1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746
|
#!/usr/bin/python3
# -*- coding: utf-8 -*-
import os
import shutil
import time
import subprocess
import sys
import py2bit
import pysam
import multiprocessing
import numpy as np
import argparse
from scipy.stats import binom
from deeptools.utilities import tbitToBamChrName, getGC_content
from deeptools import writeBedGraph, parserCommon, mapReduce
from deeptools import utilities
from deeptools.bamHandler import openBam
old_settings = np.seterr(all='ignore')
def parse_arguments(args=None):
parentParser = parserCommon.getParentArgParse(binSize=True, blackList=False)
requiredArgs = getRequiredArgs()
parser = argparse.ArgumentParser(
parents=[requiredArgs, parentParser],
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
description='This tool corrects the GC-bias using the'
' method proposed by [Benjamini & Speed (2012). '
'Nucleic Acids Research, 40(10)]. It will remove reads'
' from regions with too high coverage compared to the'
' expected values (typically GC-rich regions) and will'
' add reads to regions where too few reads are seen '
'(typically AT-rich regions). '
'The tool ``computeGCBias`` needs to be run first to generate the '
'frequency table needed here.',
usage='correctGCBias '
'-b file.bam --effectiveGenomeSize 2150570000 -g mm9.2bit '
'--GCbiasFrequenciesFile freq.txt -o gc_corrected.bam\n'
'help: correctGCBias -h / correctGCBias --help',
conflict_handler='resolve',
add_help=False)
return parser
def process_args(args=None):
args = parse_arguments().parse_args(args)
return args
def getRequiredArgs():
parser = argparse.ArgumentParser(add_help=False)
required = parser.add_argument_group('Required arguments')
# define the arguments
required.add_argument('--bamfile', '-b',
metavar='BAM file',
help='Sorted BAM file to correct.',
required=True)
required.add_argument('--effectiveGenomeSize',
help='The effective genome size is the portion '
'of the genome that is mappable. Large fractions of '
'the genome are stretches of NNNN that should be '
'discarded. Also, if repetitive regions were not '
'included in the mapping of reads, the effective '
'genome size needs to be adjusted accordingly. '
'A table of values is available here: '
'http://deeptools.readthedocs.io/en/latest/content/feature/effectiveGenomeSize.html .',
default=None,
type=int,
required=True)
required.add_argument('--genome', '-g',
help='Genome in two bit format. Most genomes can be '
'found here: http://hgdownload.cse.ucsc.edu/gbdb/ '
'Search for the .2bit ending. Otherwise, fasta '
'files can be converted to 2bit using faToTwoBit '
'available here: '
'http://hgdownload.cse.ucsc.edu/admin/exe/',
metavar='two bit file',
required=True)
required.add_argument('--GCbiasFrequenciesFile', '-freq',
help='Indicate the output file from '
'computeGCBias containing '
'the observed and expected read frequencies per GC-'
'content.',
type=argparse.FileType('r'),
metavar='FILE',
required=True)
output = parser.add_argument_group('Output options')
output.add_argument('--correctedFile', '-o',
help='Name of the corrected file. The ending will '
'be used to decide the output file format. The options '
'are ".bam", ".bw" for a bigWig file, ".bg" for a '
'bedGraph file.',
metavar='FILE',
type=argparse.FileType('w'),
required=True)
# define the optional arguments
optional = parser.add_argument_group('Optional arguments')
optional.add_argument("--help", "-h", action="help",
help="show this help message and exit")
return parser
def getReadGCcontent(tbit, read, fragmentLength, chrNameBit):
"""
The fragments for forward and reverse reads are defined as follows::
|- read.pos |- read.aend
---+=================>-----------------------+--------- Forward strand
|-fragStart |-fragEnd
