structuralvariants.py 文件源码

def score_event(nx, ny, ncommon, barcode_frequencies, resamples=100):
    """
    perform a resampling test, based on the number of fragments in each region
    and the barcode frequency distribution (the latter because some barcodes
    have more DNA in them than others)
    """

    samples = []
    for _ in range(resamples):
        s1 = numpy.random.choice(len(barcode_frequencies), nx, replace=False, p=barcode_frequencies)
        s2 = numpy.random.choice(len(barcode_frequencies), ny, replace=False, p=barcode_frequencies)
        common = len(set(s1).intersection(set(s2)))
        samples.append(common)

    # make a one-sided one-sample Wilcoxon test
    statistic, pvalue = stats.wilcoxon(numpy.array(samples)-ncommon)
    if numpy.mean(samples) > ncommon:
        pvalue = 1 - pvalue/2.0
    else:
        pvalue = pvalue/2.0

    # result = r["wilcox.test"](samples, mu=ncommon, alternative="less")
    # pvalue2 = result.rx2("p.value")[0]

    # print "::::::", nx, ny, ncommon, (numpy.array(samples)>ncommon).sum(), pvalue, pvalue2
    return pvalue