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All rights reserved.
# This code is part of the Biopython distribution and governed by its
# license. Please see the LICENSE file that should have been included
# as part of this package.
#
# This module is for reading and writing FASTQ and QUAL format files as
# SeqRecord objects, and is expected to be used via the Bio.SeqIO API.
"""Bio.SeqIO support for the FASTQ and QUAL file formats.
Note that you are expected to use this code via the Bio.SeqIO interface, as
shown below.
The FASTQ file format is used frequently at the Wellcome Trust Sanger Institute
to bundle a FASTA sequence and its PHRED quality data (integers between 0 and
90). Rather than using a single FASTQ file, often paired FASTA and QUAL files
are used containing the sequence and the quality information separately.
The PHRED software reads DNA sequencing trace files, calls bases, and
assigns a non-negative quality value to each called base using a logged
transformation of the error probability, Q = -10 log10( Pe ), for example::
Pe = 1.0, Q = 0
Pe = 0.1, Q = 10
Pe = 0.01, Q = 20
...
Pe = 0.00000001, Q = 80
Pe = 0.000000001, Q = 90
In typical raw sequence reads, the PHRED quality valuea will be from 0 to 40.
In the QUAL format these quality values are held as space separated text in
a FASTA like file format. In the FASTQ format, each quality values is encoded
with a single ASCI character using chr(Q+33), meaning zero maps to the
character "!" and for example 80 maps to "q". For the Sanger FASTQ standard
the allowed range of PHRED scores is 0 to 93 inclusive. The sequences and
quality are then stored in pairs in a FASTA like format.
Unfortunately there is no official document describing the FASTQ file format,
and worse, several related but different variants exist. For more details,
please read this open access publication::
The Sanger FASTQ file format for sequences with quality scores, and the
Solexa/Illumina FASTQ variants.
P.J.A.Cock (Biopython), C.J.Fields (BioPerl), N.Goto (BioRuby),
M.L.Heuer (BioJava) and P.M. Rice (EMBOSS).
Nucleic Acids Research 2010 38(6):1767-1771
http://dx.doi.org/10.1093/nar/gkp1137
The good news is that Roche 454 sequencers can output files in the QUAL format,
and sensibly they use PHREP style scores like Sanger. Converting a pair of
FASTA and QUAL files into a Sanger style FASTQ file is easy. To extract QUAL
files from a Roche 454 SFF binary file, use the Roche off instrument command
line tool "sffinfo" with the -q or -qual argument. You can extract a matching
FASTA file using the -s or -seq argument instead.
The bad news is that Solexa/Illumina did things differently - they have their
own scoring system AND their own incompatible versions of the FASTQ format.
Solexa/Illumina quality scores use Q = - 10 log10 ( Pe / (1-Pe) ), which can
be negative. PHRED scores and Solexa scores are NOT interchangeable (but a
reasonable mapping can be achieved between them, and they are approximately
equal for higher quality reads).
Confusingly early Solexa pipelines produced a FASTQ like file but using their
own score mapping and an ASCII offset of 64. To make things worse, for the
Solexa/Illumina pipeline 1.3 onwards, they introduced a third variant of the
FASTQ file format, this time using PHRED scores (which is more consistent) but
with an ASCII offset of 64.
i.e. There are at least THREE different and INCOMPATIBLE variants of the FASTQ
file format: The original Sanger PHRED standard, and two from Solexa/Illumina.
The good news is that as of CASAVA version 1.8, Illumina sequencers will
produce FASTQ files using the standard Sanger encoding.
You are expected to use this module via the Bio.SeqIO functions, with the
following format names:
- "qual" means simple quality files using PHRED scores (e.g. from Roche 454)
- "fastq" means Sanger style FASTQ files using PHRED scores and an ASCII
offset of 33 (e.g. from the NCBI Short Read Archive and Illumina 1.8+).
These can potentially hold PHRED scores from 0 to 93.
- "fastq-sanger" is an alias for "fastq".
- "fastq-solexa" means old Solexa (and also very early Illumina) style FASTQ
files, using Solexa scores with an ASCII offset 64. These can hold Solexa
scores from -5 to 62.
- "fastq-illumina" means newer Illumina 1.3 to 1.7 style FASTQ files, using
PHRED scores but with an ASCII offset 64, allowing PHRED scores from 0
to 62.
We could potentially add support for "qual-solexa" meaning QUAL files which
contain Solexa scores, but thus far there isn't any reason to use such files.
For example, consider the following short FASTQ file::
@EAS54_6_R1_2_1_413_324
CCCTTCTTGTCTTCAGCGTTTCTCC
+
;;3;;;;;;;;;;;;7;;;;;;;88
@EAS54_6_R1_2_1_540_792
TTGGCAGGCCAAGGCCGATGGATCA
+
;;;;;;;;;;;7;;;;;-;;;3;83
@EAS54_6_R1_2_1_443_348
GTTGCTTCTGGCGTGGGTGGGGGGG
+
;;;;;;;;;;;9;7;;.7;393333
This contains three reads of length 25. From the read length these were
probably originally from an early Solexa/Illumina sequencer but this file
follows the Sanger FASTQ convention (PHRED style qualities with an ASCII
offet of 33). This means we can parse this file using Bio.SeqIO using
"fastq" as the format name:
>>> from Bio import SeqIO
>>> for record in SeqIO.parse("Quality/example.fastq", "fastq"):
... print record.id, record.seq
EAS54_6_R1_2_1_413_324 CCCTTCTTGTCTTCAGCGTTTCTCC
EAS54_6_R1_2_1_540_792 TTGGCAGGCCAAGGCCGATGGATCA
EAS54_6_R1_2_1_443_348 GTTGCTTCTGGCGTGGGTGGGGGGG
The qualities are held as a list of integers in each record's annotation:
>>> print record
ID: EAS54_6_R1_2_1_443_348
Name: EAS54_6_R1_2_1_443_348
Description: EAS54_6_R1_2_1_443_348
Number of features: 0
Per letter annotation for: phred_quality
Seq('GTTGCTTCTGGCGTGGGTGGGGGGG', SingleLetterAlphabet())
>>> print record.letter_annotations["phred_quality"]
[26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 24, 26, 22, 26, 26, 13, 22, 26, 18, 24, 18, 18, 18, 18]
You can use the SeqRecord format method to show this in the QUAL format:
>>> print record.format("qual")
>EAS54_6_R1_2_1_443_348
26 26 26 26 26 26 26 26 26 26 26 24 26 22 26 26 13 22 26 18
24 18 18 18 18
<BLANKLINE>
Or go back to the FASTQ format, use "fastq" (or "fastq-sanger"):
>>> print record.format("fastq")
@EAS54_6_R1_2_1_443_348
GTTGCTTCTGGCGTGGGTGGGGGGG
+
;;;;;;;;;;;9;7;;.7;393333
<BLANKLINE>
Or, using the Illumina 1.3+ FASTQ encoding (PHRED values with an ASCII offset
of 64):
>>> print record.format("fastq-illumina")
@EAS54_6_R1_2_1_443_348
GTTGCTTCTGGCGTGGGTGGGGGGG
+
ZZZZZZZZZZZXZVZZMVZRXRRRR
<BLANKLINE>
You can also get Biopython to convert the scores and show a Solexa style
FASTQ file:
>>> print record.format("fastq-solexa")
@EAS54_6_R1_2_1_443_348
GTTGCTTCTGGCGTGGGTGGGGGGG
+
ZZZZZZZZZZZXZVZZMVZRXRRRR
<BLANKLINE>
Notice that this is actually the same output as above using "fastq-illumina"
as the format! The reason for this is all these scores are high enough that
the PHRED and Solexa scores are almost equal. The differences become apparent
for poor quality reads. See the functions solexa_quality_from_phred and
phred_quality_from_solexa for more details.
If you wanted to trim your sequences (perhaps to remove low quality regions,
or to remove a primer sequence), try slicing the SeqRecord objects. e.g.
>>> sub_rec = record[5:15]
>>> print sub_rec
ID: EAS54_6_R1_2_1_443_348
Name: EAS54_6_R1_2_1_443_348
Description: EAS54_6_R1_2_1_443_348
Number of features: 0
Per letter annotation for: phred_quality
Seq('TTCTGGCGTG', SingleLetterAlphabet())
>>> print sub_rec.letter_annotations["phred_quality"]
[26, 26, 26, 26, 26, 26, 24, 26, 22, 26]
>>> print sub_rec.format("fastq")
@EAS54_6_R1_2_1_443_348
TTCTGGCGTG
+
;;;;;;9;7;
<BLANKLINE>
If you wanted to, you could read in this FASTQ file, and save it as a QUAL file:
>>> from Bio import SeqIO
>>> record_iterator = SeqIO.parse("Quality/example.fastq", "fastq")
>>> out_handle = open("Quality/temp.qual", "w")
>>> SeqIO.write(record_iterator, out_handle, "qual")
3
>>> out_handle.close()
You can of course read in a QUAL file, such as the one we just created:
>>> from Bio import SeqIO
>>> for record in SeqIO.parse("Quality/temp.qual", "qual"):
... print record.id, record.seq
EAS54_6_R1_2_1_413_324 ?????????????????????????