---+-----------------------<=================+--------- Reverse strand
|-read.pos |-read.aend
|-----------------------------------------|
read.tlen
"""
fragStart = None
fragEnd = None
if read.is_paired and read.is_proper_pair and abs(read.tlen) < 2 * fragmentLength:
if read.is_reverse and read.tlen < 0:
fragEnd = read.reference_end
fragStart = read.reference_end + read.template_length
elif read.template_length >= read.query_alignment_length:
fragStart = read.pos
fragEnd = read.pos + read.template_length
if not fragStart:
if read.is_reverse:
fragEnd = read.reference_end
fragStart = read.reference_end - fragmentLength
else:
fragStart = read.pos
fragEnd = fragStart + fragmentLength
fragStart = max(0, fragStart)
try:
gc = getGC_content(tbit, chrNameBit, fragStart, fragEnd)
except Exception:
return None
if gc is None:
return None
# match the gc to the given fragmentLength
gc = int(np.round(gc * fragmentLength))
return gc
def writeCorrected_wrapper(args):
return writeCorrected_worker(*args)
def writeCorrected_worker(chrNameBam, chrNameBit, start, end, step):
r"""writes a bedgraph file containing the GC correction of
a region from the genome
>>> test = Tester()
>>> tempFile = writeCorrected_worker(*test.testWriteCorrectedChunk())
>>> open(tempFile, 'r').readlines()
['chr2L\t200\t225\t31.6\n', 'chr2L\t225\t250\t33.8\n', 'chr2L\t250\t275\t37.9\n', 'chr2L\t275\t300\t40.9\n']
>>> os.remove(tempFile)
"""
global R_gc
fragmentLength = len(R_gc) - 1
cvg_corr = np.zeros(end - start)
i = 0
tbit = py2bit.open(global_vars['2bit'])
bam = openBam(global_vars['bam'])
read_repetitions = 0
removed_duplicated_reads = 0
startTime = time.time()
# caching seems to be faster
# r.flag & 4 == 0 is to skip unmapped
# reads that nevertheless are asigned
# to a genomic position
reads = [r for r in bam.fetch(chrNameBam, start, end)
if r.flag & 4 == 0]
bam.close()
r_index = -1
for read in reads:
if read.is_unmapped:
continue
r_index += 1
try:
# calculate GC content of read fragment
gc = getReadGCcontent(tbit, read, fragmentLength,
chrNameBit)
except Exception as detail:
print(detail)
""" this exception happens when the end of a
chromosome is reached """
continue
if not gc:
continue
# is this read in the same orientation and position as the previous?
if r_index > 0 and read.pos == reads[r_index - 1].pos and \
read.is_reverse == reads[r_index - 1].is_reverse \
and read.pnext == reads[r_index - 1].pnext:
read_repetitions += 1
if read_repetitions >= global_vars['max_dup_gc'][gc]:
removed_duplicated_reads += 1
continue
else:
read_repetitions = 0
try:
fragmentStart, fragmentEnd = getFragmentFromRead(read, fragmentLength, extendPairedEnds=True)
vectorStart = max(fragmentStart - start, 0)
vectorEnd = min(fragmentEnd - start, end - start)
except TypeError:
# the get_fragment_from_read functions returns None in some cases.
# Those cases are to be skipped, hence the continue line.
continue
cvg_corr[vectorStart:vectorEnd] += float(1) / R_gc[gc]
i += 1
try:
if debug:
endTime = time.time()
print("{}, processing {} ({:.1f} per sec) "
"reads @ {}:{}-{}".format(multiprocessing.current_process().name,
i, i / (endTime - startTime),
chrNameBit, start, end))
except NameError:
pass
if i == 0:
return None
_file = open(utilities.getTempFileName(suffix='.bg'), 'w')
# save in bedgraph format
for bin in range(0, len(cvg_corr), step):
value = np.mean(cvg_corr[bin:min(bin + step, end)])
if value > 0:
writeStart = start + bin
writeEnd = min(start + bin + step, end)
_file.write("%s\t%d\t%d\t%.1f\n" % (chrNameBit, writeStart,
writeEnd, value))
tempFileName = _file.name
_file.close()
return tempFileName
def numCopiesOfRead(value):
"""
Based int he R_gc value, decides
whether to keep, duplicate, triplicate or delete the read.
It returns an integer, that tells the number of copies of the read
that should be keep.
