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#!/usr/bin/env python
# Time-stamp: <2020-11-30 14:12:58 Tao Liu>
import io
import unittest
from numpy.testing import assert_equal, assert_almost_equal, assert_array_equal
from MACS3.Signal.ScoreTrack import *
from MACS3.Signal.BedGraph import bedGraphTrackI
class Test_TwoConditionScores(unittest.TestCase):
def setUp(self):
self.t1bdg = bedGraphTrackI()
self.t2bdg = bedGraphTrackI()
self.c1bdg = bedGraphTrackI()
self.c2bdg = bedGraphTrackI()
self.test_regions1 = [(b"chrY",0,70,0.00,0.01),
(b"chrY",70,80,7.00,0.5),
(b"chrY",80,150,0.00,0.02)]
self.test_regions2 = [(b"chrY",0,75,20.0,4.00),
(b"chrY",75,90,35.0,6.00),
(b"chrY",90,150,10.0,15.00)]
for a in self.test_regions1:
self.t1bdg.safe_add_loc(a[0],a[1],a[2],a[3])
self.c1bdg.safe_add_loc(a[0],a[1],a[2],a[4])
for a in self.test_regions2:
self.t2bdg.safe_add_loc(a[0],a[1],a[2],a[3])
self.c2bdg.safe_add_loc(a[0],a[1],a[2],a[4])
self.twoconditionscore = TwoConditionScores( self.t1bdg,
self.c1bdg,
self.t2bdg,
self.c2bdg,
1.0,
1.0 )
self.twoconditionscore.build()
self.twoconditionscore.finalize()
(self.cat1,self.cat2,self.cat3) = self.twoconditionscore.call_peaks(min_length=10, max_gap=10, cutoff=3)
class Test_ScoreTrackII(unittest.TestCase):
def setUp(self):
# for initiate scoretrack
self.test_regions1 = [(b"chrY",10,100,10),
(b"chrY",60,10,10),
(b"chrY",110,15,20),
(b"chrY",160,5,20),
(b"chrY",210,20,5)]
self.treat_edm = 10
self.ctrl_edm = 5
# for different scoring method
self.p_result = [60.49, 0.38, 0.08, 0.0, 6.41] # -log10(p-value), pseudo count 1 added
self.q_result = [58.17, 0.0, 0.0, 0.0, 5.13] # -log10(q-value) from BH, pseudo count 1 added
self.l_result = [58.17, 0.0, -0.28, -3.25, 4.91] # log10 likelihood ratio, pseudo count 1 added
self.f_result = [0.96, 0.00, -0.12, -0.54, 0.54] # note, pseudo count 1 would be introduced.
self.d_result = [90.00, 0, -5.00, -15.00, 15.00]
self.m_result = [10.00, 1.00, 1.50, 0.50, 2.00]
# for norm
self.norm_T = np.array([[ 10, 100, 20, 0],
[ 60, 10, 20, 0],
[110, 15, 40, 0],
[160, 5, 40, 0],
[210, 20, 10, 0]]).transpose()
self.norm_C = np.array([[ 10, 50, 10, 0],
[ 60, 5, 10, 0],
[110, 7.5, 20, 0],
[160, 2.5, 20, 0],
[210, 10, 5, 0]]).transpose()
self.norm_M = np.array([[ 10, 10, 2, 0],
[ 60, 1, 2, 0],
[110, 1.5, 4, 0],
[160, 0.5, 4, 0],
[210, 2, 1, 0]]).transpose()
self.norm_N = np.array([[ 10, 100, 10, 0], # note precision lost
[ 60, 10, 10, 0],
[110, 15, 20, 0],
[160, 5, 20, 0],
[210, 20, 5, 0]]).transpose()
# for write_bedGraph
self.bdg1 = """chrY 0 10 100.00000
chrY 10 60 10.00000
chrY 60 110 15.00000
chrY 110 160 5.00000
chrY 160 210 20.00000
"""
self.bdg2 = """chrY 0 60 10.00000
chrY 60 160 20.00000
chrY 160 210 5.00000
"""
self.bdg3 = """chrY 0 10 60.48912
chrY 10 60 0.37599
chrY 60 110 0.07723
chrY 110 160 0.00006
chrY 160 210 6.40804
"""
# for peak calls
self.peak1 = """chrY 0 60 peak_1 60.4891
chrY 160 210 peak_2 6.40804
"""
self.summit1 = """chrY 5 6 peak_1 60.4891
chrY 185 186 peak_2 6.40804
"""
self.xls1 ="""chr start end length abs_summit pileup -log10(pvalue) fold_enrichment -log10(qvalue) name
