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EMSequenceApplication.hpp
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Thu, May 23, 05:54

EMSequenceApplication.hpp
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#ifndef EMSEQUENCEAPPLICATION_HPP
#define EMSEQUENCEAPPLICATION_HPP
#include <ApplicationInterface.hpp>
#include <string>
#include <vector>
#include <Matrix2D.hpp>
#include <Matrix3D.hpp>
/*!
* \brief The EMSequenceApplication class is a wrapper around an EMSequence
* instance creating an autonomous application to classify sequences by directly
* passing all the options and parameters from the command line.
*/
class EMSequenceApplication: public ApplicationInterface
{
public:
EMSequenceApplication() = delete ;
EMSequenceApplication(const EMSequenceApplication& app) = delete ;
/*!
* \brief Constructs an object from the command line
* options.
* \param argn the number of options passed to the
* main() function.
* \param argv the vector of options passed to the
* main() function.
*/
EMSequenceApplication(int argn, char** argv) ;
/*!
* \brief Runs the application. The data are classified
* using the given settings and the posterior probability
* matrix is returned through the stdout.
* The matrix is a 4D matrix with dimensions :
* regions, class, shift flip.
* \return an exit code EXIT_SUCCESS or EXIT_FAILURE
* to return to the OS.
*/
virtual int run() override ;
private:
/*!
* \brief Parses the program command line options and
* sets the object field accordingly.
* If the help option is detected, the "runnable"
* field is set to false and subsequent calls to
* run() will produce nothing.
* \param argn the number of options passed to the
* main() function.
* \param argv the vector of options passed to the
* main() function.
* \throw std::invalid_argument if an error is found
* in the program options.
*/
void parseOptions(int argn, char** argv) ;
/*!
* \brief Initialise the class models from the
* most significantly enriched kmers in the data.
* The kmers are turned into probability matrices
* using the following rules :
* 1) the probability of a base matching a base at
* a given position of the kmer is set to 0.7, all
* other to 0.1
* 2) if the model length is bigger than 4, two
* N's are added on each side of the central kmer
* core (prob are 0.25, 0,25, 0.25, 0.25).
* \param l_model the length of the model.
* \param data the sequences in integer format
* (A:0, C:1, G:2, T:3).
* Its dimensions are the following :
* 1st the number of sequences
* 2nd the length of the sequences.
* \return The models initialised.
* Its dimensions are the following :
* 1st the number of classes
* 2nd the length of the model
* 3rd 4 for A, C, G, T
*/
Matrix3D<double> init_model_kmer(size_t l_model,
const Matrix2D<int>& data) const ;
/*!
* \brief Initialise the class models if matrices
* are given as initial class motifs.
* If the given class motifs are shorter than the
* model after accounting for shifting, extra columns
* with uniform probabilities will be added on each
* side.
* If the number of classes is higher than the
* number of given motifs, extra classes will be
* initialised randomly.A background class is included
* if needed.
* \param l_model the number of positions (columns)
* of the model to initialise.
* \param data the sequence matrix, in integer format.
* \param motif_paths the paths to the files containing
* the probability matrices to use to initialise the
* class motifs.
* \return The models initialised.
* Its dimensions are the following :
* 1st the number of classes
* 2nd the length of the model
* 3rd 4 for A, C, G, T
*/
Matrix3D<double> init_model(size_t l_model,
const Matrix2D<int>& data,
const std::vector<std::string>& motif_paths) const ;
/*!
* \brief the paths to the file containing the sequence
* data.
*/
std::string file_seq ;
/*!
* \brief a coma separated list of files containing the
* initial motif matrices.
*/
std::string files_motif ;
/*!
* \brief the path to the file containing the
* (0-based) index of the rows to filter out
* from the data.
*/
std::string file_filter ;
/*!
* \brief the path to the file in which the probability
* matrix will be saved.
*/
std::string file_out ;
/*!
* \brief the number of classes to partition the data into.
*/
size_t n_class ;
/*!
* \brief the number of iterations allowed.
*/
size_t n_iter ;
/*!
* \brief the shifting freedom.
*/
size_t n_shift ;
/*!
* \brief whether flipping freedom is allowed.
*/
bool flip ;
/*!
* \brief whether a constant class to model the
* sequence background should be added. This
* class has the sequence background probabilities
* at each position.
*/
bool bckg_class ;
/*!
* \brief the number of threads.
*/
size_t n_threads ;
/*!
* \brief a seed to initialise the random number generator.
*/
std::string seed ;
/*!
* \brief a flag indicating whether the core of run() can be
* run or not.
*/
bool runnable ;
} ;
#endif // EMSEQUENCEAPPLICATION_HPP

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