>>> np.random.seed(1)
>>> numCopiesOfRead(0.8)
1
>>> numCopiesOfRead(2.5)
2
>>> numCopiesOfRead(None)
1
"""
copies = 1
if value:
copies = int(value) + (1 if np.random.rand() < value % 1 else 0)
return copies
def writeCorrectedSam_wrapper(args):
return writeCorrectedSam_worker(*args)
def writeCorrectedSam_worker(chrNameBam, chrNameBit, start, end,
step=None,
tag_but_not_change_number=False,
verbose=True):
r"""
Writes a BAM file, deleting and adding some reads in order to compensate
for the GC bias. **This is a stochastic method.**
>>> np.random.seed(1)
>>> test = Tester()
>>> args = test.testWriteCorrectedSam()
>>> tempFile = writeCorrectedSam_worker(*args, \
... tag_but_not_change_number=True, verbose=False)
>>> try:
... import StringIO
... except ImportError:
... from io import StringIO
>>> ostdout = sys.stdout
>>> import tempfile
>>> sys.stdout = tempfile.TemporaryFile()
>>> idx = pysam.index(tempFile)
>>> sys.stdout = ostdout
>>> bam = pysam.Samfile(tempFile)
>>> [dict(r.tags)['YN'] for r in bam.fetch(args[0], 200, 250)]
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1]
>>> res = os.remove(tempFile)
>>> res = os.remove(tempFile+".bai")
>>> tempFile = \
... writeCorrectedSam_worker(*test.testWriteCorrectedSam_paired(),\
... tag_but_not_change_number=True, verbose=False)
>>> sys.stdout = tempfile.TemporaryFile()
>>> idx = pysam.index(tempFile)
>>> sys.stdout = ostdout
>>> bam = pysam.Samfile(tempFile)
>>> [dict(r.tags)['YN'] for r in bam.fetch('chr2L', 0, 50)]
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
>>> res = os.remove(tempFile)
>>> res = os.remove(tempFile+".bai")
"""
global R_gc
fragmentLength = len(R_gc) - 1
if verbose:
print("Sam for %s %s %s " % (chrNameBit, start, end))
i = 0
tbit = py2bit.open(global_vars['2bit'])
bam = openBam(global_vars['bam'])
tempFileName = utilities.getTempFileName(suffix='.bam')
outfile = pysam.Samfile(tempFileName, 'wb', template=bam)
startTime = time.time()
matePairs = {}
read_repetitions = 0
removed_duplicated_reads = 0
# cache data
# r.flag & 4 == 0 is to filter unmapped reads that
# have a genomic position
reads = [r for r in bam.fetch(chrNameBam, start, end)
if r.pos > start and r.flag & 4 == 0]
r_index = -1
for read in reads:
if read.pos <= start or read.is_unmapped:
continue
r_index += 1
copies = None
gc = None
# check if a mate has already been procesed
# to apply the same correction
try:
copies = matePairs[read.qname]['copies']
gc = matePairs[read.qname]['gc']
del matePairs[read.qname]
except:
# this exception happens when a mate is
# not present. This could
# happen because of removal of the mate
# by some filtering
gc = getReadGCcontent(tbit, read, fragmentLength,
chrNameBit)
if gc:
copies = numCopiesOfRead(float(1) / R_gc[gc])
else:
copies = 1
# is this read in the same orientation and position as the previous?
if gc and r_index > 0 and read.pos == reads[r_index - 1].pos \
and read.is_reverse == reads[r_index - 1].is_reverse \
and read.pnext == reads[r_index - 1].pnext:
read_repetitions += 1
if read_repetitions >= global_vars['max_dup_gc'][gc]:
copies = 0 # in other words do not take into account this read
removed_duplicated_reads += 1
else:
read_repetitions = 0
readName = read.qname
# Each tag is a tuple of (tag name, value, type)
# Note that get_tags() returns ord(type) rather than type and this must
# be fixed!
# It turns out that the "with_value_type" option only started working in
# pysam-0.8.4, so we can't reliably add tags on earlier versions without
# potentially creating BAM files that break HTSJDK/IGV/etc.
readTag = read.get_tags(with_value_type=True)
replace_tags = False
if len(readTag) > 0:
if len(readTag[0]) == 3:
if type(readTag[2]) is int:
readTag = [(x[0], x[1], chr(x[2])) for x in readTag]
replace_tags = True
else:
replace_tags = True
if gc:
GC = int(100 * np.round(float(gc) / fragmentLength,
decimals=2))
readTag.append(
('YC', float(round(float(1) / R_gc[gc], 2)), "f"))
readTag.append(('YN', copies, "i"))
else:
GC = -1
readTag.append(('YG', GC, "i"))
if replace_tags:
read.set_tags(readTag)
if read.is_paired and read.is_proper_pair \
and not read.mate_is_unmapped \
and not read.is_reverse:
matePairs[readName] = {'copies': copies,
'gc': gc}
"""
outfile.write(read)
"""
if tag_but_not_change_number:
outfile.write(read)
continue
for numCop in range(1, copies + 1):
# the read has to be renamed such that newly
# formed pairs will match
if numCop > 1:
read.qname = readName + "_%d" % (numCop)
outfile.write(read)
if verbose:
if i % 500000 == 0 and i > 0:
endTime = time.time()
print("{}, processing {} ({:.1f} per sec) reads "
"@ {}:{}-{}".format(multiprocessing.current_process().name,
i, i / (endTime - startTime),
chrNameBit, start, end))
i += 1
outfile.close()
if verbose:
endTime = time.time()
print("{}, processing {} ({:.1f} per sec) reads "
"@ {}:{}-{}".format(multiprocessing.current_process().name,
i, i / (endTime - startTime),
chrNameBit, start, end))
percentage = float(removed_duplicated_reads) * 100 / len(reads) \
if len(reads) > 0 else 0
print("duplicated reads removed %d of %d (%.2f) " %
(removed_duplicated_reads, len(reads), percentage))
return tempFileName
def getFragmentFromRead(read, defaultFragmentLength, extendPairedEnds=True):
"""
The read has to be pysam object.
