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test.cc
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#define DOCTEST_CONFIG_IMPLEMENT
#include <vector>
#include <set>
#include <functional>
#include <cmath>
#include "doctest.h"
#include "io_plink.h"
#include "methods.h"
#include "multiarray.h"
#include "multiarray.cc"
#include "variant.h"
#include "li_stephens.h"
#include "site.h"
TEST_CASE("variant") {
Variant v1 {"1", 1, "C", "A", 0};
Variant v2 {"1", 1, "C", "A", 0};
Variant v3 {"2", 2, "T", "G", 0};
Variant v4 {"1", 5, "C", "A", 0};
Variant v5 {"1", 2, "T", "C", 0};
Variant v6 {"1", 2, "T", "A", 0};
CHECK(v1 == v2);
CHECK(v1 != v3);
CHECK(v1 < v3);
CHECK(!(v1 < v2));
CHECK(v4 > v1);
std::vector<Variant> variants {v1, v3, v6, v4, v5};
std::sort(variants.begin(), variants.end());
CHECK(variants == std::vector<Variant> {v1, v6, v5, v4, v3});
}
TEST_CASE("site") {
Site s1 {Variant {"1", 1, "C", "A", 0}, 2};
Site s2 {Variant {"1", 1, "A", "T", 0}, 0};
Site s3 {Variant {"1", 1, "C", "A", 0}, 1};
std::vector<Site> sites {s1, s2, s3};
std::sort(sites.begin(), sites.end());
CHECK(sites == std::vector<Site> {s2, s3, s1});
}
TEST_CASE("plink loader") {
PLINKReader pr {"data/example1"};
std::vector<Variant> variants {
Variant("1", 1, "C", "A", 0),
Variant("1", 2, "C", "A", 0),
Variant("1", 3, "C", "A", 0),
Variant("1", 4, "C", "A", 0),
Variant("1", 5, "C", "A", 0)
};
std::vector<std::string> samples {
"0", "1", "2", "3", "4", "5", "6", "7", "8", "9"
};
std::vector<int> data_expected {
0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 2, 0, 0, 0, 2, 2, 2, 0, 0,
0, 0, 0, 2, 2, 2, 2, 0, 0, 2,
2, 0, 2, 0, 0, 2, 0, 2, 0, 0,
0, 0, 0, 2, 0, 0, 2, 0, 0, 2
};
std::vector<int> data;
for (std::size_t i = 0; i < pr.n_variants; ++i) {
for (std::size_t j = 0; j < pr.n_samples; ++j) {
data.push_back(pr(i, j));
}
}
CHECK(pr.n_variants == 5);
CHECK(pr.n_samples == 10);
CHECK(pr.variants == variants);
CHECK(pr.samples == samples);
CHECK(data == data_expected);
}
TEST_CASE("zip sites") {
PLINKReader pr1 {"data/example1"};
PLINKReader pr3 {"data/example3"};
auto zipped_result = zip_sites(pr1, pr3);
auto zipped = zipped_result.zipped_sites;
CHECK(zipped.size() == 7);
CHECK(zipped_result.n_both == 2);
CHECK(zipped_result.n_only1 == 3);
CHECK(zipped_result.n_only2 == 2);
CHECK(zipped_result.contig_boundaries == std::set<std::size_t> {0, 5});
CHECK(*zipped[0].s1 == Site { Variant {"1", 1, "C", "A", 0}, 0 });
CHECK(*zipped[0].s2 == Site { Variant {"1", 1, "C", "A", 0}, 0 });
CHECK(*zipped[1].s1 == Site { Variant {"1", 2, "C", "A", 0}, 1 });
CHECK(zipped[1].s2 == nullptr);
CHECK(*zipped[2].s1 == Site { Variant {"1", 3, "C", "A", 0}, 2 });
CHECK(zipped[2].s2 == nullptr);
CHECK(*zipped[3].s1 == Site { Variant {"1", 4, "C", "A", 0}, 3 });
CHECK(zipped[3].s2 == nullptr);
CHECK(*zipped[4].s1 == Site { Variant {"1", 5, "C", "A", 0}, 4 });
CHECK(*zipped[4].s2 == Site { Variant {"1", 5, "C", "A", 0}, 2 });
CHECK(zipped[5].s1 == nullptr);
CHECK(*zipped[5].s2 == Site { Variant {"5", 2, "C", "A", 0}, 1 });
CHECK(zipped[6].s1 == nullptr);
CHECK(*zipped[6].s2 == Site { Variant {"5", 4, "C", "A", 0}, 3 });
}
TEST_CASE("call rate") {
PLINKReader pr {"data/example1"};
CHECK(call_rate(pr) == 1.0);
}
TEST_CASE("multiarray") {
std::vector<int> a {0, 1, 2, 3, 4, 5, 6, 7};
MultiArray<int> ma {a, 4, 2};
int idx = 0;
for (auto i = 0; i < 4; ++i) {
for (auto j = 0; j < 2; ++j) {
CHECK(ma(i, j) == idx);
ma(i, j) = idx - 1;
CHECK(ma(i, j) == idx - 1);
++idx;
}
}
CHECK(ma.same(ma, 1e-4));
}
TEST_CASE("li_stephens") {
