words[7]):
raise ValueError(
"Inconsistent tBaseInsert found (%s, expected %d)"
% (words[7], tBaseInsert)
)
qStart = int(words[11])
qEnd = int(words[12])
tStart = int(words[15])
tEnd = int(words[16])
if strand == "-":
qStart, qEnd = qEnd, qStart
coordinates[1, :] = qSize - coordinates[1, :]
elif strand == "+-":
tStart, tEnd = tEnd, tStart
coordinates[0, :] = tSize - coordinates[0, :]
if tStart != coordinates[0, 0]:
raise ValueError(
"Inconsistent tStart found (%d, expected %d)"
% (tStart, coordinates[0, 0])
)
if tEnd != coordinates[0, -1]:
raise ValueError(
"Inconsistent tEnd found (%d, expected %d)"
% (tEnd, coordinates[0, -1])
)
if qStart != coordinates[1, 0]:
raise ValueError(
"Inconsistent qStart found (%d, expected %d)"
% (qStart, coordinates[1, 0])
)
if qEnd != coordinates[1, -1]:
raise ValueError(
"Inconsistent qEnd found (%d, expected %d)"
% (qEnd, coordinates[1, -1])
)
feature = None
if pslx is True:
qSeqs = words[21].rstrip(",").split(",")
tSeqs = words[22].rstrip(",").split(",")
qSeq = dict(zip(qStarts, qSeqs))
if strand in ("++", "+-"):
# protein sequence aligned against translated DNA sequence
target_sequence = Seq(None, length=tSize)
query_sequence = Seq(qSeq, length=qSize)
if strand == "++":
tStart, qStart = coordinates[:, 0]
locations = []
for tEnd, qEnd in coordinates[:, 1:].transpose():
if qStart < qEnd and tStart < tEnd:
location = SimpleLocation(
ExactPosition(tStart),
ExactPosition(tEnd),
strand=+1,
)
locations.append(location)
qStart = qEnd
tStart = tEnd
if len(locations) > 1:
location = CompoundLocation(locations, "join")
tSeq = "".join(tSeqs)
qualifiers = {"translation": [tSeq]}
feature = SeqFeature(
location, type="CDS", qualifiers=qualifiers
)
elif strand == "+-":
tEnd, qStart = coordinates[:, 0]
locations = []
for tStart, qEnd in coordinates[:, 1:].transpose():
if qStart < qEnd and tStart < tEnd:
location = SimpleLocation(
ExactPosition(tStart),
ExactPosition(tEnd),
strand=-1,
)
locations.append(location)
tEnd = tStart
qStart = qEnd
if len(locations) > 1:
location = CompoundLocation(locations, "join")
tSeq = "".join(tSeqs)
qualifiers = {"translation": [tSeq]}
feature = SeqFeature(
location, type="CDS", qualifiers=qualifiers
)
else:
tSeq = dict(zip(tStarts, tSeqs))
target_sequence = Seq(tSeq, length=tSize)
query_sequence = Seq(qSeq, length=qSize)
if strand == "-":
query_sequence = query_sequence.reverse_complement()
else:
target_sequence = Seq(None, length=tSize)
query_sequence = Seq(None, length=qSize)
target_record = SeqRecord(target_sequence, id=tName, description="")
query_record = SeqRecord(query_sequence, id=qName, description="")
if feature is not None:
target_record.features.append(feature)
records = [target_record, query_record]
alignment = Alignment(records, coordinates)
alignment.matches = int(words[0])
alignment.misMatches = int(words[1])
alignment.repMatches = int(words[2])
alignment.nCount = int(words[3])
return alignment