EAS54_6_R1_2_1_540_792 ?????????????????????????
EAS54_6_R1_2_1_443_348 ?????????????????????????
Notice that QUAL files don't have a proper sequence present! But the quality
information is there:
>>> print record
ID: EAS54_6_R1_2_1_443_348
Name: EAS54_6_R1_2_1_443_348
Description: EAS54_6_R1_2_1_443_348
Number of features: 0
Per letter annotation for: phred_quality
UnknownSeq(25, alphabet = SingleLetterAlphabet(), character = '?')
>>> print record.letter_annotations["phred_quality"]
[26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 24, 26, 22, 26, 26, 13, 22, 26, 18, 24, 18, 18, 18, 18]
Just to keep things tidy, if you are following this example yourself, you can
delete this temporary file now:
>>> import os
>>> os.remove("Quality/temp.qual")
Sometimes you won't have a FASTQ file, but rather just a pair of FASTA and QUAL
files. Because the Bio.SeqIO system is designed for reading single files, you
would have to read the two in separately and then combine the data. However,
since this is such a common thing to want to do, there is a helper iterator
defined in this module that does this for you - PairedFastaQualIterator.
Alternatively, if you have enough RAM to hold all the records in memory at once,
then a simple dictionary approach would work:
>>> from Bio import SeqIO
>>> reads = SeqIO.to_dict(SeqIO.parse(open("Quality/example.fasta"), "fasta"))
>>> for rec in SeqIO.parse(open("Quality/example.qual"), "qual"):
... reads[rec.id].letter_annotations["phred_quality"]=rec.letter_annotations["phred_quality"]
You can then access any record by its key, and get both the sequence and the
quality scores.
>>> print reads["EAS54_6_R1_2_1_540_792"].format("fastq")
@EAS54_6_R1_2_1_540_792
TTGGCAGGCCAAGGCCGATGGATCA
+
;;;;;;;;;;;7;;;;;-;;;3;83
<BLANKLINE>
It is important that you explicitly tell Bio.SeqIO which FASTQ variant you are
using ("fastq" or "fastq-sanger" for the Sanger standard using PHRED values,
"fastq-solexa" for the original Solexa/Illumina variant, or "fastq-illumina"
for the more recent variant), as this cannot be detected reliably
automatically.
To illustrate this problem, let's consider an artifical example:
>>> from Bio.Seq import Seq
>>> from Bio.Alphabet import generic_dna
>>> from Bio.SeqRecord import SeqRecord
>>> test = SeqRecord(Seq("NACGTACGTA", generic_dna), id="Test",
... description="Made up!")
>>> print test.format("fasta")
>Test Made up!
NACGTACGTA
<BLANKLINE>
>>> print test.format("fastq")
Traceback (most recent call last):
...
ValueError: No suitable quality scores found in letter_annotations of SeqRecord (id=Test).
We created a sample SeqRecord, and can show it in FASTA format - but for QUAL
or FASTQ format we need to provide some quality scores. These are held as a
list of integers (one for each base) in the letter_annotations dictionary:
>>> test.letter_annotations["phred_quality"] = [0,1,2,3,4,5,10,20,30,40]
>>> print test.format("qual")
>Test Made up!
0 1 2 3 4 5 10 20 30 40
<BLANKLINE>
>>> print test.format("fastq")
@Test Made up!
NACGTACGTA
+
!"#$%&+5?I
<BLANKLINE>
We can check this FASTQ encoding - the first PHRED quality was zero, and this
mapped to a exclamation mark, while the final score was 40 and this mapped to
the letter "I":
>>> ord('!') - 33
0
>>> ord('I') - 33
40
>>> [ord(letter)-33 for letter in '!"#$%&+5?I']
[0, 1, 2, 3, 4, 5, 10, 20, 30, 40]
Similarly, we could produce an Illumina 1.3 to 1.7 style FASTQ file using PHRED
scores with an offset of 64:
>>> print test.format("fastq-illumina")
@Test Made up!
NACGTACGTA
+
@ABCDEJT^h
<BLANKLINE>
And we can check this too - the first PHRED score was zero, and this mapped to
"@", while the final score was 40 and this mapped to "h":
>>> ord("@") - 64
0
>>> ord("h") - 64
40
>>> [ord(letter)-64 for letter in "@ABCDEJT^h"]
[0, 1, 2, 3, 4, 5, 10, 20, 30, 40]
Notice how different the standard Sanger FASTQ and the Illumina 1.3 to 1.7 style
FASTQ files look for the same data! Then we have the older Solexa/Illumina
format to consider which encodes Solexa scores instead of PHRED scores.
First let's see what Biopython says if we convert the PHRED scores into Solexa
scores (rounding to one decimal place):
>>> for q in [0,1,2,3,4,5,10,20,30,40]:
... print "PHRED %i maps to Solexa %0.1f" % (q, solexa_quality_from_phred(q))
PHRED 0 maps to Solexa -5.0
PHRED 1 maps to Solexa -5.0
PHRED 2 maps to Solexa -2.3
PHRED 3 maps to Solexa -0.0
PHRED 4 maps to Solexa 1.8
PHRED 5 maps to Solexa 3.3
PHRED 10 maps to Solexa 9.5
PHRED 20 maps to Solexa 20.0
PHRED 30 maps to Solexa 30.0
PHRED 40 maps to Solexa 40.0
Now here is the record using the old Solexa style FASTQ file:
>>> print test.format("fastq-solexa")
@Test Made up!
NACGTACGTA
+
;;>@BCJT^h
<BLANKLINE>
Again, this is using an ASCII offset of 64, so we can check the Solexa scores:
>>> [ord(letter)-64 for letter in ";;>@BCJT^h"]
[-5, -5, -2, 0, 2, 3, 10, 20, 30, 40]
This explains why the last few letters of this FASTQ output matched that using
the Illumina 1.3 to 1.7 format - high quality PHRED scores and Solexa scores
are approximately equal.
"""
__docformat__ = "epytext en" #Don't just use plain text in epydoc API pages!
from Bio.Alphabet import single_letter_alphabet
from Bio.Seq import Seq, UnknownSeq
from Bio.SeqRecord import SeqRecord
from Bio.SeqIO.Interfaces import SequentialSequenceWriter
from math import log
import warnings
from Bio import BiopythonWarning
# define score offsets. See discussion for differences between Sanger and
# Solexa offsets.
SANGER_SCORE_OFFSET = 33
SOLEXA_SCORE_OFFSET = 64
def solexa_quality_from_phred(phred_quality):
"""Covert a PHRED quality (range 0 to about 90) to a Solexa quality.
PHRED and Solexa quality scores are both log transformations of a
probality of error (high score = low probability of error). This function
takes a PHRED score, transforms it back to a probability of error, and
then re-expresses it as a Solexa score. This assumes the error estimates
are equivalent.
How does this work exactly? Well the PHRED quality is minus ten times the
base ten logarithm of the probability of error::
phred_quality = -10*log(error,10)
Therefore, turning this round::
error = 10 ** (- phred_quality / 10)
Now, Solexa qualities use a different log transformation::
solexa_quality = -10*log(error/(1-error),10)
After substitution and a little manipulation we get::
solexa_quality = 10*log(10**(phred_quality/10.0) - 1, 10)
However, real Solexa files use a minimum quality of -5. This does have a
good reason - a random a random base call would be correct 25% of the time,
and thus have a probability of error of 0.75, which gives 1.25 as the PHRED
quality, or -4.77 as the Solexa quality. Thus (after rounding), a random
nucleotide read would have a PHRED quality of 1, or a Solexa quality of -5.
Taken literally, this logarithic formula would map a PHRED quality of zero
to a Solexa quality of minus infinity. Of course, taken literally, a PHRED
score of zero means a probability of error of one (i.e. the base call is
definitely wrong), which is worse than random! In practice, a PHRED quality
of zero usually means a default value, or perhaps random - and therefore
mapping it to the minimum Solexa score of -5 is reasonable.
In conclusion, we follow EMBOSS, and take this logarithmic formula but also
apply a minimum value of -5.0 for the Solexa quality, and also map a PHRED
quality of zero to -5.0 as well.
Note this function will return a floating point number, it is up to you to
round this to the nearest integer if appropriate. e.g.
>>> print "%0.2f" % round(solexa_quality_from_phred(80),2)
80.00
>>> print "%0.2f" % round(solexa_quality_from_phred(50),2)
50.00
>>> print "%0.2f" % round(solexa_quality_from_phred(20),2)
19.96
>>> print "%0.2f" % round(solexa_quality_from_phred(10),2)
9.54
>>> print "%0.2f" % round(solexa_quality_from_phred(5),2)
3.35
>>> print "%0.2f" % round(solexa_quality_from_phred(4),2)
1.80
>>> print "%0.2f" % round(solexa_quality_from_phred(3),2)
-0.02
>>> print "%0.2f" % round(solexa_quality_from_phred(2),2)
-2.33
>>> print "%0.2f" % round(solexa_quality_from_phred(1),2)
-5.00
>>> print "%0.2f" % round(solexa_quality_from_phred(0),2)
-5.00
Notice that for high quality reads PHRED and Solexa scores are numerically
equal. The differences are important for poor quality reads, where PHRED
has a minimum of zero but Solexa scores can be negative.