The following values are defined (for forward reads)::
|-- -- read.tlen -- --|
|-- read.alen --|
-----|===============>------------<==============|----
| | |
read.pos read.aend read.pnext
and for reverse reads
|-- -- read.tlen -- --|
|-- read.alen --|
-----|===============>-----------<===============|----
| | |
read.pnext read.pos read.aend
this is a sketch of a pair-end reads
The function returns the fragment start and end, either
using the paired end information (if available) or
extending the read in the appropriate direction if this
is single-end.
Parameters
----------
read : pysam read object
Returns
-------
tuple
(fragment start, fragment end)
"""
# convert reads to fragments
# this option indicates that the paired ends correspond
# to the fragment ends
# condition read.tlen < maxPairedFragmentLength is added to avoid read pairs
# that span thousands of base pairs
if extendPairedEnds is True and read.is_paired and 0 < abs(read.tlen) < 1000:
if read.is_reverse:
fragmentStart = read.pnext
fragmentEnd = read.aend
else:
fragmentStart = read.pos
# the end of the fragment is defined as
# the start of the forward read plus the insert length
fragmentEnd = read.pos + read.tlen
else:
if defaultFragmentLength <= read.aend - read.pos:
fragmentStart = read.pos
fragmentEnd = read.aend
else:
if read.is_reverse:
fragmentStart = read.aend - defaultFragmentLength
fragmentEnd = read.aend
else:
fragmentStart = read.pos
fragmentEnd = read.pos + defaultFragmentLength
return fragmentStart, fragmentEnd
def run_shell_command(command):
"""
Runs the given shell command. Report
any errors found.
"""
try:
subprocess.check_call(command, shell=True)
except subprocess.CalledProcessError as error:
sys.stderr.write('Error{}\n'.format(error))
exit(1)
except Exception as error:
sys.stderr.write('Error: {}\n'.format(error))
exit(1)
def main(args=None):
args = process_args(args)
global F_gc, N_gc, R_gc
data = np.loadtxt(args.GCbiasFrequenciesFile.name)
F_gc = data[:, 0]
N_gc = data[:, 1]
R_gc = data[:, 2]
global global_vars
global_vars = {}
global_vars['2bit'] = args.genome
global_vars['bam'] = args.bamfile
# compute the probability to find more than one read (a redundant read)
# at a certain position based on the gc of the read fragment
# the binomial function is used for that
max_dup_gc = [binom.isf(1e-7, F_gc[x], 1.0 / N_gc[x])
if F_gc[x] > 0 and N_gc[x] > 0 else 1
for x in range(len(F_gc))]
global_vars['max_dup_gc'] = max_dup_gc
tbit = py2bit.open(global_vars['2bit'])
bam, mapped, unmapped, stats = openBam(args.bamfile, returnStats=True, nThreads=args.numberOfProcessors)
global_vars['genome_size'] = sum(tbit.chroms().values())
global_vars['total_reads'] = mapped
global_vars['reads_per_bp'] = \
float(global_vars['total_reads']) / args.effectiveGenomeSize
# apply correction
print("applying correction")
