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-rw-r--r--src/lm.cpp8
-rw-r--r--src/lmm.cpp202
-rw-r--r--src/param.h5
3 files changed, 84 insertions, 131 deletions
diff --git a/src/lm.cpp b/src/lm.cpp
index 83558e4..0c2a2bb 100644
--- a/src/lm.cpp
+++ b/src/lm.cpp
@@ -362,7 +362,7 @@ void LM::AnalyzeGene(const gsl_matrix *W, const gsl_vector *x) {
time_opt += (clock() - time_start) / (double(CLOCKS_PER_SEC) * 60.0);
// Store summary data.
- SUMSTAT SNPs = {beta, se, 0.0, 0.0, p_wald, p_lrt, p_score};
+ SUMSTAT SNPs = {beta, se, 0.0, 0.0, p_wald, p_lrt, p_score, -0.0 };
sumStat.push_back(SNPs);
}
cout << endl;
@@ -587,7 +587,7 @@ void LM::Analyzebgen(const gsl_matrix *W, const gsl_vector *y) {
time_opt += (clock() - time_start) / (double(CLOCKS_PER_SEC) * 60.0);
// Store summary data.
- SUMSTAT SNPs = {beta, se, 0.0, 0.0, p_wald, p_lrt, p_score};
+ SUMSTAT SNPs = {beta, se, 0.0, 0.0, p_wald, p_lrt, p_score, -0.0};
sumStat.push_back(SNPs);
}
cout << endl;
@@ -702,7 +702,7 @@ void LM::AnalyzeBimbam(const gsl_matrix *W, const gsl_vector *y) {
time_opt += (clock() - time_start) / (double(CLOCKS_PER_SEC) * 60.0);
// Store summary data.
- SUMSTAT SNPs = {beta, se, 0.0, 0.0, p_wald, p_lrt, p_score};
+ SUMSTAT SNPs = {beta, se, 0.0, 0.0, p_wald, p_lrt, p_score, -0.0};
sumStat.push_back(SNPs);
}
cout << endl;
@@ -844,7 +844,7 @@ void LM::AnalyzePlink(const gsl_matrix *W, const gsl_vector *y) {
p_lrt, p_score);
// store summary data
- SUMSTAT SNPs = {beta, se, 0.0, 0.0, p_wald, p_lrt, p_score};
+ SUMSTAT SNPs = {beta, se, 0.0, 0.0, p_wald, p_lrt, p_score, -0.0};
sumStat.push_back(SNPs);
time_opt += (clock() - time_start) / (double(CLOCKS_PER_SEC) * 60.0);
diff --git a/src/lmm.cpp b/src/lmm.cpp
index 37f2f5b..e2f23a2 100644
--- a/src/lmm.cpp
+++ b/src/lmm.cpp
@@ -95,6 +95,7 @@ void LMM::CopyToParam(PARAM &cPar) {
}
void LMM::WriteFiles() {
+
string file_str;
file_str = path_out + "/" + file_out;
file_str += ".assoc.txt";
@@ -105,150 +106,99 @@ void LMM::WriteFiles() {
return;
}
- if (!file_gene.empty()) {
- outfile << "geneID"
- << "\t";
-
- if (a_mode == 1) {
- outfile << "beta"
- << "\t"
- << "se"
- << "\t"
- << "l_remle"
- << "\t"
+ auto common_header = [&] () {
+ outfile << "beta" << "\t"
+ << "se" << "\t";
+
+ outfile << "logl_H1" << "\t"; // we may make this an option
+
+ switch(a_mode) {
+ case 1:
+ outfile << "l_remle" << "\t"
<< "p_wald" << endl;
- } else if (a_mode == 2) {
- outfile << "l_mle"
- << "\t"
+ break;
+ case 2:
+ outfile << "l_mle" << "\t"
<< "p_lrt" << endl;
- } else if (a_mode == 3) {
- outfile << "beta"
- << "\t"
- << "se"
- << "\t"
+ break;
+ case 3:
+ outfile << "p_score" << endl;
+ break;
+ case 4:
+ outfile << "l_remle" << "\t"
+ << "l_mle" << "\t"
+ << "p_wald" << "\t"
+ << "p_lrt" << "\t"
<< "p_score" << endl;
- } else if (a_mode == 4) {
- outfile << "beta"
- << "\t"
- << "se"
- << "\t"
- << "l_remle"
- << "\t"
- << "l_mle"
- << "\t"
- << "p_wald"
- << "\t"
- << "p_lrt"
- << "\t"
- << "p_score" << endl;
- } else {
+ break;
}
+ };
+
+ auto sumstats = [&] (SUMSTAT st) {
+ outfile << scientific << setprecision(6) << st.beta << "\t"
+ << st.se << "\t";
+
+ outfile << st.logl_H1 << "\t";
+
+ switch(a_mode) {
+ case 1:
+ outfile << st.lambda_remle << "\t"
+ << st.p_wald << endl;
+ break;
+ case 2:
+ outfile << st.lambda_mle << "\t"
+ << st.p_lrt << endl;
+ break;
+ case 3:
+ outfile << st.p_score << endl;
+ break;
+ case 4:
+ outfile << st.lambda_remle << "\t"
+ << st.lambda_mle << "\t"