Finally, as a special case where None is used for a "missing value", None
is returned:
>>> print solexa_quality_from_phred(None)
None
"""
if phred_quality is None:
#Assume None is used as some kind of NULL or NA value; return None
#e.g. Bio.SeqIO gives Ace contig gaps a quality of None.
return None
elif phred_quality > 0:
#Solexa uses a minimum value of -5, which after rounding matches a
#random nucleotide base call.
return max(-5.0, 10*log(10**(phred_quality/10.0) - 1, 10))
elif phred_quality == 0:
#Special case, map to -5 as discussed in the docstring
return -5.0
else:
raise ValueError("PHRED qualities must be positive (or zero), not %s" \
% repr(phred_quality))
def phred_quality_from_solexa(solexa_quality):
"""Convert a Solexa quality (which can be negative) to a PHRED quality.
PHRED and Solexa quality scores are both log transformations of a
probality of error (high score = low probability of error). This function
takes a Solexa score, transforms it back to a probability of error, and
then re-expresses it as a PHRED score. This assumes the error estimates
are equivalent.
The underlying formulas are given in the documentation for the sister
function solexa_quality_from_phred, in this case the operation is::
phred_quality = 10*log(10**(solexa_quality/10.0) + 1, 10)
This will return a floating point number, it is up to you to round this to
the nearest integer if appropriate. e.g.
>>> print "%0.2f" % round(phred_quality_from_solexa(80),2)
80.00
>>> print "%0.2f" % round(phred_quality_from_solexa(20),2)
20.04
>>> print "%0.2f" % round(phred_quality_from_solexa(10),2)
10.41
>>> print "%0.2f" % round(phred_quality_from_solexa(0),2)
3.01
>>> print "%0.2f" % round(phred_quality_from_solexa(-5),2)
1.19
Note that a solexa_quality less then -5 is not expected, will trigger a
warning, but will still be converted as per the logarithmic mapping
(giving a number between 0 and 1.19 back).
As a special case where None is used for a "missing value", None is
returned:
>>> print phred_quality_from_solexa(None)
None
"""
if solexa_quality is None:
#Assume None is used as some kind of NULL or NA value; return None
return None
if solexa_quality < -5:
warnings.warn("Solexa quality less than -5 passed, %s" \
% repr(solexa_quality), BiopythonWarning)
return 10*log(10**(solexa_quality/10.0) + 1, 10)
def _get_phred_quality(record):
"""Extract PHRED qualities from a SeqRecord's letter_annotations (PRIVATE).
If there are no PHRED qualities, but there are Solexa qualities, those are
used instead after conversion.
"""
try:
return record.letter_annotations["phred_quality"]
except KeyError:
pass
try:
return [phred_quality_from_solexa(q) for \
q in record.letter_annotations["solexa_quality"]]
except KeyError:
raise ValueError("No suitable quality scores found in "
"letter_annotations of SeqRecord (id=%s)." \
% record.id)
#Only map 0 to 93, we need to give a warning on truncating at 93
_phred_to_sanger_quality_str = dict((qp, chr(min(126, qp+SANGER_SCORE_OFFSET))) \
for qp in range(0, 93+1))
#Only map -5 to 93, we need to give a warning on truncating at 93
_solexa_to_sanger_quality_str = dict( \
(qs, chr(min(126, int(round(phred_quality_from_solexa(qs)))+SANGER_SCORE_OFFSET))) \
for qs in range(-5, 93+1))
def _get_sanger_quality_str(record):
"""Returns a Sanger FASTQ encoded quality string (PRIVATE).
>>> from Bio.Seq import Seq
>>> from Bio.SeqRecord import SeqRecord
>>> r = SeqRecord(Seq("ACGTAN"), id="Test",
... letter_annotations = {"phred_quality":[50,40,30,20,10,0]})
>>> _get_sanger_quality_str(r)
'SI?5+!'
If as in the above example (or indeed a SeqRecord parser with Bio.SeqIO),
the PHRED qualities are integers, this function is able to use a very fast
pre-cached mapping. However, if they are floats which differ slightly, then
it has to do the appropriate rounding - which is slower:
>>> r2 = SeqRecord(Seq("ACGTAN"), id="Test2",
... letter_annotations = {"phred_quality":[50.0,40.05,29.99,20,9.55,0.01]})
>>> _get_sanger_quality_str(r2)
'SI?5+!'
If your scores include a None value, this raises an exception:
>>> r3 = SeqRecord(Seq("ACGTAN"), id="Test3",
... letter_annotations = {"phred_quality":[50,40,30,20,10,None]})
>>> _get_sanger_quality_str(r3)
Traceback (most recent call last):
...
TypeError: A quality value of None was found
If (strangely) your record has both PHRED and Solexa scores, then the PHRED
scores are used in preference:
>>> r4 = SeqRecord(Seq("ACGTAN"), id="Test4",
... letter_annotations = {"phred_quality":[50,40,30,20,10,0],
... "solexa_quality":[-5,-4,0,None,0,40]})
>>> _get_sanger_quality_str(r4)
'SI?5+!'
If there are no PHRED scores, but there are Solexa scores, these are used
instead (after the approriate conversion):
>>> r5 = SeqRecord(Seq("ACGTAN"), id="Test5",
... letter_annotations = {"solexa_quality":[40,30,20,10,0,-5]})
>>> _get_sanger_quality_str(r5)
'I?5+$"'
Again, integer Solexa scores can be looked up in a pre-cached mapping making
this very fast. You can still use approximate floating point scores:
>>> r6 = SeqRecord(Seq("ACGTAN"), id="Test6",
... letter_annotations = {"solexa_quality":[40.1,29.7,20.01,10,0.0,-4.9]})
>>> _get_sanger_quality_str(r6)
'I?5+$"'
Notice that due to the limited range of printable ASCII characters, a
PHRED quality of 93 is the maximum that can be held in an Illumina FASTQ
file (using ASCII 126, the tilde). This function will issue a warning
in this situation.
"""
#TODO - This functions works and is fast, but it is also ugly
#and there is considerable repetition of code for the other
#two FASTQ variants.
try:
#These take priority (in case both Solexa and PHRED scores found)
qualities = record.letter_annotations["phred_quality"]
except KeyError:
#Fall back on solexa scores...
pass
else:
#Try and use the precomputed mapping:
try:
return "".join([_phred_to_sanger_quality_str[qp] \
for qp in qualities])
except KeyError:
#Could be a float, or a None in the list, or a high value.
pass
if None in qualities:
raise TypeError("A quality value of None was found")
if max(qualities) >= 93.5:
warnings.warn("Data loss - max PHRED quality 93 in Sanger FASTQ",
BiopythonWarning)
#This will apply the truncation at 93, giving max ASCII 126
return "".join([chr(min(126, int(round(qp))+SANGER_SCORE_OFFSET)) \
for qp in qualities])
#Fall back on the Solexa scores...
try:
qualities = record.letter_annotations["solexa_quality"]
except KeyError:
raise ValueError("No suitable quality scores found in "
"letter_annotations of SeqRecord (id=%s)." \
% record.id)
#Try and use the precomputed mapping:
try:
return "".join([_solexa_to_sanger_quality_str[qs] \
for qs in qualities])
except KeyError:
#Either no PHRED scores, or something odd like a float or None
pass
if None in qualities:
raise TypeError("A quality value of None was found")
#Must do this the slow way, first converting the PHRED scores into
#Solexa scores:
if max(qualities) >= 93.5:
warnings.warn("Data loss - max PHRED quality 93 in Sanger FASTQ",
BiopythonWarning)
#This will apply the truncation at 93, giving max ASCII 126
return "".join([chr(min(126, int(round(phred_quality_from_solexa(qs)))+SANGER_SCORE_OFFSET)) \
for qs in qualities])
#Only map 0 to 62, we need to give a warning on truncating at 62
assert 62+SOLEXA_SCORE_OFFSET == 126
_phred_to_illumina_quality_str = dict((qp, chr(qp+SOLEXA_SCORE_OFFSET)) \
for qp in range(0, 62+1))
#Only map -5 to 62, we need to give a warning on truncating at 62
_solexa_to_illumina_quality_str = dict( \
(qs, chr(int(round(phred_quality_from_solexa(qs)))+SOLEXA_SCORE_OFFSET)) \
for qs in range(-5, 62+1))
def _get_illumina_quality_str(record):
"""Returns an Illumina 1.3 to 1.7 FASTQ encoded quality string (PRIVATE).
