/usr/bin/mapDamage is in mapdamage 2.0.8+dfsg-1.
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# -*- coding: utf-8 -*-
from __future__ import print_function
import logging
import random
import time
import sys
import os
""" Copyright (c) 2012 Aurélien Ginolhac, Mikkel Schubert, Hákon Jónsson
and Ludovic Orlando
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"),
to deal in the Software without restriction, including without limitation
the rights to use, copy, modify, merge, publish, distribute, sublicense,
and/or sell copies of the Software, and to permit persons to whom
the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included
in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,
DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE
OR OTHER DEALINGS IN THE SOFTWARE.
plot and quantify damage patterns from a SAM/BAM file
:Authors: Aurélien Ginolhac, Mikkel Schubert, Hákon Jónsson, Ludovic Orlando
:Contact: aginolhac@snm.ku.dk, MSchubert@snm.ku.dk, jonsson.hakon@gmail.com
:Date: November 2012
:Type: tool
:Input: SAM/BAM
:Output: tabulated tables, pdf
"""
# check if pysam if available
MODULE = "pysam"
URL = "http://code.google.com/p/pysam/"
try:
__import__(MODULE)
except ImportError, e:
sys.stderr.write("Error: Could not import required module '%s':\n\t- %s\n" % (MODULE, e))
sys.stderr.write(" If module is not installed, please download from '%s'.\n" % URL)
sys.stderr.write(" A local install may be performed using the following command:\n")
sys.stderr.write(" $ python setup.py install --user\n\n")
sys.exit(1)
import pysam
_BAM_UNMAPPED = 0x4
_BAM_SECONDARY = 0x100
_BAM_FAILED_QC = 0x200
_BAM_PCR_DUPE = 0x400
_BAM_CHIMERIC = 0x800
def _filter_reads(bamfile):
filtered_flags = _BAM_UNMAPPED | \
_BAM_SECONDARY | \
_BAM_FAILED_QC | \
_BAM_PCR_DUPE | \
_BAM_CHIMERIC
for read in bamfile:
if not (read.flag & filtered_flags):
yield read
def _downsample_to_fraction(bamfile, options):
if options.verbose:
print("\tDownsampling %.2f fraction of the original file" % options.downsample)
assert options.downsample > 0, "Downsample fraction must be positive, not %s" % options.downsample
rand = random.Random(options.downsample_seed)
for read in _filter_reads(bamfile):
if rand.random() < options.downsample:
yield read
def _downsample_to_fixed_number(bamfile, options):
if options.verbose:
print("\tDownsampling %d random reads from the original file" % options.downsample)
# use reservoir sampling
downsample_to = int(options.downsample)
rand = random.Random(options.downsample_seed)
sample = [None] * downsample_to
for (index, record) in enumerate(_filter_reads(bamfile)):
if index >= downsample_to:
index = rand.randint(0, index)
if index >= downsample_to:
continue
sample[index] = record
return filter(None, sample)
def _read_bamfile(bamfile, options):
"""
Takes a subset of the bamfile. Can use a approximate fraction of the
hits or specific number of reads using reservoir sampling. Returns
a list in the last case otherwise a iterator.