+ << st.p_wald << "\t"
+ << st.p_lrt << "\t"
+ << st.p_score << endl;
+ break;
+ }
+ };
+
+
+ if (!file_gene.empty()) {
+ outfile << "geneID" << "\t";
+
+ common_header();
for (vector<SUMSTAT>::size_type t = 0; t < sumStat.size(); ++t) {
outfile << snpInfo[t].rs_number << "\t";
-
- if (a_mode == 1) {
- outfile << scientific << setprecision(6) << sumStat[t].beta << "\t"
- << sumStat[t].se << "\t" << sumStat[t].lambda_remle << "\t"
- << sumStat[t].p_wald << endl;
- } else if (a_mode == 2) {
- outfile << scientific << setprecision(6) << sumStat[t].lambda_mle
- << "\t" << sumStat[t].p_lrt << endl;
- } else if (a_mode == 3) {
- outfile << scientific << setprecision(6) << sumStat[t].beta << "\t"
- << sumStat[t].se << "\t" << sumStat[t].p_score << endl;
- } else if (a_mode == 4) {
- outfile << scientific << setprecision(6) << sumStat[t].beta << "\t"
- << sumStat[t].se << "\t" << sumStat[t].lambda_remle << "\t"
- << sumStat[t].lambda_mle << "\t" << sumStat[t].p_wald << "\t"
- << sumStat[t].p_lrt << "\t" << sumStat[t].p_score << endl;
- } else {
- }
+ sumstats(sumStat[t]);
}
} else {
bool process_gwasnps = setGWASnps.size();
- outfile << "chr"
- << "\t"
- << "rs"
- << "\t"
- << "ps"
- << "\t"
- << "n_miss"
- << "\t"
- << "allele1"
- << "\t"
- << "allele0"
- << "\t"
- << "af"
- << "\t";
-
- if (a_mode == 1) {
- outfile << "beta"
- << "\t"
- << "se"
- << "\t"
- << "l_remle"
- << "\t"
- << "p_wald" << endl;
- } else if (a_mode == 2) {
- outfile << "l_mle"
- << "\t"
- << "p_lrt" << endl;
- } else if (a_mode == 3) {
- outfile << "beta"
- << "\t"
- << "se"
- << "\t"
- << "p_score" << endl;
- } else if (a_mode == 4) {
- outfile << "beta"
- << "\t"
- << "se"
- << "\t"
- << "l_remle"
- << "\t"
- << "l_mle"
- << "\t"
- << "p_wald"
- << "\t"
- << "p_lrt"
- << "\t"
- << "p_score" << endl;
- } else {
- }
+
+ outfile << "chr" << "\t"
+ << "rs" << "\t"
+ << "ps" << "\t"
+ << "n_miss" << "\t"
+ << "allele1" << "\t"
+ << "allele0" << "\t"
+ << "af" << "\t";
+
+ common_header();
size_t t = 0;
for (size_t i = 0; i < snpInfo.size(); ++i) {
-
if (indicator_snp[i] == 0)
continue;
auto snp = snpInfo[i].rs_number;
if (process_gwasnps && setGWASnps.count(snp) == 0)
continue;
// cout << t << endl;
-
outfile << snpInfo[i].chr << "\t" << snpInfo[i].rs_number << "\t"
<< snpInfo[i].base_position << "\t" << snpInfo[i].n_miss << "\t"
<< snpInfo[i].a_minor << "\t" << snpInfo[i].a_major << "\t"
<< fixed << setprecision(3) << snpInfo[i].maf << "\t";
- if (a_mode == 1) {
- outfile << scientific << setprecision(6) << sumStat[t].beta << "\t"
- << sumStat[t].se << "\t" << sumStat[t].lambda_remle << "\t"
- << sumStat[t].p_wald << endl;
- } else if (a_mode == 2) {
- outfile << scientific << setprecision(6) << sumStat[t].lambda_mle
- << "\t" << sumStat[t].p_lrt << endl;
- } else if (a_mode == 3) {
- outfile << scientific << setprecision(6) << sumStat[t].beta << "\t"
- << sumStat[t].se << "\t" << sumStat[t].p_score << endl;
- } else if (a_mode == 4) {
- outfile << scientific << setprecision(6) << sumStat[t].beta << "\t"
- << sumStat[t].se << "\t" << sumStat[t].lambda_remle << "\t"
- << sumStat[t].lambda_mle << "\t" << sumStat[t].p_wald << "\t"
- << sumStat[t].p_lrt << "\t" << sumStat[t].p_score << endl;
- } else {
- }
+ sumstats(sumStat[t]);
t++;
}
}
@@ -1299,7 +1249,7 @@ void LMM::AnalyzeGene(const gsl_matrix *U, const gsl_vector *eval,
time_opt += (clock() - time_start) / (double(CLOCKS_PER_SEC) * 60.0);
// Store summary data.