Notice that due to the limited range of printable ASCII characters, a
PHRED quality of 62 is the maximum that can be held in an Illumina FASTQ
file (using ASCII 126, the tilde). This function will issue a warning
in this situation.
"""
#TODO - This functions works and is fast, but it is also ugly
#and there is considerable repetition of code for the other
#two FASTQ variants.
try:
#These take priority (in case both Solexa and PHRED scores found)
qualities = record.letter_annotations["phred_quality"]
except KeyError:
#Fall back on solexa scores...
pass
else:
#Try and use the precomputed mapping:
try:
return "".join([_phred_to_illumina_quality_str[qp] \
for qp in qualities])
except KeyError:
#Could be a float, or a None in the list, or a high value.
pass
if None in qualities:
raise TypeError("A quality value of None was found")
if max(qualities) >= 62.5:
warnings.warn("Data loss - max PHRED quality 62 in Illumina FASTQ",
BiopythonWarning)
#This will apply the truncation at 62, giving max ASCII 126
return "".join([chr(min(126, int(round(qp))+SOLEXA_SCORE_OFFSET)) \
for qp in qualities])
#Fall back on the Solexa scores...
try:
qualities = record.letter_annotations["solexa_quality"]
except KeyError:
raise ValueError("No suitable quality scores found in "
"letter_annotations of SeqRecord (id=%s)." \
% record.id)
#Try and use the precomputed mapping:
try:
return "".join([_solexa_to_illumina_quality_str[qs] \
for qs in qualities])
except KeyError:
#Either no PHRED scores, or something odd like a float or None
pass
if None in qualities:
raise TypeError("A quality value of None was found")
#Must do this the slow way, first converting the PHRED scores into
#Solexa scores:
if max(qualities) >= 62.5:
warnings.warn("Data loss - max PHRED quality 62 in Illumina FASTQ",
BiopythonWarning)
#This will apply the truncation at 62, giving max ASCII 126
return "".join([chr(min(126, int(round(phred_quality_from_solexa(qs)))+SOLEXA_SCORE_OFFSET)) \
for qs in qualities])
#Only map 0 to 62, we need to give a warning on truncating at 62
assert 62+SOLEXA_SCORE_OFFSET == 126
_solexa_to_solexa_quality_str = dict((qs, chr(min(126, qs+SOLEXA_SCORE_OFFSET))) \
for qs in range(-5, 62+1))
#Only map -5 to 62, we need to give a warning on truncating at 62
_phred_to_solexa_quality_str = dict(\
(qp, chr(min(126, int(round(solexa_quality_from_phred(qp)))+SOLEXA_SCORE_OFFSET))) \
for qp in range(0, 62+1))
def _get_solexa_quality_str(record):
"""Returns a Solexa FASTQ encoded quality string (PRIVATE).
Notice that due to the limited range of printable ASCII characters, a
Solexa quality of 62 is the maximum that can be held in a Solexa FASTQ
file (using ASCII 126, the tilde). This function will issue a warning
in this situation.
"""
#TODO - This functions works and is fast, but it is also ugly
#and there is considerable repetition of code for the other
#two FASTQ variants.
try:
#These take priority (in case both Solexa and PHRED scores found)
qualities = record.letter_annotations["solexa_quality"]
except KeyError:
#Fall back on PHRED scores...
pass
else:
#Try and use the precomputed mapping:
try:
return "".join([_solexa_to_solexa_quality_str[qs] \
for qs in qualities])
except KeyError:
#Could be a float, or a None in the list, or a high value.
pass
if None in qualities:
raise TypeError("A quality value of None was found")
if max(qualities) >= 62.5:
warnings.warn("Data loss - max Solexa quality 62 in Solexa FASTQ",
BiopythonWarning)
#This will apply the truncation at 62, giving max ASCII 126
return "".join([chr(min(126, int(round(qs))+SOLEXA_SCORE_OFFSET)) \
for qs in qualities])
#Fall back on the PHRED scores...
try:
qualities = record.letter_annotations["phred_quality"]
except KeyError:
raise ValueError("No suitable quality scores found in "
"letter_annotations of SeqRecord (id=%s)." \
% record.id)
#Try and use the precomputed mapping:
try:
return "".join([_phred_to_solexa_quality_str[qp] \
for qp in qualities])
except KeyError:
#Either no PHRED scores, or something odd like a float or None
#or too big to be in the cache
pass
if None in qualities:
raise TypeError("A quality value of None was found")
#Must do this the slow way, first converting the PHRED scores into
#Solexa scores:
if max(qualities) >= 62.5:
warnings.warn("Data loss - max Solexa quality 62 in Solexa FASTQ",
BiopythonWarning)
return "".join([chr(min(126,
int(round(solexa_quality_from_phred(qp))) + \
SOLEXA_SCORE_OFFSET)) \
for qp in qualities])
#TODO - Default to nucleotide or even DNA?
def FastqGeneralIterator(handle):
"""Iterate over Fastq records as string tuples (not as SeqRecord objects).
This code does not try to interpret the quality string numerically. It
just returns tuples of the title, sequence and quality as strings. For
the sequence and quality, any whitespace (such as new lines) is removed.
Our SeqRecord based FASTQ iterators call this function internally, and then
turn the strings into a SeqRecord objects, mapping the quality string into
a list of numerical scores. If you want to do a custom quality mapping,
then you might consider calling this function directly.
For parsing FASTQ files, the title string from the "@" line at the start
of each record can optionally be omitted on the "+" lines. If it is
repeated, it must be identical.
The sequence string and the quality string can optionally be split over
multiple lines, although several sources discourage this. In comparison,
for the FASTA file format line breaks between 60 and 80 characters are
the norm.
WARNING - Because the "@" character can appear in the quality string,
this can cause problems as this is also the marker for the start of
a new sequence. In fact, the "+" sign can also appear as well. Some
sources recommended having no line breaks in the quality to avoid this,
but even that is not enough, consider this example::
@071113_EAS56_0053:1:1:998:236
TTTCTTGCCCCCATAGACTGAGACCTTCCCTAAATA
+071113_EAS56_0053:1:1:998:236
IIIIIIIIIIIIIIIIIIIIIIIIIIIIICII+III
@071113_EAS56_0053:1:1:182:712
ACCCAGCTAATTTTTGTATTTTTGTTAGAGACAGTG
+
@IIIIIIIIIIIIIIICDIIIII<%<6&-*).(*%+
@071113_EAS56_0053:1:1:153:10
TGTTCTGAAGGAAGGTGTGCGTGCGTGTGTGTGTGT
+
IIIIIIIIIIIICIIGIIIII>IAIIIE65I=II:6
@071113_EAS56_0053:1:3:990:501
TGGGAGGTTTTATGTGGA
AAGCAGCAATGTACAAGA
+
IIIIIII.IIIIII1@44
@-7.%<&+/$/%4(++(%
This is four PHRED encoded FASTQ entries originally from an NCBI source
(given the read length of 36, these are probably Solexa Illumna reads where
the quality has been mapped onto the PHRED values).
This example has been edited to illustrate some of the nasty things allowed
in the FASTQ format. Firstly, on the "+" lines most but not all of the
(redundant) identifiers are ommited. In real files it is likely that all or
none of these extra identifiers will be present.
Secondly, while the first three sequences have been shown without line
breaks, the last has been split over multiple lines. In real files any line
breaks are likely to be consistent.
Thirdly, some of the quality string lines start with an "@" character. For
the second record this is unavoidable. However for the fourth sequence this
only happens because its quality string is split over two lines. A naive
parser could wrongly treat any line starting with an "@" as the beginning of
a new sequence! This code copes with this possible ambiguity by keeping
track of the length of the sequence which gives the expected length of the
quality string.
Using this tricky example file as input, this short bit of code demonstrates
what this parsing function would return:
>>> handle = open("Quality/tricky.fastq", "rU")
>>> for (title, sequence, quality) in FastqGeneralIterator(handle):
... print title
... print sequence, quality
071113_EAS56_0053:1:1:998:236
TTTCTTGCCCCCATAGACTGAGACCTTCCCTAAATA IIIIIIIIIIIIIIIIIIIIIIIIIIIIICII+III
071113_EAS56_0053:1:1:182:712
ACCCAGCTAATTTTTGTATTTTTGTTAGAGACAGTG @IIIIIIIIIIIIIIICDIIIII<%<6&-*).(*%+
071113_EAS56_0053:1:1:153:10
TGTTCTGAAGGAAGGTGTGCGTGCGTGTGTGTGTGT IIIIIIIIIIIICIIGIIIII>IAIIIE65I=II:6
071113_EAS56_0053:1:3:990:501
TGGGAGGTTTTATGTGGAAAGCAGCAATGTACAAGA IIIIIII.IIIIII1@44@-7.%<&+/$/%4(++(%
>>> handle.close()
Finally we note that some sources state that the quality string should
start with "!" (which using the PHRED mapping means the first letter always
has a quality score of zero). This rather restrictive rule is not widely
observed, so is therefore ignored here. One plus point about this "!" rule
is that (provided there are no line breaks in the quality sequence) it
would prevent the above problem with the "@" character.
