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ClassSequenceDataCreator.hpp
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#ifndef CLASSSEQUENCEDATACREATOR_HPP
#define CLASSSEQUENCEDATACREATOR_HPP
#include <string>
#include <list>
#include <future>
#include <seqan/bam_io.h> // BamFileIn
#include <seqan/bed_io.h> // BedFileIn
#include <SequenceMatrixCreator.hpp>
#include <Matrix2D.hpp>
#include <Matrix3D.hpp>
/*!
* \brief The ClassSequenceDataCreator class class allows to extract the data
* that have been assigned to a given class, given a data partition.
*
* Given posterior probabilities and a sequence matrix, the corresponding
* class models can be computed. They are the weighted aggregations of the
* DNA sequences assigned to each given class. However, because DNA sequences
* cannot be summed, the aggregation are represented as probability matrices
* or consensus sequence (A+C is represented as 50%A, 50%C, 0%G, 0%T). Instead
* of this, this program creates the unfolded matrix that, if summed over the
* columns, gives the model of class K.
*
* For a hard clustering methods, this procedure would simply correspond to the
* creation of a matrix of dimensions N'xL where N'<=N is the number sequences
* assigned to class K among the N overall sequences and L the length of
* the each sequence.
*
* In the case of a soft clustering methods, this procedure creates a 3D matrix of
* dimensions NxL'x4. This matrix contains N probability matrices, each one of
* dimensions L'x4 where L'=L-S+1, 4 corresponds to A, C, G, T and S is the
* shifting freedom allowed during the classification. The resulting matrix
* contains as many rows as the starting matrix because in soft clustering, all
* sequences (rows) are assigned to all classes
*
* To construct a final matrix M3 of dimensions NxL3 where L3 covers a given
* range <from>/<to>, the original matrix M1 of dimensions NxL is computed and
* extended into a matrix M2 NxL2 with L2>=L1. The final M3 of dimensions NxL
* is eventually computed, for class K, using the given posterior probabilities.
* A row of the final matrix M3 is the weighted average of each of the S
* possibles slices of the corresponding row in M2, represented as a probability
* matrix. The weights used are the probabilities with which this row was assigned
* to class K, for each of the S shift states, in each flip state.
*
* The original matrix M1 that was partitionned with shifting freedom S is
* generated using the BED and fasta files that were originally used to
* create it.
* The posterior probabilities should be a 4D matrix in binary format, with
* dimensions :
* 1) number of sequences
* 2) number of classes
* 3) number of shift states
* 4) number of flip states
* The results is returned as a 3D binary matrix of dimensions :
* 1) number of sequences
* 2) length of the sequences, as defined by the <from>/<to> range
* 3= 4 for A, C, G, T
*/
class ClassSequenceDataCreator
{
public:
ClassSequenceDataCreator() = delete ;
/*!
* \brief Constructs an object to build a
* class sequence matrix from a partition.
* \param bed_file_path the path to the file containing
* the references.
* \param fasta_file_path the path to the file containing
* the sequences.
* \param prob_file_path the path to the file containing
* the assignment probabilities of the partition.
* It should be 4D matrix with the following dimensions :
* 1st the number of regions, should be the number of
* references in the BED file.
* 2nd the number of classes.
* 3rd the shifting freedom.
* 4th the flipping freedom (1 for no flip, 2 otherwise).
* \param from the upstream most relative position
* to consider around the references. It may
* be changed to make sure that the central bin
* is centered on +/- 0.
* \param to the dowmstream most relative position
* to consider around the references. It may
* be changed to make sure that the central bin
* is centered on +/- 0.
* \param class_k the index (1-based) of the class of
* interest for which a matrix should be computed,
* from the partition.
*/
ClassSequenceDataCreator(const std::string& bed_file_path,
const std::string& fasta_file_path,
const std::string& prob_file_path,
int from,
int to,
size_t class_k) ;
/*!
* Destructor.
*/
~ClassSequenceDataCreator() ;
/*!
* \brief Computes the matrix and returns it.
* \return the class sequence matrix.
* For each region, a consensus sequence is
* returned as a probability matrix.
* The matrix dimensions are :
* 1st the number of regions.
* 2nd the consensus sequence length.
* 3rd 4 for A,C,G,T
*/
Matrix3D<double> create_matrix() ;
protected:
/*!
* \brief Bed file path.
*/
std::string bed_file_path ;
/*!
* \brief Fasta file path.
*/
std::string fasta_file_path ;
/*!
* \brief the path to the posterior probability
* file (the partition).
*/
std::string prob_file_path ;
/*!
* \brief The smallest relative coordinate from the region
* center to consider (included).
*/
int from ;
/*!
* \brief The biggest relative coordinate from the region
* center to consider (not included).
*/
int to ;
/*!
* \brief the class of interest (0-based).
*/
size_t class_k ;
} ;
#endif // CLASSSEQUENCEDATACREATOR_HPP

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