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ClassReadDataCreator.hpp
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ClassReadDataCreator.hpp
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#ifndef CLASSREADDATACREATOR_HPP
#define CLASSREADDATACREATOR_HPP
#include <string>
#include <list>
#include <future>
#include <seqan/bam_io.h> // BamFileIn
#include <seqan/bed_io.h> // BedFileIn
#include <CorrelationMatrixCreator.hpp>
#include <Matrix2D.hpp>
/*!
* \brief The ClassReadDataCreator class allows to extract the data
* that have been assigned to a given class, given a data partition.
*
* Given posterior probabilities and a read density matrix, the corresponding
* class models can be computed. They are the weighted aggregations of the
* data assigned to each given class. 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 regions
* assigned to class K among the N overall regions and L the number of bins of
* the each region.
*
* In the case of a soft clustering methods, this procedure creates a matrix of
* dimensions NxL' where L'=L-S+1 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 regions (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. 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, BAM and BAI files that were originally used to
* create it.
* The posterior probabilities should be a 4D matrix in binary format, with
* dimensions :
* 1) number of regions
* 2) number of classes
* 3) number of shift states
* 4) number of flip states
* The results is returned through stdout as a 2D text matrix of dimensions :
* 1) number of regions
* 2) number of bins in each regions, as defined by the <from>/<to> range and
* the <binsiz> value. ;
*/
class ClassReadDataCreator
{
public:
ClassReadDataCreator() = delete ;
/*!
* \brief Constructs an object to build a
* class correlation matrix from a partition.
* \param bed_file_path the path to the file containing
* the references.
* \param bam_file_path the path to the file containing
* the targets.
* \param bai_file_path the path to index file of the bam
* file containing the targets.
* \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 bin_size the bin size in base pair.
* \param class_k the index (1-based) of the class of
* interest for which a matrix should be computed,
* from the partition.
* \param method how the targets should be counted.
* READ all the positions inside the reads are
* counted.
* READ_ATAC only the +4bp position of +strand reads
* and the -5bp of -strand reads are counted. It
* correspond to the insertion position in ATAC-seq
* data.
* FRAGMENT all the positions within fragments (the
* genome segment between a pair of reads, reads
* included) are counted.
* FRAGMENT_CENTER only the central position of the
* fragements (the genome segment between a pair of
* reads, reads included) are counted.
*/
ClassReadDataCreator(const std::string& bed_file_path,
const std::string& bam_file_path,
const std::string& bai_file_path,
const std::string& prob_file_path,
int from,
int to,
int bin_size,
size_t class_k,
CorrelationMatrixCreator::methods method) ;
/*!
* Destructor.
*/
~ClassReadDataCreator() ;
/*!
* \brief Computes the matrix and returns it.
* \return the class count matrix.
* The weighted averages are floating values
* however, they are rounded and returned as
* integer values.
*/
Matrix2D<int> create_matrix() ;
protected:
/*!
* \brief Bed file path.
*/
std::string bed_file_path ;
/*!
* \brief Bam file path.
*/
std::string bam_file_path ;
/*!
* \brief Bam index file path.
*/
std::string bai_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 bin size.
*/
int bin_size ;
/*!
* \brief the class of interest (0-based).
*/
size_t class_k ;
/*!
* \brief How to consider the sequenced fragments when computing
* the bin values.
*/
CorrelationMatrixCreator::methods method ;
} ;
#endif // CLASSREADDATACREATOR_HPP

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