"""
#We need to call handle.readline() at least four times per record,
#so we'll save a property look up each time:
handle_readline = handle.readline
#Skip any text before the first record (e.g. blank lines, comments?)
while True:
line = handle_readline()
if line == "" : return #Premature end of file, or just empty?
if line[0] == "@":
break
while True:
if line[0] != "@":
raise ValueError("Records in Fastq files should start with '@' character")
title_line = line[1:].rstrip()
#Will now be at least one line of quality data - in most FASTQ files
#just one line! We therefore use string concatenation (if needed)
#rather using than the "".join(...) trick just in case it is multiline:
seq_string = handle_readline().rstrip()
#There may now be more sequence lines, or the "+" quality marker line:
while True:
line = handle_readline()
if not line:
raise ValueError("End of file without quality information.")
if line[0] == "+":
#The title here is optional, but if present must match!
second_title = line[1:].rstrip()
if second_title and second_title != title_line:
raise ValueError("Sequence and quality captions differ.")
break
seq_string += line.rstrip() #removes trailing newlines
#This is going to slow things down a little, but assuming
#this isn't allowed we should try and catch it here:
if " " in seq_string or "\t" in seq_string:
raise ValueError("Whitespace is not allowed in the sequence.")
seq_len = len(seq_string)
#Will now be at least one line of quality data...
quality_string = handle_readline().rstrip()
#There may now be more quality data, or another sequence, or EOF
while True:
line = handle_readline()
if not line : break #end of file
if line[0] == "@":
#This COULD be the start of a new sequence. However, it MAY just
#be a line of quality data which starts with a "@" character. We
#should be able to check this by looking at the sequence length
#and the amount of quality data found so far.
if len(quality_string) >= seq_len:
#We expect it to be equal if this is the start of a new record.
#If the quality data is longer, we'll raise an error below.
break
#Continue - its just some (more) quality data.
quality_string += line.rstrip()
if seq_len != len(quality_string):
raise ValueError("Lengths of sequence and quality values differs "
" for %s (%i and %i)." \
% (title_line, seq_len, len(quality_string)))
#Return the record and then continue...
yield (title_line, seq_string, quality_string)
if not line : return #StopIteration at end of file
assert False, "Should not reach this line"
#This is a generator function!
def FastqPhredIterator(handle, alphabet = single_letter_alphabet, title2ids = None):
"""Generator function to iterate over FASTQ records (as SeqRecord objects).
- handle - input file
- alphabet - optional alphabet
- title2ids - A function that, when given the title line from the FASTQ
file (without the beginning >), will return the id, name and
description (in that order) for the record as a tuple of
strings. If this is not given, then the entire title line
will be used as the description, and the first word as the
id and name.
Note that use of title2ids matches that of Bio.SeqIO.FastaIO.
For each sequence in a (Sanger style) FASTQ file there is a matching string
encoding the PHRED qualities (integers between 0 and about 90) using ASCII
values with an offset of 33.
For example, consider a file containing three short reads::
@EAS54_6_R1_2_1_413_324
CCCTTCTTGTCTTCAGCGTTTCTCC
+
;;3;;;;;;;;;;;;7;;;;;;;88
@EAS54_6_R1_2_1_540_792
TTGGCAGGCCAAGGCCGATGGATCA
+
;;;;;;;;;;;7;;;;;-;;;3;83
@EAS54_6_R1_2_1_443_348
GTTGCTTCTGGCGTGGGTGGGGGGG
+
;;;;;;;;;;;9;7;;.7;393333
For each sequence (e.g. "CCCTTCTTGTCTTCAGCGTTTCTCC") there is a matching
string encoding the PHRED qualities using a ASCI values with an offset of
33 (e.g. ";;3;;;;;;;;;;;;7;;;;;;;88").
Using this module directly you might run:
>>> handle = open("Quality/example.fastq", "rU")
>>> for record in FastqPhredIterator(handle):
... print record.id, record.seq
EAS54_6_R1_2_1_413_324 CCCTTCTTGTCTTCAGCGTTTCTCC
EAS54_6_R1_2_1_540_792 TTGGCAGGCCAAGGCCGATGGATCA
EAS54_6_R1_2_1_443_348 GTTGCTTCTGGCGTGGGTGGGGGGG
>>> handle.close()
Typically however, you would call this via Bio.SeqIO instead with "fastq"
(or "fastq-sanger") as the format:
>>> from Bio import SeqIO
>>> handle = open("Quality/example.fastq", "rU")
>>> for record in SeqIO.parse(handle, "fastq"):
... print record.id, record.seq
EAS54_6_R1_2_1_413_324 CCCTTCTTGTCTTCAGCGTTTCTCC
EAS54_6_R1_2_1_540_792 TTGGCAGGCCAAGGCCGATGGATCA
EAS54_6_R1_2_1_443_348 GTTGCTTCTGGCGTGGGTGGGGGGG
>>> handle.close()
If you want to look at the qualities, they are record in each record's
per-letter-annotation dictionary as a simple list of integers:
>>> print record.letter_annotations["phred_quality"]
[26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 24, 26, 22, 26, 26, 13, 22, 26, 18, 24, 18, 18, 18, 18]
"""
assert SANGER_SCORE_OFFSET == ord("!")
#Originally, I used a list expression for each record:
#
# qualities = [ord(letter)-SANGER_SCORE_OFFSET for letter in quality_string]
#
#Precomputing is faster, perhaps partly by avoiding the subtractions.
q_mapping = dict()
for letter in range(0, 255):
q_mapping[chr(letter)] = letter-SANGER_SCORE_OFFSET
for title_line, seq_string, quality_string in FastqGeneralIterator(handle):
if title2ids:
id, name, descr = title2ids(title_line)
else:
descr = title_line
id = descr.split()[0]
name = id
record = SeqRecord(Seq(seq_string, alphabet),
id=id, name=name, description=descr)
qualities = [q_mapping[letter] for letter in quality_string]
if qualities and (min(qualities) < 0 or max(qualities) > 93):
raise ValueError("Invalid character in quality string")
#For speed, will now use a dirty trick to speed up assigning the
#qualities. We do this to bypass the length check imposed by the
#per-letter-annotations restricted dict (as this has already been
#checked by FastqGeneralIterator). This is equivalent to:
#record.letter_annotations["phred_quality"] = qualities
dict.__setitem__(record._per_letter_annotations,
"phred_quality", qualities)
yield record
#This is a generator function!
def FastqSolexaIterator(handle, alphabet = single_letter_alphabet, title2ids = None):
r"""Parsing old Solexa/Illumina FASTQ like files (which differ in the quality mapping).
The optional arguments are the same as those for the FastqPhredIterator.
For each sequence in Solexa/Illumina FASTQ files there is a matching string
encoding the Solexa integer qualities using ASCII values with an offset
of 64. Solexa scores are scaled differently to PHRED scores, and Biopython
will NOT perform any automatic conversion when loading.
NOTE - This file format is used by the OLD versions of the Solexa/Illumina
pipeline. See also the FastqIlluminaIterator function for the NEW version.
