Esempio n. 1
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def test_auto_dom_extended():

    fam = make_fam2()
    efam = EvalFamily(fam)
    assert [f.affected for f in efam.subjects] == [False, True, True, False, True, False]

    efam.gt_types = [Family.HOM_REF, Family.HET, Family.HET, Family.HOM_REF, Family.HET, Family.HOM_REF]

    assert efam.auto_dom()

    # unaffected is het:
    efam.gt_types[0] = Family.HET
    assert not efam.auto_dom()
    assert efam.auto_dom(only_affected=False)
    efam.gt_types[0] = Family.HOM_REF

    assert efam.auto_dom()
    efam.gt_depths = [9] * 6
    assert not efam.auto_dom(min_depth=10)

    # check with no unaffecteds
    for f in efam.subjects:
        f.affected = True
    assert not efam.auto_dom()

    # check with all unaffecteds
    for f in efam.subjects:
        f.affected = False
    assert not efam.auto_dom()
Esempio n. 2
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def test_auto_dom_extended():

    fam = make_fam2()
    efam = EvalFamily(fam)
    assert [f.affected
            for f in efam.subjects] == [False, True, True, False, True, False]

    efam.gt_types = [
        Family.HOM_REF, Family.HET, Family.HET, Family.HOM_REF, Family.HET,
        Family.HOM_REF
    ]

    assert efam.auto_dom()

    # unaffected is het:
    efam.gt_types[0] = Family.HET
    assert not efam.auto_dom()
    assert efam.auto_dom(only_affected=False)
    efam.gt_types[0] = Family.HOM_REF

    assert efam.auto_dom()
    efam.gt_depths = [9] * 6
    assert not efam.auto_dom(min_depth=10)

    # check with no unaffecteds
    for f in efam.subjects:
        f.affected = True
    assert not efam.auto_dom()

    # check with all unaffecteds
    for f in efam.subjects:
        f.affected = False
    assert not efam.auto_dom()
Esempio n. 3
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def make_fam(n_affecteds, n_unaffecteds, n_unknowns, id="xxx"):

    samples = []
    for i in range(n_affecteds):
        samples.append(
            Sample('affected_%d' % i,
                   affected=True,
                   sex=random.randint(1, 2),
                   name='affected_%d' % i))
    for i in range(n_unaffecteds):
        samples.append(
            Sample('unaffected_%d' % i,
                   affected=False,
                   sex=random.randint(1, 2),
                   name='affected_%d' % i))
    for i in range(n_unknowns):
        samples.append(
            Sample('unknown_%d' % i,
                   affected=None,
                   sex=random.randint(1, 2),
                   name='affected_%d' % i))

    for i in range(int((n_affecteds + n_affecteds + n_unknowns) / 2)):

        sample = random.choice(samples)
        if random.random() < 0.9:
            try:
                sample.dad = random.choice([
                    s for s in samples if not s == sample and s.sex == 'male'
                ])
            except IndexError:
                pass
        if random.random() < 0.9:
            try:
                sample.mom = random.choice([
                    s for s in samples if not s == sample and s.sex == 'female'
                ])
            except IndexError:
                pass

    fam = EvalFamily(Family(samples, 'fam_%s' % id))
    fam.gt_types = [random.randrange(0, 4) for _ in range(len(samples))]
    fam.gt_depths = [random.randrange(0, 100) for _ in range(len(samples))]
    fam.gt_phred_ll_homref = [
        random.randrange(0, 100) for _ in range(len(samples))
    ]
    fam.gt_phred_ll_het = [
        random.randrange(0, 100) for _ in range(len(samples))
    ]
    fam.gt_phred_ll_homalt = [
        random.randrange(0, 100) for _ in range(len(samples))
    ]
    fam.gt_quals = [random.randrange(5, 100) for _ in range(len(samples))]
    return fam
Esempio n. 4
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def test_auto_rec_extended():
    fam = make_fam1()

    efam = EvalFamily(fam)
    efam.gt_types = [
        Family.HET, Family.HET, Family.HOM_ALT, Family.HET, Family.HET,
        Family.HET
    ]
    assert efam.auto_rec()

