Analysis of molecular population genetic data
[Molecular Population Genetics]
Classes | |
| class | Sequence::FST |
analysis of population structure using  More... | |
| class | Sequence::PolySIM |
| Analysis of coalescent simulation data. More... | |
| class | Sequence::PolySNP |
| Molecular population genetic analysis. More... | |
| class | Sequence::PolyTableSlice< T > |
| A container class for "sliding windows" along a polymorphism table. More... | |
Namespaces | |
| namespace | Sequence::Recombination |
Methods dealing with recombination. | |
Functions | |
| template<typename uniform_int_generator > | |
| std::pair< double, double > | Sequence::Snn_test (const PolyTable &snpTable, const unsigned config[], const size_t &npop, uniform_int_generator &uni_int, const unsigned &nperms=10000) |
| Conducts a permutation-test of Hudson's Snn (sequence nearest-neighbor) statistic. | |
| template<typename uniform_int_generator > | |
| std::vector< std::vector < double > > | Sequence::Snn_test_pairwise (const PolyTable &snpTable, const unsigned config[], const size_t &npop, uniform_int_generator &uni_int, const unsigned &nperms=10000) |
| Conducts a permutation-test of Hudson's Snn (sequence nearest-neighbor) statistic, for all pairwise combinations of populations. | |
| template<typename uniform_int_generator > | |
| std::pair< double, double > | Sequence::Snn_test (const PolyTable &snpTable, const unsigned config[], const size_t &npop, const uniform_int_generator &uni_int, const unsigned &nperms=10000) |
| Conducts a permutation-test of Hudson's Snn (sequence nearest-neighbor) statistic. | |
| template<typename uniform_int_generator > | |
| std::vector< std::vector < double > > | Sequence::Snn_test_pairwise (const PolyTable &snpTable, const unsigned config[], const size_t &npop, const uniform_int_generator &uni_int, const unsigned &nperms=10000) |
| Conducts a permutation-test of Hudson's Snn (sequence nearest-neighbor) statistic, for all pairwise combinations of populations. | |
Function Documentation
template<typename uniform_int_generator >
| std::pair< double, double > Sequence::Snn_test | ( | const PolyTable & | snpTable, | |
| const unsigned | config[], | |||
| const size_t & | npop, | |||
| const uniform_int_generator & | uni_int, | |||
| const unsigned & | nperms = 10000 | |||
| ) | [inline] |
Conducts a permutation-test of Hudson's Snn (sequence nearest-neighbor) statistic.
- Parameters:
-
snpTable The data on which we wish to perform the test. config An array of the sample sizes in each deme. npop The number of populations. For example, npop could equal config.size() if config were a vector uni_int A random number generator whose operator() takes one argument, n, and returns a value uniformly-distributed on the half-open interval [0,N) nperms The number of permutations to do for the test
- Returns:
- A pair of doubles (std::pair<double,double>). the first member of the pair is the observed value of the statistic, and the second member is the estimated p-value
template<typename uniform_int_generator >
| std::pair< double, double > Sequence::Snn_test | ( | const PolyTable & | snpTable, | |
| const unsigned | config[], | |||
| const size_t & | npop, | |||
| uniform_int_generator & | uni_int, | |||
| const unsigned & | nperms = 10000 | |||
| ) | [inline] |
Conducts a permutation-test of Hudson's Snn (sequence nearest-neighbor) statistic.
- Parameters:
-
snpTable The data on which we wish to perform the test. config An array of the sample sizes in each deme. npop The number of populations. For example, npop could equal config.size() if config were a vector uni_int A random number generator whose operator() takes one argument, n, and returns a value uniformly-distributed on the half-open interval [0,N) nperms The number of permutations to do for the test
- Returns:
- A pair of doubles (std::pair<double,double>). the first member of the pair is the observed value of the statistic, and the second member is the estimated p-value
template<typename uniform_int_generator >
| std::vector< std::vector< double > > Sequence::Snn_test_pairwise | ( | const PolyTable & | snpTable, | |
| const unsigned | config[], | |||
| const size_t & | npop, | |||
| const uniform_int_generator & | uni_int, | |||
| const unsigned & | nperms = 10000 | |||
| ) | [inline] |
Conducts a permutation-test of Hudson's Snn (sequence nearest-neighbor) statistic, for all pairwise combinations of populations.
- Parameters:
-
snpTable The data on which we wish to perform the test. config An array of the sample sizes in each deme. npop The number of populations. For example, npop could equal config.size() if config were a vector uni_int A random number generator whose operator() takes one argument, n, and returns a value uniformly-distributed on the half-open interval [0,N) nperms The number of permutations to do for the test
- Returns:
- A vector of vector<double>. Each vector contains 4 elements, indexed 0 to 3. Elements 0 and 1 are the indexes of the i-th and j-th population. Element 2 is the observed Snn between the i-th and j-th population, and element 3 is the p-value estimated by permutation
template<typename uniform_int_generator >
| std::vector< std::vector< double > > Sequence::Snn_test_pairwise | ( | const PolyTable & | snpTable, | |
| const unsigned | config[], | |||
| const size_t & | npop, | |||
| uniform_int_generator & | uni_int, | |||
| const unsigned & | nperms = 10000 | |||
| ) | [inline] |
Conducts a permutation-test of Hudson's Snn (sequence nearest-neighbor) statistic, for all pairwise combinations of populations.
- Parameters:
-
snpTable The data on which we wish to perform the test. config An array of the sample sizes in each deme. npop The number of populations. For example, npop could equal config.size() if config were a vector uni_int A random number generator whose operator() takes one argument, n, and returns a value uniformly-distributed on the half-open interval [0,N) nperms The number of permutations to do for the test
- Returns:
- A vector of vector<double>. Each vector contains 4 elements, indexed 0 to 3. Elements 0 and 1 are the indexes of the i-th and j-th population. Element 2 is the observed Snn between the i-th and j-th population, and element 3 is the p-value estimated by permutation