For example, consider a file containing these five records::
@SLXA-B3_649_FC8437_R1_1_1_610_79
GATGTGCAATACCTTTGTAGAGGAA
+SLXA-B3_649_FC8437_R1_1_1_610_79
YYYYYYYYYYYYYYYYYYWYWYYSU
@SLXA-B3_649_FC8437_R1_1_1_397_389
GGTTTGAGAAAGAGAAATGAGATAA
+SLXA-B3_649_FC8437_R1_1_1_397_389
YYYYYYYYYWYYYYWWYYYWYWYWW
@SLXA-B3_649_FC8437_R1_1_1_850_123
GAGGGTGTTGATCATGATGATGGCG
+SLXA-B3_649_FC8437_R1_1_1_850_123
YYYYYYYYYYYYYWYYWYYSYYYSY
@SLXA-B3_649_FC8437_R1_1_1_362_549
GGAAACAAAGTTTTTCTCAACATAG
+SLXA-B3_649_FC8437_R1_1_1_362_549
YYYYYYYYYYYYYYYYYYWWWWYWY
@SLXA-B3_649_FC8437_R1_1_1_183_714
GTATTATTTAATGGCATACACTCAA
+SLXA-B3_649_FC8437_R1_1_1_183_714
YYYYYYYYYYWYYYYWYWWUWWWQQ
Using this module directly you might run:
>>> handle = open("Quality/solexa_example.fastq", "rU")
>>> for record in FastqSolexaIterator(handle):
... print record.id, record.seq
SLXA-B3_649_FC8437_R1_1_1_610_79 GATGTGCAATACCTTTGTAGAGGAA
SLXA-B3_649_FC8437_R1_1_1_397_389 GGTTTGAGAAAGAGAAATGAGATAA
SLXA-B3_649_FC8437_R1_1_1_850_123 GAGGGTGTTGATCATGATGATGGCG
SLXA-B3_649_FC8437_R1_1_1_362_549 GGAAACAAAGTTTTTCTCAACATAG
SLXA-B3_649_FC8437_R1_1_1_183_714 GTATTATTTAATGGCATACACTCAA
>>> handle.close()
Typically however, you would call this via Bio.SeqIO instead with
"fastq-solexa" as the format:
>>> from Bio import SeqIO
>>> handle = open("Quality/solexa_example.fastq", "rU")
>>> for record in SeqIO.parse(handle, "fastq-solexa"):
... print record.id, record.seq
SLXA-B3_649_FC8437_R1_1_1_610_79 GATGTGCAATACCTTTGTAGAGGAA
SLXA-B3_649_FC8437_R1_1_1_397_389 GGTTTGAGAAAGAGAAATGAGATAA
SLXA-B3_649_FC8437_R1_1_1_850_123 GAGGGTGTTGATCATGATGATGGCG
SLXA-B3_649_FC8437_R1_1_1_362_549 GGAAACAAAGTTTTTCTCAACATAG
SLXA-B3_649_FC8437_R1_1_1_183_714 GTATTATTTAATGGCATACACTCAA
>>> handle.close()
If you want to look at the qualities, they are recorded in each record's
per-letter-annotation dictionary as a simple list of integers:
>>> print record.letter_annotations["solexa_quality"]
[25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 23, 25, 25, 25, 25, 23, 25, 23, 23, 21, 23, 23, 23, 17, 17]
These scores aren't very good, but they are high enough that they map
almost exactly onto PHRED scores:
>>> print "%0.2f" % phred_quality_from_solexa(25)
25.01
Let's look at faked example read which is even worse, where there are
more noticeable differences between the Solexa and PHRED scores::
@slxa_0001_1_0001_01
ACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTNNNNNN
+slxa_0001_1_0001_01
hgfedcba`_^]\[ZYXWVUTSRQPONMLKJIHGFEDCBA@?>=<;
Again, you would typically use Bio.SeqIO to read this file in (rather than
calling the Bio.SeqIO.QualtityIO module directly). Most FASTQ files will
contain thousands of reads, so you would normally use Bio.SeqIO.parse()
as shown above. This example has only as one entry, so instead we can
use the Bio.SeqIO.read() function:
>>> from Bio import SeqIO
>>> handle = open("Quality/solexa_faked.fastq", "rU")
>>> record = SeqIO.read(handle, "fastq-solexa")
>>> handle.close()
>>> print record.id, record.seq
slxa_0001_1_0001_01 ACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTNNNNNN
>>> print record.letter_annotations["solexa_quality"]
[40, 39, 38, 37, 36, 35, 34, 33, 32, 31, 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0, -1, -2, -3, -4, -5]
These quality scores are so low that when converted from the Solexa scheme
into PHRED scores they look quite different:
>>> print "%0.2f" % phred_quality_from_solexa(-1)
2.54
>>> print "%0.2f" % phred_quality_from_solexa(-5)
1.19
Note you can use the Bio.SeqIO.write() function or the SeqRecord's format
method to output the record(s):
>>> print record.format("fastq-solexa")
@slxa_0001_1_0001_01
ACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTNNNNNN
+
hgfedcba`_^]\[ZYXWVUTSRQPONMLKJIHGFEDCBA@?>=<;
<BLANKLINE>
Note this output is slightly different from the input file as Biopython
has left out the optional repetition of the sequence identifier on the "+"
line. If you want the to use PHRED scores, use "fastq" or "qual" as the
output format instead, and Biopython will do the conversion for you:
>>> print record.format("fastq")
@slxa_0001_1_0001_01
ACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTNNNNNN
+
IHGFEDCBA@?>=<;:9876543210/.-,++*)('&&%%$$##""
<BLANKLINE>
>>> print record.format("qual")
>slxa_0001_1_0001_01
40 39 38 37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21
20 19 18 17 16 15 14 13 12 11 10 10 9 8 7 6 5 5 4 4 3 3 2 2
1 1
<BLANKLINE>
As shown above, the poor quality Solexa reads have been mapped to the
equivalent PHRED score (e.g. -5 to 1 as shown earlier).
"""
q_mapping = dict()
for letter in range(0, 255):
q_mapping[chr(letter)] = letter-SOLEXA_SCORE_OFFSET
for title_line, seq_string, quality_string in FastqGeneralIterator(handle):
if title2ids:
id, name, descr = title_line
else:
descr = title_line
id = descr.split()[0]
name = id
record = SeqRecord(Seq(seq_string, alphabet),
id=id, name=name, description=descr)
qualities = [q_mapping[letter] for letter in quality_string]
#DO NOT convert these into PHRED qualities automatically!
if qualities and (min(qualities) < -5 or max(qualities)>62):
raise ValueError("Invalid character in quality string")
#Dirty trick to speed up this line:
#record.letter_annotations["solexa_quality"] = qualities
dict.__setitem__(record._per_letter_annotations,
"solexa_quality", qualities)
yield record
#This is a generator function!
def FastqIlluminaIterator(handle, alphabet = single_letter_alphabet, title2ids = None):
"""Parse Illumina 1.3 to 1.7 FASTQ like files (which differ in the quality mapping).
The optional arguments are the same as those for the FastqPhredIterator.
For each sequence in Illumina 1.3+ FASTQ files there is a matching string
encoding PHRED integer qualities using ASCII values with an offset of 64.
>>> from Bio import SeqIO
>>> record = SeqIO.read(open("Quality/illumina_faked.fastq"), "fastq-illumina")
>>> print record.id, record.seq
Test ACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTN
>>> max(record.letter_annotations["phred_quality"])
40
>>> min(record.letter_annotations["phred_quality"])
0
NOTE - Older versions of the Solexa/Illumina pipeline encoded Solexa scores
with an ASCII offset of 64. They are approximately equal but only for high
quality reads. If you have an old Solexa/Illumina file with negative
Solexa scores, and try and read this as an Illumina 1.3+ file it will fail:
>>> record2 = SeqIO.read(open("Quality/solexa_faked.fastq"), "fastq-illumina")
Traceback (most recent call last):
...
ValueError: Invalid character in quality string
NOTE - True Sanger style FASTQ files use PHRED scores with an offset of 33.
"""
q_mapping = dict()
for letter in range(0, 255):
q_mapping[chr(letter)] = letter-SOLEXA_SCORE_OFFSET
for title_line, seq_string, quality_string in FastqGeneralIterator(handle):
if title2ids:
id, name, descr = title2ids(title_line)
else:
descr = title_line
id = descr.split()[0]
name = id
record = SeqRecord(Seq(seq_string, alphabet),
id=id, name=name, description=descr)
qualities = [q_mapping[letter] for letter in quality_string]
if qualities and (min(qualities) < 0 or max(qualities) > 62):
raise ValueError("Invalid character in quality string")
#Dirty trick to speed up this line:
#record.letter_annotations["phred_quality"] = qualities
dict.__setitem__(record._per_letter_annotations,
"phred_quality", qualities)
yield record
def QualPhredIterator(handle, alphabet = single_letter_alphabet, title2ids = None):
"""For QUAL files which include PHRED quality scores, but no sequence.
For example, consider this short QUAL file::
>EAS54_6_R1_2_1_413_324
26 26 18 26 26 26 26 26 26 26 26 26 26 26 26 22 26 26 26 26
26 26 26 23 23
>EAS54_6_R1_2_1_540_792
26 26 26 26 26 26 26 26 26 26 26 22 26 26 26 26 26 12 26 26
26 18 26 23 18
>EAS54_6_R1_2_1_443_348
26 26 26 26 26 26 26 26 26 26 26 24 26 22 26 26 13 22 26 18
24 18 18 18 18
Using this module directly you might run:
>>> handle = open("Quality/example.qual", "rU")
>>> for record in QualPhredIterator(handle):
... print record.id, record.seq
EAS54_6_R1_2_1_413_324 ?????????????????????????
EAS54_6_R1_2_1_540_792 ?????????????????????????
EAS54_6_R1_2_1_443_348 ?????????????????????????
>>> handle.close()
Typically however, you would call this via Bio.SeqIO instead with "qual"
as the format:
>>> from Bio import SeqIO
>>> handle = open("Quality/example.qual", "rU")
>>> for record in SeqIO.parse(handle, "qual"):
... print record.id, record.seq
EAS54_6_R1_2_1_413_324 ?????????????????????????
EAS54_6_R1_2_1_540_792 ?????????????????????????
EAS54_6_R1_2_1_443_348 ?????????????????????????
>>> handle.close()
Becase QUAL files don't contain the sequence string itself, the seq
property is set to an UnknownSeq object. As no alphabet was given, this
has defaulted to a generic single letter alphabet and the character "?"
used.