- SUMSTAT SNPs = {beta, se, lambda_remle, lambda_mle, p_wald, p_lrt, p_score};
+ SUMSTAT SNPs = {beta, se, lambda_remle, lambda_mle, p_wald, p_lrt, p_score, logl_H1};
sumStat.push_back(SNPs);
}
cout << endl;
@@ -1400,7 +1350,7 @@ void LMM::AnalyzeBimbam(const gsl_matrix *U, const gsl_vector *eval,
// Store summary data.
SUMSTAT SNPs = {beta, se, lambda_remle, lambda_mle,
- p_wald, p_lrt, p_score};
+ p_wald, p_lrt, p_score, logl_H1};
sumStat.push_back(SNPs);
}
};
@@ -1653,7 +1603,7 @@ void LMM::AnalyzePlink(const gsl_matrix *U, const gsl_vector *eval,
// Store summary data.
SUMSTAT SNPs = {beta, se, lambda_remle, lambda_mle,
- p_wald, p_lrt, p_score};
+ p_wald, p_lrt, p_score, logl_H1};
sumStat.push_back(SNPs);
}
}
@@ -1930,7 +1880,7 @@ void LMM::Analyzebgen(const gsl_matrix *U, const gsl_vector *eval,
// Store summary data.
SUMSTAT SNPs = {beta, se, lambda_remle, lambda_mle,
- p_wald, p_lrt, p_score};
+ p_wald, p_lrt, p_score, logl_H1};
sumStat.push_back(SNPs);
}
}
@@ -2411,7 +2361,7 @@ void LMM::AnalyzeBimbamGXE(const gsl_matrix *U, const gsl_vector *eval,
time_opt += (clock() - time_start) / (double(CLOCKS_PER_SEC) * 60.0);
// Store summary data.
- SUMSTAT SNPs = {beta, se, lambda_remle, lambda_mle, p_wald, p_lrt, p_score};
+ SUMSTAT SNPs = {beta, se, lambda_remle, lambda_mle, p_wald, p_lrt, p_score, logl_H1};
sumStat.push_back(SNPs);
}
cout << endl;
@@ -2589,7 +2539,7 @@ void LMM::AnalyzePlinkGXE(const gsl_matrix *U, const gsl_vector *eval,
time_opt += (clock() - time_start) / (double(CLOCKS_PER_SEC) * 60.0);
// Store summary data.
- SUMSTAT SNPs = {beta, se, lambda_remle, lambda_mle, p_wald, p_lrt, p_score};
+ SUMSTAT SNPs = {beta, se, lambda_remle, lambda_mle, p_wald, p_lrt, p_score, logl_H1};
sumStat.push_back(SNPs);
}
cout << endl;
diff --git a/src/param.h b/src/param.h
index 08b1e10..ff279bd 100644
--- a/src/param.h
+++ b/src/param.h
@@ -56,6 +56,9 @@ public:
double p_wald; // p value from a Wald test.
double p_lrt; // p value from a likelihood ratio test.
double p_score; // p value from a score test.
+ double logl_H1; // log likelihood under the alternative
+ // hypothesis as a measure of goodness of fit,
+ // see https://github.com/genetics-statistics/GEMMA/issues/81
};
// Results for mvLMM.
@@ -118,7 +121,7 @@ public:
bool mode_debug = false;
uint issue; // enable tests for issue on github tracker
- int a_mode; // Analysis mode, 1/2/3/4 for Frequentist tests
+ uint a_mode; // Analysis mode, 1/2/3/4 for Frequentist tests
int k_mode; // Kinship read mode: 1: n by n matrix, 2: id/id/k_value;
vector<size_t> p_column; // Which phenotype column needs analysis.
size_t d_pace; // Display pace
generated by cgit v1.2.3 (git 2.44.0) at 2025-01-19 23:07:52 +0000