"""
if options.downsample is None:
return _filter_reads(bamfile)
elif options.downsample < 1:
return _downsample_to_fraction(bamfile, options)
else:
return _downsample_to_fixed_number(bamfile, options)
def _check_mm_option():
"""
As the user can override the system wide mapdamage modules with
the --mapdamage-modules, it has to happen before option parsing
in mapdamage.parseoptions
"""
path_to_mm = None
for nr,arg in zip(xrange(len(sys.argv)),sys.argv):
if arg.startswith("--mapdamage-modules"):
try:
if "=" in arg:
# the option is of the format --mapdamage-modules=AAAA
arg_p = arg.split("=")
path_to_mm = arg_p[1]
else:
# the option is of the format --mapdamage-modules AAAA
path_to_mm = sys.argv[nr+1]
break
except IndexError as e:
raise SystemExit("Must specify a path to --mapdamage-modules")
if path_to_mm != None:
if not os.path.isdir(path_to_mm):
raise SystemExit("The --mapdamage-modules option must be a valid path (path=%s)" % path_to_mm)
if not os.path.isdir(os.path.join(path_to_mm,"mapdamage")):
raise SystemExit("The --mapdamage-modules path (path=%s) must contain the mapdamage module" % path_to_mm)
return path_to_mm
def main():
start_time = time.time()
# the user can override the system wide mapdamage modules
path_to_mm = _check_mm_option()
if path_to_mm != None:
sys.path.insert(0,path_to_mm)
import mapdamage
fpath_seqtk = '/usr/bin/seqtk'
if not (os.path.isfile(fpath_seqtk) and os.access(fpath_seqtk, os.X_OK)):
sys.stderr.write("Seqtk executable not accessible; mapDamage has not\n"
"been intalled properly or current user does not\n"
"sufficient permissions. Expected executable at\n "
"'%s'\n" % (fpath_seqtk,))
return 1
options = mapdamage.parseoptions.options()
if options == None:
sys.stderr.write("Option parsing failed, terminating the program\n")
return 1
logging.basicConfig(filename = os.path.join(options.folder, "Runtime_log.txt"),
format = '%(asctime)s\t%(levelname)s\t%(name)s: %(message)s',
level = logging.DEBUG)
handler = logging.StreamHandler()
handler.setLevel(logging.INFO)
logging.getLogger().addHandler(handler)
logger = logging.getLogger("main")
logger.info("Started with the command: " + " ".join(sys.argv))
# plot using R if results folder already done
if options.plot_only:
if options.no_r:
logger.error("Cannot use plot damage patterns if R is missing, terminating the program")
return 1
else:
mapdamage.rscript.plot(options)
mapdamage.rscript.opt_plots(options)
return 0
# run the Bayesian estimation if the matrix construction is done
if options.stats_only:
# does not work for very low damage levels
if mapdamage.tables.check_table_and_warn_if_dmg_freq_is_low(options.folder):
logger.error("Cannot use the Bayesian estimation, terminating the program")
return 1
else:
# before running the Bayesian estimation get the base composition
path_to_basecomp = os.path.join(options.folder,"dnacomp_genome.csv")
if os.path.isfile(path_to_basecomp):
#Try to read the base composition file
mapdamage.composition.read_base_comp(path_to_basecomp)
else:
#Construct the base composition file
mapdamage.composition.get_base_comp(options.ref,path_to_basecomp)
mapdamage.rscript.run_stats(options)
return 0
# fetch all references and associated lengths in nucleotides
try:
ref = pysam.Fastafile(options.ref)
except IOError as e:
# Couldn't open the reference file
logger.error("Couldn't open the reference file "+options.ref+\
" or there are permission problems writing the "+options.ref+".fai file")
raise e
# rescale the qualities
if options.rescale_only:
if not options.quiet:
print("Starting rescaling...")
mapdamage.rescale.rescale_qual(ref, options)
return 0
# open SAM/BAM file
if options.filename == "-":
in_bam = pysam.Samfile("-", 'rb')
# disabling rescaling if reading from standard input since we need
# to read it twice
if options.rescale:
print("Warning, reading from standard input, rescaling is disabled")
options.rescale = False
else:
in_bam = pysam.Samfile(options.filename)
reflengths = dict(zip(in_bam.references, in_bam.lengths))
# check if references in SAM/BAM are the same in the fasta reference file
fai_lengths = mapdamage.seq.read_fasta_index(options.ref + ".fai")
if not fai_lengths:
return 1
elif not mapdamage.seq.compare_sequence_dicts(fai_lengths, reflengths):
return 1
elif (len(reflengths) >= 1000) and not options.merge_reference_sequences:
print("WARNING: Alignment contains a large number of reference sequences (%i)!" % len(reflengths))
print(" This may lead to excessive memory/disk usage.")
