import os
import sys
import shutil
import numpy as np
import pyBigWig
# own modules
from deeptools import mapReduce
from deeptools.utilities import getCommonChrNames
import deeptools.countReadsPerBin as cr
from deeptools import bamHandler
from deeptools import utilities
import config as cfg
debug = 0
old_settings = np.seterr(all='ignore')
[docs]def writeBedGraph_wrapper(args):
"""
Passes the arguments to writeBedGraph_worker.
This is a step required given
the constrains from the multiprocessing module.
The args var, contains as first element the 'self' value
from the WriteBedGraph object
"""
return WriteBedGraph.writeBedGraph_worker(*args)
[docs]class WriteBedGraph(cr.CountReadsPerBin):
r"""Reads bam files coverages and writes a bedgraph or bigwig file
Extends the CountReadsPerBin object such that the coverage
of bam files is writen to multiple bedgraph files at once.
The bedgraph files are later merge into one and converted
into a bigwig file if necessary.
The constructor arguments are the same as for CountReadsPerBin. However,
when calling the `run` method, the following parameters have
to be passed
Examples
--------
Given the following distribution of reads that cover 200 on
a chromosome named '3R'::
0 100 200
|------------------------------------------------------------|
A ===============
===============
B =============== ===============
===============
===============
>>> import tempfile
>>> test_path = os.path.dirname(os.path.abspath(__file__)) + "/test/test_data/"
>>> outFile = tempfile.NamedTemporaryFile()
>>> bam_file = test_path + "testA.bam"
For the example a simple scaling function is going to be used. This function
takes the coverage found at each region and multiplies it to the scaling factor.
In this case the scaling factor is 1.5
>>> function_to_call = scaleCoverage
>>> funcArgs = {'scaleFactor': 1.5}
Restrict process to a region between positions 0 and 200 of chromosome 3R
>>> region = '3R:0:200'
Set up such that coverage is computed for consecutive bins of length 25 bp
>>> bin_length = 25
>>> step_size = 25
>>> num_sample_sites = 0 #overruled by step_size
>>> c = WriteBedGraph([bam_file], binLength=bin_length, region=region, stepSize=step_size)
>>> c.run(function_to_call, funcArgs, outFile.name)
>>> open(outFile.name, 'r').readlines()
['3R\t0\t100\t0.00\n', '3R\t100\t200\t1.5\n']
>>> outFile.close()
"""
[docs] def run(self, func_to_call, func_args, out_file_name, blackListFileName=None, format="bedgraph", smoothLength=0):
r"""
Given a list of bamfiles, a function and a function arguments,
this method writes a bedgraph file (or bigwig) file
for a partition of the genome into tiles of given size
and a value for each tile that corresponds to the given function
and that is related to the coverage underlying the tile.
Parameters
----------
func_to_call : str
function name to be called to convert the list of coverages computed
for each bam file at each position into a single value. An example
is a function that takes the ratio between the coverage of two
bam files.
func_args : dict
dict of arguments to pass to `func`. E.g. {'scaleFactor':1.0}
out_file_name : str
name of the file to save the resulting data.
smoothLength : int
Distance in bp for smoothing the coverage per tile.
"""
self.__dict__["smoothLength"] = smoothLength
bam_handlers = [bamHandler.openBam(x) for x in self.bamFilesList]
genome_chunk_length = getGenomeChunkLength(bam_handlers, self.binLength)
# check if both bam files correspond to the same species
# by comparing the chromosome names:
chrom_names_and_size, non_common = getCommonChrNames(bam_handlers, verbose=False)
if self.region:
# in case a region is used, append the tilesize
self.region += ":{}".format(self.binLength)
for x in self.__dict__.keys():
sys.stderr.write("{}: {}\n".format(x, self.__getattribute__(x)))
res = mapReduce.mapReduce([func_to_call, func_args],
writeBedGraph_wrapper,
chrom_names_and_size,
self_=self,
genomeChunkLength=genome_chunk_length,
region=self.region,
blackListFileName=blackListFileName,
numberOfProcessors=self.numberOfProcessors)
# concatenate intermediary bedgraph files
out_file = open(out_file_name + ".bg", 'wb')
for tempfilename in res:
if tempfilename:
# concatenate all intermediate tempfiles into one
# bedgraph file
shutil.copyfileobj(open(tempfilename, 'rb'), out_file)
os.remove(tempfilename)
bedgraph_file = out_file.name
out_file.close()
if format == 'bedgraph':
os.rename(bedgraph_file, out_file_name)
if self.verbose:
print "output file: {}".format(out_file_name)
else:
bedGraphToBigWig(
chrom_names_and_size, bedgraph_file, out_file_name, True)
if self.verbose:
print "output file: {}".format(out_file_name)
os.remove(bedgraph_file)
[docs] def writeBedGraph_worker(self, chrom, start, end,
func_to_call, func_args,
bed_regions_list=None):
r"""Writes a bedgraph based on the read coverage found on bamFiles
The given func is called to compute the desired bedgraph value
using the funcArgs
Parameters
----------
chrom : str
Chrom name
start : int
start coordinate
end : int
end coordinate
func_to_call : str
function name to be called to convert the list of coverages computed
for each bam file at each position into a single value. An example
is a function that takes the ratio between the coverage of two
bam files.
func_args : dict
dict of arguments to pass to `func`.
smoothLength : int
Distance in bp for smoothing the coverage per tile.
bed_regions_list: list
List of tuples of the form (chrom, start, end)
corresponding to bed regions to be processed.
If not bed file was passed to the object constructor
then this list is empty.
Returns
-------
temporary file with the bedgraph results for the region queried.
