Exemple #1
0
 def test_draw_density_plot(self):
     fhand = NamedTemporaryFile(suffix='.png')
     data = {
         'y': array('f', numpy.random.normal(40, 5, 40000)),
         'x': array('f', numpy.random.normal(40, 5, 40000))
     }
     draw_density_plot(data['x'], data['y'], fhand, n_bins=200)
Exemple #2
0
def calc_recomb_rates_along_chroms(vcf_fpath, pop_type, samples=None,
                                   min_phys_dist=1000, max_phys_dist=50000):
    reader = pyvcfReader(open(vcf_fpath))
    random_reader = pyvcfReader(open(vcf_fpath))

    diffs_from_r_expected = []
    diffs_distort =[]
    recomb_rates = []
    diffs_xs = []
    diffs_ys = []
    to_return = []
    r_xs = []
    r_ys = []
    r_dist_color = []
    #samples = reader.samples
    #samples = [sample for sample in samples if sample[0] == '4']
    for snv in reader:
        pos = snv.POS
        chrom = snv.CHROM
        start = pos - max_phys_dist
        if start < 0:
            start = 0
        end = pos - min_phys_dist
        if end < 0:
            end = 0
        if end > 0:
            snvs_prev = random_reader.fetch(chrom=chrom, start=start, end=end)
        else:
            snvs_prev = iter([])
        start = pos + min_phys_dist
        end = pos + max_phys_dist
        snvs_after = random_reader.fetch(chrom=chrom, start=start, end=end)

        if samples is None:
            calls1 = snv.samples
        else:
            calls1 = [call for call in snv.samples if call.sample in samples]
        recombs = []
        for snv_2 in chain(snvs_prev, snvs_after):
            dist = abs(pos - snv_2.POS)

            if samples is None:
                calls2 = snv_2.samples
            else:
                calls2 = [call for call in snv_2.samples if call.sample in samples]

            result = _calc_recomb_rate(calls1, calls2, pop_type)
            if result:
                recomb, haplo_count = result
            else:
                recomb, haplo_count = None, None
            if haplo_count:
                diff_from_r_expected = ((abs(haplo_count.AB - haplo_count.ab) +
                                         abs(haplo_count.Ab - haplo_count.aB)) /
                                         sum(haplo_count))
                diff_distort = ((abs((haplo_count.Ab + haplo_count.AB) - (haplo_count.ab + haplo_count.aB)) +
                                abs((haplo_count.AB + haplo_count.aB) - (haplo_count.ab + haplo_count.Ab))) /
                                sum(haplo_count))
                diffs_xs.append(diff_from_r_expected)
                diffs_ys.append(diff_distort)
                diffs_from_r_expected.append(diff_from_r_expected)
                diffs_distort.append(diff_distort)
            if recomb is not None:
                recomb_rates.append(recomb)
                r_xs.append(recomb)
                r_ys.append(diff_from_r_expected)
                r_dist_color.append(diff_distort)
                #if 0.6 > recomb > 0.2 and  diff_from_r_expected > 0.9:
                #    print 'pau->', haplo_count, recomb, diff_from_r_expected
            #if recomb > 0.5:
            if recomb is None:
                continue
            print snv.CHROM, snv.POS, snv_2.CHROM, snv_2.POS, recomb, diff_from_r_expected, diff_distort
            recombs.append((dist, recomb))
        if recombs:
            to_return.append([chrom, pos, recombs])
    from crumbs.plot import build_histogram, draw_density_plot
    print 'hola'
    from os.path import join as pjoin

    dir_ = '/home/jose/tmp/rils/results/'
    fpath = pjoin(dir_, 'diffs_from_r.png')
    build_histogram(diffs_from_r_expected, open(fpath, 'w'), bins=30)
    fpath = pjoin(dir_, 'diffs_distort.png')
    build_histogram(diffs_distort, open(fpath, 'w'), bins=30)
    fpath = pjoin(dir_, 'recomb_rates.png')
    build_histogram(recomb_rates, open(fpath, 'w'), bins=30, log=True)
    fpath = pjoin(dir_, 'diffs_density.png')
    draw_density_plot(diffs_xs, diffs_ys, open(fpath, 'w'))
    fpath = pjoin(dir_, 'diffs_scatter.png')
    draw_scatter(diffs_xs, diffs_ys, open(fpath, 'w'))

    fpath = pjoin(dir_, 'r_vs_diff_r_scatter.png')
    print len(r_xs), len(r_ys)
    draw_scatter(r_xs, r_ys, open(fpath, 'w'), color=r_dist_color)
    fpath = pjoin(dir_, 'r_vs_diff_r_density.png')
    draw_density_plot(r_xs, r_ys, open(fpath, 'w'))

    return to_return
Exemple #3
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 def test_draw_density_plot(self):
     fhand = NamedTemporaryFile(suffix='.png')
     data = {'y': array('f', numpy.random.normal(40, 5, 40000)),
             'x': array('f', numpy.random.normal(40, 5, 40000))}
     draw_density_plot(data['x'], data['y'], fhand, n_bins=200)