By specifying a nucleotide alphabet, "N" is used instead:
>>> from Bio import SeqIO
>>> from Bio.Alphabet import generic_dna
>>> handle = open("Quality/example.qual", "rU")
>>> for record in SeqIO.parse(handle, "qual", alphabet=generic_dna):
... print record.id, record.seq
EAS54_6_R1_2_1_413_324 NNNNNNNNNNNNNNNNNNNNNNNNN
EAS54_6_R1_2_1_540_792 NNNNNNNNNNNNNNNNNNNNNNNNN
EAS54_6_R1_2_1_443_348 NNNNNNNNNNNNNNNNNNNNNNNNN
>>> handle.close()
However, the quality scores themselves are available as a list of integers
in each record's per-letter-annotation:
>>> print record.letter_annotations["phred_quality"]
[26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 24, 26, 22, 26, 26, 13, 22, 26, 18, 24, 18, 18, 18, 18]
You can still slice one of these SeqRecord objects with an UnknownSeq:
>>> sub_record = record[5:10]
>>> print sub_record.id, sub_record.letter_annotations["phred_quality"]
EAS54_6_R1_2_1_443_348 [26, 26, 26, 26, 26]
"""
#Skip any text before the first record (e.g. blank lines, comments)
while True:
line = handle.readline()
if line == "" : return #Premature end of file, or just empty?
if line[0] == ">":
break
while True:
if line[0] != ">":
raise ValueError("Records in Fasta files should start with '>' character")
if title2ids:
id, name, descr = title2ids(line[1:].rstrip())
else:
descr = line[1:].rstrip()
id = descr.split()[0]
name = id
qualities = []
line = handle.readline()
while True:
if not line : break
if line[0] == ">": break
qualities.extend([int(word) for word in line.split()])
line = handle.readline()
if qualities and min(qualities) < 0:
raise ValueError(("Negative quality score %i found in %s. " + \
"Are these Solexa scores, not PHRED scores?") \
% (min(qualities), id))
#Return the record and then continue...
record = SeqRecord(UnknownSeq(len(qualities), alphabet),
id = id, name = name, description = descr)
#Dirty trick to speed up this line:
#record.letter_annotations["phred_quality"] = qualities
dict.__setitem__(record._per_letter_annotations,
"phred_quality", qualities)
yield record
if not line : return #StopIteration
assert False, "Should not reach this line"
class FastqPhredWriter(SequentialSequenceWriter):
"""Class to write standard FASTQ format files (using PHRED quality scores).
Although you can use this class directly, you are strongly encouraged
to use the Bio.SeqIO.write() function instead via the format name "fastq"
or the alias "fastq-sanger". For example, this code reads in a standard
Sanger style FASTQ file (using PHRED scores) and re-saves it as another
Sanger style FASTQ file:
>>> from Bio import SeqIO
>>> record_iterator = SeqIO.parse(open("Quality/example.fastq"), "fastq")
>>> out_handle = open("Quality/temp.fastq", "w")
>>> SeqIO.write(record_iterator, out_handle, "fastq")
3
>>> out_handle.close()
You might want to do this if the original file included extra line breaks,
which while valid may not be supported by all tools. The output file from
Biopython will have each sequence on a single line, and each quality
string on a single line (which is considered desirable for maximum
compatibility).
In this next example, an old style Solexa/Illumina FASTQ file (using Solexa
quality scores) is converted into a standard Sanger style FASTQ file using
PHRED qualities:
>>> from Bio import SeqIO
>>> record_iterator = SeqIO.parse(open("Quality/solexa_example.fastq"), "fastq-solexa")
>>> out_handle = open("Quality/temp.fastq", "w")
>>> SeqIO.write(record_iterator, out_handle, "fastq")
5
>>> out_handle.close()
This code is also called if you use the .format("fastq") method of a
SeqRecord, or .format("fastq-sanger") if you prefer that alias.
Note that Sanger FASTQ files have an upper limit of PHRED quality 93, which is
encoded as ASCII 126, the tilde. If your quality scores are truncated to fit, a
warning is issued.
P.S. To avoid cluttering up your working directory, you can delete this
temporary file now:
>>> import os
>>> os.remove("Quality/temp.fastq")
"""
assert SANGER_SCORE_OFFSET == ord("!")
def write_record(self, record):
"""Write a single FASTQ record to the file."""
assert self._header_written
assert not self._footer_written
self._record_written = True
#TODO - Is an empty sequence allowed in FASTQ format?
if record.seq is None:
raise ValueError("No sequence for record %s" % record.id)
seq_str = str(record.seq)
qualities_str = _get_sanger_quality_str(record)
if len(qualities_str) != len(seq_str):
raise ValueError("Record %s has sequence length %i but %i quality scores" \
% (record.id, len(seq_str), len(qualities_str)))
#FASTQ files can include a description, just like FASTA files
#(at least, this is what the NCBI Short Read Archive does)
id = self.clean(record.id)
description = self.clean(record.description)
if description and description.split(None, 1)[0]==id:
#The description includes the id at the start
title = description
elif description:
title = "%s %s" % (id, description)
else:
title = id
self.handle.write("@%s\n%s\n+\n%s\n" % (title, seq_str, qualities_str))
class QualPhredWriter(SequentialSequenceWriter):
"""Class to write QUAL format files (using PHRED quality scores).
Although you can use this class directly, you are strongly encouraged
to use the Bio.SeqIO.write() function instead. For example, this code
reads in a FASTQ file and saves the quality scores into a QUAL file:
>>> from Bio import SeqIO
>>> record_iterator = SeqIO.parse(open("Quality/example.fastq"), "fastq")
>>> out_handle = open("Quality/temp.qual", "w")
>>> SeqIO.write(record_iterator, out_handle, "qual")
3
>>> out_handle.close()
This code is also called if you use the .format("qual") method of a
SeqRecord.
P.S. Don't forget to clean up the temp file if you don't need it anymore:
>>> import os
>>> os.remove("Quality/temp.qual")
"""
def __init__(self, handle, wrap=60, record2title=None):
"""Create a QUAL writer.
Arguments:
- handle - Handle to an output file, e.g. as returned
by open(filename, "w")
- wrap - Optional line length used to wrap sequence lines.
Defaults to wrapping the sequence at 60 characters
Use zero (or None) for no wrapping, giving a single
long line for the sequence.
- record2title - Optional function to return the text to be
used for the title line of each record. By default
a combination of the record.id and record.description
is used. If the record.description starts with the
record.id, then just the record.description is used.
The record2title argument is present for consistency with the
Bio.SeqIO.FastaIO writer class.
"""
SequentialSequenceWriter.__init__(self, handle)
#self.handle = handle
self.wrap = None
if wrap:
if wrap < 1:
raise ValueError
self.wrap = wrap
self.record2title = record2title
def write_record(self, record):
"""Write a single QUAL record to the file."""
assert self._header_written
assert not self._footer_written
self._record_written = True
handle = self.handle
wrap = self.wrap
if self.record2title:
title = self.clean(self.record2title(record))
else:
id = self.clean(record.id)
description = self.clean(record.description)
if description and description.split(None, 1)[0]==id:
#The description includes the id at the start
title = description
elif description:
title = "%s %s" % (id, description)
else:
title = id
handle.write(">%s\n" % title)
qualities = _get_phred_quality(record)
try:
#This rounds to the nearest integer.
#TODO - can we record a float in a qual file?
qualities_strs = [("%i" % round(q, 0)) for q in qualities]
except TypeError, e:
if None in qualities:
raise TypeError("A quality value of None was found")
else:
raise e
if wrap > 5:
#Fast wrapping
data = " ".join(qualities_strs)
while True:
if len(data) <= wrap:
self.handle.write(data + "\n")
break
else:
#By construction there must be spaces in the first X chars
#(unless we have X digit or higher quality scores!)
i = data.rfind(" ", 0, wrap)
handle.write(data[:i] + "\n")
data = data[i+1:]
elif wrap:
#Safe wrapping
while qualities_strs:
line = qualities_strs.pop(0)
while qualities_strs \
and len(line) + 1 + len(qualities_strs[0]) < wrap:
line += " " + qualities_strs.pop(0)
handle.write(line + "\n")
else:
#No wrapping
data = " ".join(qualities_strs)
handle.write(data + "\n")
class FastqSolexaWriter(SequentialSequenceWriter):
r"""Write old style Solexa/Illumina FASTQ format files (with Solexa qualities).
This outputs FASTQ files like those from the early Solexa/Illumina
pipeline, using Solexa scores and an ASCII offset of 64. These are
NOT compatible with the standard Sanger style PHRED FASTQ files.
If your records contain a "solexa_quality" entry under letter_annotations,
this is used, otherwise any "phred_quality" entry will be used after
conversion using the solexa_quality_from_phred function. If neither style
of quality scores are present, an exception is raised.
Although you can use this class directly, you are strongly encouraged
to use the Bio.SeqIO.write() function instead. For example, this code
reads in a FASTQ file and re-saves it as another FASTQ file:
>>> from Bio import SeqIO
>>> record_iterator = SeqIO.parse(open("Quality/solexa_example.fastq"), "fastq-solexa")
>>> out_handle = open("Quality/temp.fastq", "w")
>>> SeqIO.write(record_iterator, out_handle, "fastq-solexa")
5
>>> out_handle.close()
You might want to do this if the original file included extra line breaks,
which (while valid) may not be supported by all tools. The output file
from Biopython will have each sequence on a single line, and each quality
string on a single line (which is considered desirable for maximum
compatibility).
