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關(guān)于近交系數(shù)是什么的定義，除了英文資料，中文上也給出了清晰的定義，這里引用一下：

近交系數(shù)（inbreeding coefficient）是指根據(jù)近親交配的世代數(shù)，將基因的純化程度用百分?jǐn)?shù)來表示即為近交系數(shù)，也指個(gè)體由于近交而造成異質(zhì)基因減少時(shí)，同質(zhì)基因或純合子所占的百分比也叫近交系數(shù)，普遍以F或f來表示。

GATK近交系數(shù)的計(jì)算程序在github上可以找到：AS_InbreedingCoeff.java

代碼不短，但計(jì)算很簡單，我主要說展示一下這個(gè)計(jì)算的核心部分并在代碼中做些注釋，如下：

    protected double calculateIC(final VariantContext vc, final Allele altAllele) {
        final int AN = vc.getCalledChrCount();
        final double altAF;

        final double hetCount = heterozygosityUtils.getHetCount(vc, altAllele);

        final double F;
        //shortcut to get a value closer to the non-alleleSpecific value for bialleleics
        if (vc.isBiallelic()) {
            double refAC = heterozygosityUtils.getAlleleCount(vc, vc.getReference());
            double altAC = heterozygosityUtils.getAlleleCount(vc, altAllele);
            double refAF = refAC/(altAC+refAC);
            altAF = 1 - refAF;
            F = 1.0 - (hetCount / (2.0 * refAF * altAF * (double) heterozygosityUtils.getSampleCount())); // inbreeding coefficient
        } else {
            //compare number of hets for this allele (and any other second allele) with the expectation based on AFs
            //derive the altAF from the likelihoods to account for any accumulation of fractional counts from non-primary likelihoods,
            //e.g. for a GQ10 variant, the probability of the call will be ~0.9 and the second best call will be ~0.1 so adding up those 0.1s for het counts can dramatically change the AF compared with integer counts
            altAF = heterozygosityUtils.getAlleleCount(vc, altAllele)/ (double) AN;

            // 計(jì)算inbreeding coefficient
            F = 1.0 - (hetCount / (2.0 * (1 - altAF) * altAF * (double) heterozygosityUtils.getSampleCount())); // heterozygosityUtils.getSampleCount() 獲取總樣本數(shù) 
        }

        return F;
    }

總的來說，是利用哈迪溫伯格定律來計(jì)算的。 1.0 - (hetCount / (2.0 * (1 - altAF) * altAF(double)N ，N是人數(shù)。這個(gè)值給出的是期望的雜合變異的個(gè)數(shù)。所以參數(shù)F說的就是"實(shí)際的hetCount”除以"期望的hetCount"再與1.0取差。當(dāng)F值越接近0，就意味著實(shí)際的hetCount與理論的hetCount越接近。

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