print(" Consider using --merge-reference-sequences")
print()
refnames = in_bam.references
if options.merge_reference_sequences:
refnames = ['*']
# for misincorporation patterns, record mismatches
misincorp = mapdamage.tables.initialize_mut(refnames, options.length)
# for fragmentation patterns, record base compositions
dnacomp = mapdamage.tables.initialize_comp(refnames, options.around, options.length)
# for length distributions
lgdistrib = mapdamage.tables.initialize_lg()
if not options.quiet:
print("\tReading from '%s'" % options.filename)
if options.minqual != 0:
print("\tFiltering out bases with a Phred score < %d" % options.minqual)
if options.verbose:
print("\t%d references are assumed in SAM/BAM file, for a total of %d nucleotides" % (len(reflengths), sum(reflengths.values())))
print("\tWriting results to '%s/'" % options.folder)
# open file handler to write alignments in fasta format
if options.fasta:
# use name of the SAM/BAM filename without extension
ffasta = os.path.splitext(os.path.basename(options.filename))[0]+'.fasta'
if not options.quiet:
print("\tWriting alignments in '%s'" % ffasta)
fhfasta = open(options.folder+"/"+ffasta,"w")
counter = 0
# main loop
for read in _read_bamfile(in_bam, options):
counter += 1
# external coordinates 5' and 3' , 3' is 1-based offset
coordinate = mapdamage.align.get_coordinates(read)
# record aligned length for single-end reads
lgdistrib = mapdamage.seq.record_lg(read, coordinate, lgdistrib)
# fetch reference name, chromosome or contig names
chrom = in_bam.getrname(read.tid)
(before, after) = mapdamage.align.get_around(coordinate, chrom, reflengths, options.around, ref)
refseq = ref.fetch(chrom, min(coordinate), max(coordinate)).upper()
# read.query contains aligned sequences while read.seq is the read itself
seq = read.query
# add gaps according to the cigar string, do it for qualities if filtering options is on
if not (options.minqual and read.qual):
if options.minqual:
logger.warning("Cannot filter bases by PHRED scores for read '%s'; no scores available." % read.qname)
(seq, refseq) = mapdamage.align.align(read.cigar, seq, refseq)
else:
# add gaps to qualities and mask read and reference nucleotides if below desired threshold
(seq, _, refseq) = mapdamage.align.align_with_qual(read.cigar, seq, read.qqual, options.minqual, refseq)
# reverse complement read and reference when mapped reverse strand
if read.is_reverse:
refseq = mapdamage.seq.revcomp(refseq)
seq = mapdamage.seq.revcomp(seq)
beforerev = mapdamage.seq.revcomp(after)
after = mapdamage.seq.revcomp(before)
before = beforerev
if options.merge_reference_sequences:
chrom = '*'
# record soft clipping when present
mapdamage.align.record_soft_clipping(read, misincorp[chrom], options.length)
# count misincorparations by comparing read and reference base by base
mapdamage.align.get_mis(read, seq, refseq, chrom, options.length, misincorp, '5p')
# do the same with sequences align to 3'-ends
mapdamage.align.get_mis(read, seq[::-1], refseq[::-1], chrom, options.length, misincorp, '3p')
# compute base composition for reads
mapdamage.composition.count_read_comp(read, chrom, options.length, dnacomp)
# compute base composition for genomic regions
mapdamage.composition.count_ref_comp(read, chrom, before, after, dnacomp)
if options.fasta:
mapdamage.seq.write_fasta(read, chrom, seq, refseq, min(coordinate), max(coordinate), before, after, fhfasta)
if options.verbose:
if counter % 50000 == 0:
print("\t%10d filtered alignments processed" % (counter,))
if options.verbose:
print("\tDone. %d filtered alignments processed" % (counter,))
logger.debug("BAM read in %f seconds" % (time.time() - start_time,))
# close file handlers
in_bam.close()
if options.fasta:
fhfasta.close()
# output results, write summary tables to disk
with open(options.folder+"/"+"misincorporation.txt", 'w') as fmut:
mapdamage.tables.print_mut(misincorp, options, fmut)
with open(options.folder+"/"+"dnacomp.txt", 'w') as fcomp:
mapdamage.tables.print_comp(dnacomp, options, fcomp)
with open(options.folder+"/"+"lgdistribution.txt", 'w') as flg:
mapdamage.tables.print_lg(lgdistrib, options, flg)
# plot using R
if not options.no_r:
mapdamage.rscript.plot(options)
mapdamage.rscript.opt_plots(options)
# raises a warning for very low damage levels
if mapdamage.tables.check_table_and_warn_if_dmg_freq_is_low(options.folder):
options.no_stats = True
# run the Bayesian estimation
if not options.no_stats:
# before running the Bayesian estimation get the base composition
mapdamage.composition.get_base_comp(options.ref,os.path.join(options.folder,"dnacomp_genome.csv"))
mapdamage.rscript.run_stats(options)
# rescale the qualities
if options.rescale:
mapdamage.rescale.rescale_qual(ref, options)
# need the fasta reference still open for rescaling
ref.close()
# log the time it took
logger.info("Successful run")
logger.debug("Run completed in %f seconds" % (time.time() - start_time,))
return 0
if __name__ == '__main__':
sys.exit(main())
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