This code is also called if you use the .format("fastq-solexa") method of
a SeqRecord. For example,
>>> record = SeqIO.read(open("Quality/sanger_faked.fastq"), "fastq-sanger")
>>> print record.format("fastq-solexa")
@Test PHRED qualities from 40 to 0 inclusive
ACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTN
+
hgfedcba`_^]\[ZYXWVUTSRQPONMLKJHGFECB@>;;
<BLANKLINE>
Note that Solexa FASTQ files have an upper limit of Solexa quality 62, which is
encoded as ASCII 126, the tilde. If your quality scores must be truncated to fit,
a warning is issued.
P.S. Don't forget to delete the temp file if you don't need it anymore:
>>> import os
>>> os.remove("Quality/temp.fastq")
"""
def write_record(self, record):
"""Write a single FASTQ record to the file."""
assert self._header_written
assert not self._footer_written
self._record_written = True
#TODO - Is an empty sequence allowed in FASTQ format?
if record.seq is None:
raise ValueError("No sequence for record %s" % record.id)
seq_str = str(record.seq)
qualities_str = _get_solexa_quality_str(record)
if len(qualities_str) != len(seq_str):
raise ValueError("Record %s has sequence length %i but %i quality scores" \
% (record.id, len(seq_str), len(qualities_str)))
#FASTQ files can include a description, just like FASTA files
#(at least, this is what the NCBI Short Read Archive does)
id = self.clean(record.id)
description = self.clean(record.description)
if description and description.split(None, 1)[0]==id:
#The description includes the id at the start
title = description
elif description:
title = "%s %s" % (id, description)
else:
title = id
self.handle.write("@%s\n%s\n+\n%s\n" % (title, seq_str, qualities_str))
class FastqIlluminaWriter(SequentialSequenceWriter):
r"""Write Illumina 1.3+ FASTQ format files (with PHRED quality scores).
This outputs FASTQ files like those from the Solexa/Illumina 1.3+ pipeline,
using PHRED scores and an ASCII offset of 64. Note these files are NOT
compatible with the standard Sanger style PHRED FASTQ files which use an
ASCII offset of 32.
Although you can use this class directly, you are strongly encouraged to
use the Bio.SeqIO.write() function with format name "fastq-illumina"
instead. This code is also called if you use the .format("fastq-illumina")
method of a SeqRecord. For example,
>>> from Bio import SeqIO
>>> record = SeqIO.read(open("Quality/sanger_faked.fastq"), "fastq-sanger")
>>> print record.format("fastq-illumina")
@Test PHRED qualities from 40 to 0 inclusive
ACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTN
+
hgfedcba`_^]\[ZYXWVUTSRQPONMLKJIHGFEDCBA@
<BLANKLINE>
Note that Illumina FASTQ files have an upper limit of PHRED quality 62, which is
encoded as ASCII 126, the tilde. If your quality scores are truncated to fit, a
warning is issued.
"""
def write_record(self, record):
"""Write a single FASTQ record to the file."""
assert self._header_written
assert not self._footer_written
self._record_written = True
#TODO - Is an empty sequence allowed in FASTQ format?
if record.seq is None:
raise ValueError("No sequence for record %s" % record.id)
seq_str = str(record.seq)
qualities_str = _get_illumina_quality_str(record)
if len(qualities_str) != len(seq_str):
raise ValueError("Record %s has sequence length %i but %i quality scores" \
% (record.id, len(seq_str), len(qualities_str)))
#FASTQ files can include a description, just like FASTA files
#(at least, this is what the NCBI Short Read Archive does)
id = self.clean(record.id)
description = self.clean(record.description)
if description and description.split(None, 1)[0]==id:
#The description includes the id at the start
title = description
elif description:
title = "%s %s" % (id, description)
else:
title = id
self.handle.write("@%s\n%s\n+\n%s\n" % (title, seq_str, qualities_str))
def PairedFastaQualIterator(fasta_handle, qual_handle, alphabet = single_letter_alphabet, title2ids = None):
"""Iterate over matched FASTA and QUAL files as SeqRecord objects.
For example, consider this short QUAL file with PHRED quality scores::
>EAS54_6_R1_2_1_413_324
26 26 18 26 26 26 26 26 26 26 26 26 26 26 26 22 26 26 26 26
26 26 26 23 23
>EAS54_6_R1_2_1_540_792
26 26 26 26 26 26 26 26 26 26 26 22 26 26 26 26 26 12 26 26
26 18 26 23 18
>EAS54_6_R1_2_1_443_348
26 26 26 26 26 26 26 26 26 26 26 24 26 22 26 26 13 22 26 18
24 18 18 18 18
And a matching FASTA file::
>EAS54_6_R1_2_1_413_324
CCCTTCTTGTCTTCAGCGTTTCTCC
>EAS54_6_R1_2_1_540_792
TTGGCAGGCCAAGGCCGATGGATCA
>EAS54_6_R1_2_1_443_348
GTTGCTTCTGGCGTGGGTGGGGGGG
You can parse these separately using Bio.SeqIO with the "qual" and
"fasta" formats, but then you'll get a group of SeqRecord objects with
no sequence, and a matching group with the sequence but not the
qualities. Because it only deals with one input file handle, Bio.SeqIO
can't be used to read the two files together - but this function can!
For example,
>>> rec_iter = PairedFastaQualIterator(open("Quality/example.fasta", "rU"),
... open("Quality/example.qual", "rU"))
>>> for record in rec_iter:
... print record.id, record.seq
EAS54_6_R1_2_1_413_324 CCCTTCTTGTCTTCAGCGTTTCTCC
EAS54_6_R1_2_1_540_792 TTGGCAGGCCAAGGCCGATGGATCA
EAS54_6_R1_2_1_443_348 GTTGCTTCTGGCGTGGGTGGGGGGG
As with the FASTQ or QUAL parsers, if you want to look at the qualities,
they are in each record's per-letter-annotation dictionary as a simple
list of integers:
>>> print record.letter_annotations["phred_quality"]
[26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 24, 26, 22, 26, 26, 13, 22, 26, 18, 24, 18, 18, 18, 18]
If you have access to data as a FASTQ format file, using that directly
would be simpler and more straight forward. Note that you can easily use
this function to convert paired FASTA and QUAL files into FASTQ files:
>>> from Bio import SeqIO
>>> rec_iter = PairedFastaQualIterator(open("Quality/example.fasta", "rU"),
... open("Quality/example.qual", "rU"))
>>> out_handle = open("Quality/temp.fastq", "w")
>>> SeqIO.write(rec_iter, out_handle, "fastq")
3
>>> out_handle.close()
And don't forget to clean up the temp file if you don't need it anymore:
>>> import os
>>> os.remove("Quality/temp.fastq")
"""
from Bio.SeqIO.FastaIO import FastaIterator
fasta_iter = FastaIterator(fasta_handle, alphabet=alphabet, \
title2ids=title2ids)
qual_iter = QualPhredIterator(qual_handle, alphabet=alphabet, \
title2ids=title2ids)
#Using zip(...) would create a list loading everything into memory!
#It would also not catch any extra records found in only one file.
while True:
try:
f_rec = fasta_iter.next()
except StopIteration:
f_rec = None
try:
q_rec = qual_iter.next()
except StopIteration:
q_rec = None
if f_rec is None and q_rec is None:
#End of both files
break
if f_rec is None:
raise ValueError("FASTA file has more entries than the QUAL file.")
if q_rec is None:
raise ValueError("QUAL file has more entries than the FASTA file.")
if f_rec.id != q_rec.id:
raise ValueError("FASTA and QUAL entries do not match (%s vs %s)." \
% (f_rec.id, q_rec.id))
if len(f_rec) != len(q_rec.letter_annotations["phred_quality"]):
raise ValueError("Sequence length and number of quality scores disagree for %s" \
% f_rec.id)
#Merge the data....
f_rec.letter_annotations["phred_quality"] = q_rec.letter_annotations["phred_quality"]
yield f_rec
#Done
def _test():
"""Run the Bio.SeqIO module's doctests.
This will try and locate the unit tests directory, and run the doctests
from there in order that the relative paths used in the examples work.
"""
import doctest
import os
if os.path.isdir(os.path.join("..", "..", "Tests")):
print "Runing doctests..."
cur_dir = os.path.abspath(os.curdir)
os.chdir(os.path.join("..", "..", "Tests"))
assert os.path.isfile("Quality/example.fastq")
assert os.path.isfile("Quality/example.fasta")
assert os.path.isfile("Quality/example.qual")
assert os.path.isfile("Quality/tricky.fastq")
assert os.path.isfile("Quality/solexa_faked.fastq")
doctest.testmod(verbose=0)
os.chdir(cur_dir)
del cur_dir
print "Done"
if __name__ == "__main__":
_test()
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