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import deeptools.bigwigCompare as bwComp
import deeptools.multiBigwigSummary as bwCorr
import numpy as np
import numpy.testing as nt
import os.path
from os import unlink
ROOT = os.path.dirname(os.path.abspath(__file__)) + "/test_data/"
BIGWIG_A = ROOT + "testA_skipNAs.bw"
BIGWIG_B = ROOT + "testB_skipNAs.bw"
BIGWIG_C = ROOT + "test1.bw.bw"
"""
The distribution of reads for the bam file is:
0 100 200
|------------------------------------------------------------|
testA.bam 3R ==============>
<==============
testB.bam 3R <============== ==============>
==============>
==============>
The resulting bigwig files are as follows:
testA_skipNas:
3R 100 200 1
chr_cigar 0 50 2
testB_skipNas:
3R 50 150 1
3R 150 200 2
"""
def test_bigwigCompare():
outfile = '/tmp/result.bg'
args = "-b1 {} -b2 {} -o {} --operation add --outFileFormat bedgraph".format(BIGWIG_A, BIGWIG_B, outfile).split()
bwComp.main(args)
_foo = open(outfile, 'r')
resp = _foo.readlines()
_foo.close()
expected = ['3R\t0\t50\t0\n', '3R\t50\t100\t1\n', '3R\t100\t150\t2\n', '3R\t150\t200\t3\n']
assert resp == expected, "{} != {}".format(resp, expected)
unlink(outfile)
def test_bigwigCompare_skipnas():
outfile = '/tmp/result.bg'
args = "-b1 {} -b2 {} -o {} --operation add --skipNAs " \
"--outFileFormat bedgraph".format(BIGWIG_A, BIGWIG_B, outfile).split()
bwComp.main(args)
_foo = open(outfile, 'r')
resp = _foo.readlines()
_foo.close()
expected = ['3R\t100\t150\t2\n', '3R\t150\t200\t3\n']
assert resp == expected, "{} != {}".format(resp, expected)
unlink(outfile)
def test_bigwigCompare_skipZeroOverZero():
outfile = '/tmp/result.bg"'
args = "-b1 {} -b2 {} -o {} --skipZeroOverZero --pseudocount 1 3 --outFileFormat bedgraph".format(BIGWIG_A, BIGWIG_A, outfile).split()
bwComp.main(args)
_foo = open(outfile, 'r')
resp = _foo.readlines()
_foo.close()
expected = ['3R\t100\t200\t-1\n']
assert resp == expected, "{} != {}".format(resp, expected)
unlink(outfile)
def test_multiBigwigSummary():
outfile = '/tmp/result.bg'
args = "bins -b {} {} --binSize 50 -o {}".format(BIGWIG_A, BIGWIG_B, outfile).split()
bwCorr.main(args)
resp = np.load(outfile)
matrix = resp['matrix']
labels = resp['labels']
nt.assert_equal(matrix, np.array([[np.nan, np.nan],
[np.nan, 1.],
[1., 1.],
[1., 2.]]))
nt.assert_equal(labels, ['testA_skipNAs.bw', 'testB_skipNAs.bw'])
unlink(outfile)
def test_multiBigwigSummary_outrawcounts():
"""
Test multiBigwigSummary raw counts output
"""
outfile = '/tmp/result.bg'
args = "bins -b {} {} --binSize 50 -o /tmp/null --outRawCounts {} ".format(BIGWIG_A, BIGWIG_B, outfile).split()
bwCorr.main(args)
_foo = open(outfile, 'r')
resp = _foo.read()
_foo.close()
expected = """#'chr' 'start' 'end' 'testA_skipNAs.bw' 'testB_skipNAs.bw'
3R 0 50 nan nan
3R 50 100 nan 1.0
3R 100 150 1.0 1.0
3R 150 200 1.0 2.0
"""
assert resp == expected, "{} != {}".format(resp, expected)
unlink(outfile)
unlink("/tmp/null")
def test_multiBigwigSummary_gtf():
outfile = '/tmp/_test.npz'
args = "BED-file -b {0} {0} --BED {1}/test.gtf -o {2}".format(BIGWIG_C, ROOT, outfile).split()
bwCorr.main(args)
resp = np.load(outfile)
matrix = resp['matrix']
labels = resp['labels']
nt.assert_equal(labels, ['test1.bw.bw', 'test1.bw.bw'])
nt.assert_allclose(matrix, np.array([[27.475, 27.475],
[27.31248719, 27.31248719]]))
unlink(outfile)
def test_multiBigwigSummary_metagene():
outfile = '/tmp/_test.npz'
args = "BED-file --metagene -b {0} {0} --BED {1}/test.gtf -o {2}".format(BIGWIG_C, ROOT, outfile).split()
bwCorr.main(args)
resp = np.load(outfile)
matrix = resp['matrix']
labels = resp['labels']
nt.assert_equal(labels, ['test1.bw.bw', 'test1.bw.bw'])
nt.assert_allclose(matrix, np.array([[20.28956028, 20.28956028],
[22.1923501, 22.1923501]]))
unlink(outfile)
|