    #if grandpa is affected it is no longer autosomal recessive
    efam.subjects[5].affected = True
    assert not efam.auto_rec()
    efam.subjects[5].affected = False

    # set both kids to hom_alt:
    efam.gt_types[3] = Family.HOM_ALT
    assert not efam.auto_rec()
    assert efam.auto_rec(only_affected=False)

    # set unaffected kid back:
    efam.gt_types[3] = Family.HET
    # expected that is is auto_rec
    assert efam.auto_rec()
    # but it's not if we set all depths to 9 and have min_depth of 10
    efam.gt_depths = [9] * 6
    assert not efam.auto_rec(min_depth=10)

    efam.gt_depths[2] = 1000
    # even if affected has high depth
    assert not efam.auto_rec(min_depth=10)

    # passes if we meet the minimum depth
    efam.gt_depths = [100] * 6
    assert efam.auto_rec(min_depth=10)

    # check if we have no affecteds:
    efam.subjects[2].affected = False
    assert not efam.auto_rec(min_depth=10)
Esempio n. 5
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def test_auto_rec_extended():
    fam = make_fam1()

    efam = EvalFamily(fam)
    efam.gt_types = [Family.HET, Family.HET, Family.HOM_ALT, Family.HET, Family.HET, Family.HET]
    assert efam.auto_rec()

    #if grandpa is affected it is no longer autosomal recessive
    efam.subjects[5].affected = True
    assert not efam.auto_rec()
    efam.subjects[5].affected = False

    # set both kids to hom_alt:
    efam.gt_types[3] = Family.HOM_ALT
    assert not efam.auto_rec()
    assert efam.auto_rec(only_affected=False)

    # set unaffected kid back:
    efam.gt_types[3] = Family.HET
    # expected that is is auto_rec
    assert efam.auto_rec()
    # but it's not if we set all depths to 9 and have min_depth of 10
    efam.gt_depths = [9] * 6
    assert not efam.auto_rec(min_depth=10)

    efam.gt_depths[2] = 1000
    # even if affected has high depth
    assert not efam.auto_rec(min_depth=10)

    # passes if we meet the minimum depth
    efam.gt_depths = [100] * 6
    assert efam.auto_rec(min_depth=10)

    # check if we have no affecteds:
    efam.subjects[2].affected = False
    assert not efam.auto_rec(min_depth=10)
Esempio n. 6
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def make_fam(n_affecteds, n_unaffecteds, n_unknowns, id="xxx"):


    samples = []
    for i in range(n_affecteds):
        samples.append(Sample('affected_%d' % i, affected=True,
            sex=random.randint(1, 2), name='affected_%d' % i))
    for i in range(n_unaffecteds):
        samples.append(Sample('unaffected_%d' % i, affected=False,
            sex=random.randint(1, 2), name='affected_%d' % i))
    for i in range(n_unknowns):
        samples.append(Sample('unknown_%d' % i, affected=None,
            sex=random.randint(1, 2), name='affected_%d' % i))

    for i in range(int((n_affecteds + n_affecteds + n_unknowns) / 2)):

        sample = random.choice(samples)
        if random.random() < 0.9:
            try:
                sample.dad = random.choice([s for s in samples if not s == sample and s.sex == 'male'])
            except IndexError:
                pass
        if random.random() < 0.9:
            try:
                sample.mom = random.choice([s for s in samples if not s == sample and s.sex == 'female'])
            except IndexError:
                pass

    fam = EvalFamily(Family(samples, 'fam_%s' % id))
    fam.gt_types = [random.randrange(0, 4) for _ in range(len(samples))]
    fam.gt_depths = [random.randrange(0, 100) for _ in range(len(samples))]
    fam.gt_phred_ll_homref = [random.randrange(0, 100) for _ in range(len(samples))]
    fam.gt_phred_ll_het = [random.randrange(0, 100) for _ in range(len(samples))]
    fam.gt_phred_ll_homalt = [random.randrange(0, 100) for _ in range(len(samples))]
    fam.gt_quals = [random.randrange(5, 100) for _ in range(len(samples))]
    return fam