chrY 1 60 60 6 100 63.2725 9.18182 -1 MACS_peak_1
chrY 161 210 50 186 20 7.09102 3.5 -1 MACS_peak_2
"""
def assertListAlmostEqual ( self, a, b, places =2 ):
return all( [self.assertAlmostEqual(x, y, places=places) for (x, y) in zip( a, b)] )
def test_compute_scores(self):
s1 = ScoreTrackII( self.treat_edm, self.ctrl_edm )
s1.add_chromosome( b"chrY", 5 )
for a in self.test_regions1:
s1.add( a[0],a[1],a[2],a[3] )
s1.set_pseudocount ( 1.0 )
s1.change_score_method( ord('p') )
r = s1.get_data_by_chr(b"chrY")
self.assertListAlmostEqual( [round(x,2) for x in r[3]], self.p_result )
s1.change_score_method( ord('q') )
r = s1.get_data_by_chr(b"chrY")
self.assertListAlmostEqual( [round(x,2) for x in list(r[3])], self.q_result )
s1.change_score_method( ord('l') )
r = s1.get_data_by_chr(b"chrY")
self.assertListAlmostEqual( [round(x,2) for x in list(r[3])], self.l_result )
s1.change_score_method( ord('f') )
r = s1.get_data_by_chr(b"chrY")
self.assertListAlmostEqual( [round(x,2) for x in list(r[3])], self.f_result )
s1.change_score_method( ord('d') )
r = s1.get_data_by_chr(b"chrY")
self.assertListAlmostEqual( [round(x,2) for x in list(r[3])], self.d_result )
s1.change_score_method( ord('m') )
r = s1.get_data_by_chr(b"chrY")
self.assertListAlmostEqual( [round(x,2) for x in list(r[3])], self.m_result )
def test_normalize(self):
s1 = ScoreTrackII( self.treat_edm, self.ctrl_edm )
s1.add_chromosome( b"chrY", 5 )
for a in self.test_regions1:
s1.add( a[0],a[1],a[2],a[3] )
s1.change_normalization_method( ord('T') )
r = s1.get_data_by_chr(b"chrY")
assert_array_equal( r, self.norm_T )
s1.change_normalization_method( ord('C') )
r = s1.get_data_by_chr(b"chrY")
assert_array_equal( r, self.norm_C )
s1.change_normalization_method( ord('M') )
r = s1.get_data_by_chr(b"chrY")
assert_array_equal( r, self.norm_M )
s1.change_normalization_method( ord('N') )
r = s1.get_data_by_chr(b"chrY")
assert_array_equal( r, self.norm_N )
def test_writebedgraph ( self ):
s1 = ScoreTrackII( self.treat_edm, self.ctrl_edm )
s1.add_chromosome( b"chrY", 5 )
for a in self.test_regions1:
s1.add( a[0],a[1],a[2],a[3] )
s1.change_score_method( ord('p') )
strio = io.StringIO()
s1.write_bedGraph( strio, "NAME", "DESC", 1 )
self.assertEqual( strio.getvalue(), self.bdg1 )
strio = io.StringIO()
s1.write_bedGraph( strio, "NAME", "DESC", 2 )
self.assertEqual( strio.getvalue(), self.bdg2 )
strio = io.StringIO()
s1.write_bedGraph( strio, "NAME", "DESC", 3 )
self.assertEqual( strio.getvalue(), self.bdg3 )
def test_callpeak ( self ):
s1 = ScoreTrackII( self.treat_edm, self.ctrl_edm )
s1.add_chromosome( b"chrY", 5 )
for a in self.test_regions1:
s1.add( a[0],a[1],a[2],a[3] )
s1.change_score_method( ord('p') )
p = s1.call_peaks( cutoff = 0.10, min_length=10, max_gap=10 )
strio = io.StringIO()
p.write_to_bed( strio, trackline = False )
self.assertEqual( strio.getvalue(), self.peak1 )
strio = io.StringIO()
p.write_to_summit_bed( strio, trackline = False )
self.assertEqual( strio.getvalue(), self.summit1 )
strio = io.StringIO()
p.write_to_xls( strio )
self.assertEqual( strio.getvalue(), self.xls1 )
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