Examples
--------
>>> test_path = os.path.dirname(os.path.abspath(__file__)) + "/test/test_data/"
>>> bamFile1 = test_path + "testA.bam"
>>> bin_length = 50
>>> number_of_samples = 0 # overruled by step_size
>>> func_to_call = scaleCoverage
>>> funcArgs = {'scaleFactor': 1.0}
>>> c = WriteBedGraph([bamFile1], bin_length, number_of_samples, stepSize=50)
>>> tempFile = c.writeBedGraph_worker( '3R', 0, 200, func_to_call, funcArgs)
>>> open(tempFile, 'r').readlines()
['3R\t0\t100\t0.00\n', '3R\t100\t200\t1.0\n']
>>> os.remove(tempFile)
"""
if start > end:
raise NameError("start position ({0}) bigger "
"than end position ({1})".format(start, end))
coverage = []
bam_handlers = [bamHandler.openBam(bam) for bam in self.bamFilesList]
for bam in bam_handlers:
coverage.append(
self.get_coverage_of_region(bam, chrom, start, end, self.binLength))
bam.close()
_file = open(utilities.getTempFileName(suffix='.bg'), 'w')
previous_value = None
length_coverage = len(coverage[0])
for tileIndex in xrange(length_coverage):
tileCoverage = []
for index in range(len(self.bamFilesList)):
if self.smoothLength > 0:
vector_start, vector_end = self.getSmoothRange(tileIndex,
self.binLength,
self.smoothLength,
length_coverage)
tileCoverage.append(
np.mean(coverage[index][vector_start:vector_end]))
else:
tileCoverage.append(coverage[index][tileIndex])
value = func_to_call(tileCoverage, func_args)
"""
# uncomment this lines if fixed step bedgraph is wanted
if not np.isnan(value):
writeStart = start + tileIndex*self.binLength
writeEnd = min(writeStart+self.binLength, end)
_file.write( "%s\t%d\t%d\t%.2f\n" % (chrom, writeStart,
writeEnd, value) )
"""
if previous_value is None:
writeStart = start + tileIndex * self.binLength
writeEnd = min(writeStart + self.binLength, end)
previous_value = value
elif previous_value == value:
writeEnd = min(writeEnd + self.binLength, end)
elif previous_value != value:
if not np.isnan(previous_value):
_file.write(
"{}\t{}\t{}\t{:.2f}\n".format(chrom, writeStart,
writeEnd, previous_value))
previous_value = value
writeStart = writeEnd
writeEnd = min(writeStart + self.binLength, end)
# write remaining value if not a nan
if previous_value and writeStart != end and not np.isnan(previous_value):
_file.write("%s\t%d\t%d\t%.1f\n" % (chrom, writeStart,
end, previous_value))
tempfilename = _file.name
_file.close()
return tempfilename
[docs]def bedGraphToBigWig(chromSizes, bedGraphPath, bigWigPath, sort=True):
"""
takes a bedgraph file, orders it and converts it to
a bigwig file using pyBigWig.
"""
from tempfile import NamedTemporaryFile
from os import remove, system
# Make a list of tuples for the bigWig header, this MUST be sorted identically to the bedGraph file
sort_cmd = cfg.config.get('external_tools', 'sort')
_file = NamedTemporaryFile(delete=False)
for chrom, size in chromSizes:
_file.write("{}\t{}\n".format(chrom, size))
_file.close()
system("LC_ALL=C {} -k1,1 -k2,2n {} > {}.sorted".format(sort_cmd, _file.name, _file.name))
cl = []
for line in open("{}.sorted".format(_file.name)):
chrom, chromLen = line.split()
cl.append((chrom, int(chromLen)))
remove(_file.name)
remove("{}.sorted".format(_file.name))
# check if the file is empty
if os.stat(bedGraphPath).st_size < 10:
import sys
sys.stderr.write(
"Error: The generated bedGraphFile was empty. Please adjust\n"
"your deepTools settings and check your input files.\n")
exit(1)
if sort:
# temporary file to store sorted bedgraph file
_file = NamedTemporaryFile(delete=False)
tempfilename1 = _file.name
system("LC_ALL=C {} -k1,1 -k2,2n {} > {}".format(sort_cmd, bedGraphPath, tempfilename1))
bedGraphPath = tempfilename1
bw = pyBigWig.open(bigWigPath, "w")
assert(bw is not None)
# The lack of maxZooms will change the results a bit, perhaps the defaults are better
bw.addHeader(cl, maxZooms=10)
for line in open(bedGraphPath):
interval = line.split()
bw.addEntries([interval[0]], [int(interval[1])], ends=[int(interval[2])], values=[float(interval[3])])
bw.close()
if sort:
remove(tempfilename1)
[docs]def getGenomeChunkLength(bamHandlers, tile_size):
"""
Tries to estimate the length of the genome sent to the workers
based on the density of reads per bam file and the number
of bam files.
The chunk length should be a multiple of the tileSize
"""
genomeLength = sum(bamHandlers[0].lengths)
max_reads_per_bp = max(
[float(x.mapped) / genomeLength for x in bamHandlers])
# 2e6 is an empirical estimate
genomeChunkLength = int(
min(5e6, int(2e6 / (max_reads_per_bp * len(bamHandlers)))))
genomeChunkLength -= genomeChunkLength % tile_size
return genomeChunkLength
[docs]def scaleCoverage(tile_coverage, args):
"""
tileCoverage should be an list with only one element
"""
return args['scaleFactor'] * tile_coverage[0]
[docs]def ratio(tile_coverage, args):
"""
tileCoverage should be an list of two elements
"""
return float(tile_coverage[0]) / tile_coverage[1]