# divide the genome in fragments containing about 4e5 reads.
# This amount of reads takes about 20 seconds
# to process per core (48 cores, 256 Gb memory)
chunkSize = int(4e5 / global_vars['reads_per_bp'])
# chromSizes: list of tuples
chromSizes = [(bam.references[i], bam.lengths[i])
for i in range(len(bam.references))]
regionStart = 0
if args.region:
chromSizes, regionStart, regionEnd, chunkSize = \
mapReduce.getUserRegion(chromSizes, args.region,
max_chunk_size=chunkSize)
print("genome partition size for multiprocessing: {}".format(chunkSize))
print("using region {}".format(args.region))
mp_args = []
bedGraphStep = args.binSize
chrNameBitToBam = tbitToBamChrName(list(tbit.chroms().keys()), bam.references)
chrNameBamToBit = dict([(v, k) for k, v in chrNameBitToBam.items()])
print(chrNameBitToBam, chrNameBamToBit)
c = 1
for chrom, size in chromSizes:
start = 0 if regionStart == 0 else regionStart
for i in range(start, size, chunkSize):
try:
chrNameBamToBit[chrom]
except KeyError:
print("no sequence information for ")
"chromosome {} in 2bit file".format(chrom)
print("Reads in this chromosome will be skipped")
continue
length = min(size, i + chunkSize)
mp_args.append((chrom, chrNameBamToBit[chrom], i, length,
bedGraphStep))
c += 1
pool = multiprocessing.Pool(args.numberOfProcessors)
if args.correctedFile.name.endswith('bam'):
if len(mp_args) > 1 and args.numberOfProcessors > 1:
print(("using {} processors for {} "
"number of tasks".format(args.numberOfProcessors,
len(mp_args))))
res = pool.map_async(
writeCorrectedSam_wrapper, mp_args).get(9999999)
else:
res = list(map(writeCorrectedSam_wrapper, mp_args))
if len(res) == 1:
command = "cp {} {}".format(res[0], args.correctedFile.name)
run_shell_command(command)
else:
print("concatenating (sorted) intermediate BAMs")
header = pysam.Samfile(res[0])
of = pysam.Samfile(args.correctedFile.name, "wb", template=header)
header.close()
for f in res:
f = pysam.Samfile(f)
for e in f.fetch(until_eof=True):
of.write(e)
f.close()
of.close()
print("indexing BAM")
pysam.index(args.correctedFile.name)
for tempFileName in res:
os.remove(tempFileName)
if args.correctedFile.name.endswith('bg') or \
args.correctedFile.name.endswith('bw'):
if len(mp_args) > 1 and args.numberOfProcessors > 1:
res = pool.map_async(writeCorrected_wrapper, mp_args).get(9999999)
else:
res = list(map(writeCorrected_wrapper, mp_args))
oname = args.correctedFile.name
args.correctedFile.close()
if oname.endswith('bg'):
f = open(oname, 'wb')
for tempFileName in res:
if tempFileName:
shutil.copyfileobj(open(tempFileName, 'rb'), f)
os.remove(tempFileName)
f.close()
else:
chromSizes = [(k, v) for k, v in tbit.chroms().items()]
writeBedGraph.bedGraphToBigWig(chromSizes, res, oname)
class Tester():
def __init__(self):
import os
self.root = os.path.dirname(os.path.abspath(__file__)) + "/test/test_corrGC/"
self.tbitFile = self.root + "sequence.2bit"
self.bamFile = self.root + "test.bam"
self.chrNameBam = '2L'
self.chrNameBit = 'chr2L'
bam, mapped, unmapped, stats = openBam(self.bamFile, returnStats=True)
tbit = py2bit.open(self.tbitFile)
global debug
debug = 0
global global_vars
global_vars = {'2bit': self.tbitFile,
'bam': self.bamFile,
'filter_out': None,
'extra_sampling_file': None,
'max_reads': 5,
'min_reads': 0,
'min_reads': 0,
'reads_per_bp': 0.3,
'total_reads': mapped,
'genome_size': sum(tbit.chroms().values())}
def testWriteCorrectedChunk(self):
""" prepare arguments for test
"""
global R_gc, R_gc_min, R_gc_max
R_gc = np.loadtxt(self.root + "R_gc_paired.txt")
global_vars['max_dup_gc'] = np.ones(301)
start = 200
end = 300
bedGraphStep = 25
return (self.chrNameBam,
self.chrNameBit, start, end, bedGraphStep)
def testWriteCorrectedSam(self):
""" prepare arguments for test
"""
global R_gc, R_gc_min, R_gc_max
R_gc = np.loadtxt(self.root + "R_gc_paired.txt")
global_vars['max_dup_gc'] = np.ones(301)
start = 200
end = 250
return (self.chrNameBam,
self.chrNameBit, start, end)
def testWriteCorrectedSam_paired(self):
""" prepare arguments for test.
"""
global R_gc, R_gc_min, R_gc_max
R_gc = np.loadtxt(self.root + "R_gc_paired.txt")
start = 0
end = 500
global global_vars
global_vars['bam'] = self.root + "paired.bam"
return 'chr2L', 'chr2L', start, end
if __name__ == "__main__":
main()
|