Example #1
0
void SnpEstimation::result(const boost::ptr_vector<Snp> &snpList, const boost::ptr_vector<Region> &regionList){
    bool sign = !(snpList.front().getSign()==0);
    double i2 = (m_bt)? usefulTools::dnorm(usefulTools::qnorm(m_prevalence))/(m_prevalence): 0;
    i2 = i2*i2;
    double adjust = 0.0;
    size_t countNum  = 0;
    double sampleSize = 0.0;
    std::vector<double> heritability;
    std::vector<double> variance;
    std::vector<double> effective;
    for(size_t i = 0; i < regionList.size(); ++i){
        // add stuff
        heritability.push_back(0.0);
        variance.push_back(regionList[i].getVariance());
        effective.push_back(0.0);
    }
    std::ofstream fullOutput;
    bool requireFullOut = false;
    if(!m_output.empty()) requireFullOut = true;
    if(requireFullOut){
        std::string fullOutName = m_output;
        fullOutName.append(".res");
        fullOutput.open(fullOutName.c_str());
        if(!fullOutput.is_open()){
            requireFullOut = false;
            fprintf(stderr, "Cannot access output file: %s\n", fullOutName.c_str());
            fprintf(stderr, "Will only provide basic output\n");
        }
        else{
            fullOutput << "Chr\tLoc\trsID\tZ\tF\tH\tStatus" << std::endl;
        }
    }
    for(size_t i = 0; i < snpList.size(); ++i){
        if(requireFullOut){
            fullOutput << snpList[i].getChr() << "\t" << snpList[i].getLoc() << "\t" << snpList[i].getRs() << "\t" << snpList[i].getTStat() << "\t"<< snpList[i].getFStat() << "\t" << snpList[i].getHeritability() << "\t" << snpList[i].getStatus() << std::endl;
        }
        for(size_t j = 0; j < regionList.size(); ++j){
//            if(j ==0) std::cerr << snpList[i].flag(j) << std::endl;
            if(snpList[i].flag(j)) heritability[j]+=snpList[i].getHeritability();
            if(snpList[i].flag(j)) effective[j] += snpList[i].getEffective();
        }
        sampleSize +=(double)(snpList[i].getSampleSize());
        countNum++;
        if(m_bt){
            double portionCase = (double)(snpList[i].getNCase()) / (double)(snpList[i].getSampleSize());
            adjust+= ((1.0-m_prevalence)*(1.0-m_prevalence))/(i2*portionCase*(1-portionCase));
        }

    }

    if(requireFullOut) fullOutput.close();

    double adjustment = adjust/(double)countNum; // we use the average adjustment value here
    if(!m_bt) adjustment = m_extreme;
    double averageSampleSize = sampleSize/(double)countNum;
    if(!m_output.empty()) requireFullOut =true;
    std::ofstream sumOut;
    if(requireFullOut){
        std::string sumOutName = m_output;
        sumOutName.append(".sum");
        sumOut.open(sumOutName.c_str());
        if(!sumOut.is_open()){
            fprintf(stderr, "Cannot access output file %s\n", sumOutName.c_str());
            fprintf(stderr, "Will output to stdout instead\n");
            requireFullOut=false;
        }
    }
    // We separate it, because it is possible for the previous if to change the requireFullOut flag
    if(!requireFullOut){
        // Only output to the stdout
        std::cout << "Region\tHeritability\tVariance" << std::endl;
        for(size_t i = 0; i < regionList.size(); ++i){
            std::cout << regionList[i].getName() << "\t" << adjustment*heritability[i] << "\t";
            if(!sign) std::cout << adjustment*(2.0*(effective[i]*adjustment*adjustment+2.0*adjustment*heritability[i]*averageSampleSize)/(averageSampleSize*averageSampleSize)) << std::endl;
            else std::cout << adjustment*adjustment*variance[i] << std::endl;
        }
    }
    else{
        sumOut << "Region\tHeritability\tVariance" << std::endl;
        std::cout << "Region\tHeritability\tVariance" << std::endl;
        for(size_t i = 0; i < regionList.size(); ++i){
            sumOut << regionList[i].getName() << "\t" << adjustment*heritability[i] << "\t";
            std::cout << regionList[i].getName() << "\t" << heritability[i] << "\t";
            if(!sign){ // We use effective number
                sumOut << adjustment*(2.0*(effective[i]*adjustment*adjustment+2.0*adjustment*heritability[i]*averageSampleSize)/(averageSampleSize*averageSampleSize)) << std::endl;
                std::cout << adjustment*(2.0*(effective[i]*adjustment*adjustment+2.0*adjustment*heritability[i]*averageSampleSize)/(averageSampleSize*averageSampleSize)) << std::endl;
            }
            else{
                sumOut << adjustment*adjustment*variance[i] << std::endl;
                std::cout << adjustment*adjustment*variance[i] << std::endl;
            }
        }
        sumOut.close();
    }
}