PLINKReader reference {"data/example1"};
PLINKReader sample {"data/example2"};
LSModel ls {reference, sample};
CHECK(ls.alpha.n_rows == 5);
CHECK(ls.alpha.n_cols == 10);
auto g = 0.01;
auto theta = 0.2;
std::vector<double> c(10, 0.4);
auto f_likelihood = ls.forward_pass(theta, c, g);
std::vector<double> forward_probs_expected {
0.198, 0.198, 0.198, 0.198, 0.198, 0.198, 0.198, 0.198, 0.198, 0.198,
0.006113479, 0.605234387, 0.006113479, 0.006113479, 0.006113479, 0.605234387, 0.605234387, 0.605234387, 0.006113479, 0.006113479,
0.003664031, 0.013474405, 0.003664031, 0.362739067, 0.362739067, 1.333966117, 1.333966117, 0.013474405, 0.003664031, 0.362739067,
0.550639216, 0.005722653, 0.550639216, 0.011441728, 0.011441728, 2.707174489, 0.027345197, 0.566542685, 0.005562012, 0.011441728,
0.015466719, 0.00654392, 0.015466719, 0.657119154, 0.006637567, 0.050779153, 0.682900059, 0.015727132, 0.006541289, 0.657119154
};
CHECK(ls.alpha.same(MultiArray<double> {forward_probs_expected, ls.alpha.n_rows, ls.alpha.n_cols}, 1e-4));
CHECK(doctest::Approx(f_likelihood) == 2.11430086);
auto b_likelihood = ls.backward_pass(theta, c, g);
CHECK(doctest::Approx(b_likelihood) == 2.11430086);
}
TEST_CASE("li_stephens_uneven") {
PLINKReader reference {"data/example1"};
PLINKReader sample {"data/example3"};
LSModel ls {reference, sample};
CHECK(ls.alpha.n_rows == 2);
CHECK(ls.alpha.n_cols == 10);
auto g = 0.01;
auto theta = 0.2;
std::vector<double> c(10, 0.4);
auto f_likelihood = ls.forward_pass(theta, c, g);
std::vector<double> forward_probs_expected {
0.198, 0.198, 0.198, 0.198, 0.198, 0.198, 0.198, 0.198, 0.198, 0.198,
0.010501972, 0.010501972, 0.010501972, 1.039695219, 0.010501972, 0.010501972, 1.039695219, 0.010501972, 0.010501972, 1.039695219
};
CHECK(ls.alpha.same(MultiArray<double> {forward_probs_expected, ls.alpha.n_rows, ls.alpha.n_cols}, 1e-4));
CHECK(doctest::Approx(f_likelihood) == 3.19259946);
auto b_likelihood = ls.backward_pass(theta, c, g);
CHECK(doctest::Approx(b_likelihood) == 3.19259946);
}
TEST_CASE("li_stevens_multiple_contigs") {
PLINKReader reference {"data/example3"};
PLINKReader sample {"data/example4"};
LSModel ls {reference, sample};
CHECK(ls.alpha.n_rows == 2);
CHECK(ls.alpha.n_cols == 1);
auto g = 0.01;
auto theta = 0.2;
std::vector<double> c(1, 0.4);
auto f_likelihood = ls.forward_pass(theta, c, g);
std::vector<double> forward_probs_expected {
1.98,
1.98
};
CHECK(ls.alpha.same(MultiArray<double> {forward_probs_expected, ls.alpha.n_rows, ls.alpha.n_cols}, 1e-4));
CHECK(doctest::Approx(f_likelihood) == 1.98);
auto b_likelihood = ls.backward_pass(theta, c, g);
CHECK(doctest::Approx(b_likelihood) == 1.98);
}
TEST_CASE("li_stephens_identical_haplotype") {
PLINKReader reference {"data/example5"};
PLINKReader sample {"data/example5-chimera"};
auto g = 0.01;
auto theta = 0.2;
std::vector<double> c(10, 0.4);
LSModel ls {reference, sample, 0};
auto f_likelihood = ls.forward_pass(theta, c, g);
auto b_likelihood = ls.backward_pass(theta, c, g);
CHECK(doctest::Approx(f_likelihood) == b_likelihood);
ls.compute_gamma(f_likelihood);
printf("%s\n", ls.gamma.to_string().c_str());
}
TEST_CASE("li_stephens_expectation_maximization") {
PLINKReader reference {"data/example5"};
PLINKReader sample {"data/example5-chimera"};
auto g = 0.01;
auto theta = 0.2;
std::vector<double> c(10, 0.4);
LSModel ls {reference, sample};
EMResult emr = ls.em(theta, c, g, 0.001, 10);
for (auto i = 0; i < ls.n_states; ++i) {
if (i == 0 || i == 1) {
CHECK(emr.c[i] >= 0.4);
CHECK(emr.c[i] <= 0.5);
} else {
CHECK(emr.c[i] < 0.05);
}
}
}