Local MFE Structure Prediction and Z-scores

Overview

// global functions

float vrna_Lfold (
    const char* string,
    int window_size,
    FILE* file
    )

float vrna_Lfoldz (
    const char* string,
    int window_size,
    double min_z,
    FILE* file
    )

float Lfold (
    const char* string,
    char* structure,
    int maxdist
    )

float Lfoldz (
    const char* string,
    char* structure,
    int maxdist,
    int zsc,
    double min_z
    )

float vrna_mfe_window (
    vrna_fold_compound_t* vc,
    FILE* file
    )

float vrna_mfe_window_zscore (
    vrna_fold_compound_t* vc,
    double min_z,
    FILE* file
    )

Detailed Documentation

Global Functions

float vrna_Lfold (
    const char* string,
    int window_size,
    FILE* file
    )
Local MFE prediction using a sliding window approach (simplified interface)

This simplified interface to vrna_mfe_window() computes the MFE and locally optimal secondary structure using default options. Structures are predicted using a sliding window approach, where base pairs may not span outside the window. Memory required for dynamic programming (DP) matrices will be allocated and free’d on-the-fly. Hence, after return of this function, the recursively filled matrices are not available any more for any post-processing.

Parameters:

string The nucleic acid sequence
window_size The window size for locally optimal structures
file The output file handle where predictions are written to (if NULL, output is written to stdout)

Note

In case you want to use the filled DP matrices for any subsequent post-processing step, or you require other conditions than specified by the default model details, use vrna_mfe_window() , and the data structure vrna_fold_compound_t instead.

float vrna_Lfoldz (
    const char* string,
    int window_size,
    double min_z,
    FILE* file
    )
Local MFE prediction using a sliding window approach with z-score cut-off (simplified interface)

This simplified interface to vrna_mfe_window_zscore() computes the MFE and locally optimal secondary structure using default options. Structures are predicted using a sliding window approach, where base pairs may not span outside the window. Memory required for dynamic programming (DP) matrices will be allocated and free’d on-the-fly. Hence, after return of this function, the recursively filled matrices are not available any more for any post-processing. This function is the z-score version of vrna_Lfold() , i.e. only predictions above a certain z-score cut-off value are printed.

Parameters:

string The nucleic acid sequence
window_size The window size for locally optimal structures
min_z The minimal z-score for a predicted structure to appear in the output
file The output file handle where predictions are written to (if NULL, output is written to stdout)

Note

In case you want to use the filled DP matrices for any subsequent post-processing step, or you require other conditions than specified by the default model details, use vrna_mfe_window() , and the data structure vrna_fold_compound_t instead.

float Lfold (
    const char* string,
    char* structure,
    int maxdist
    )
The local analog to fold() .

Computes the minimum free energy structure including only base pairs with a span smaller than ‘maxdist’

Deprecated Use vrna_mfe_window() instead!

float Lfoldz (
    const char* string,
    char* structure,
    int maxdist,
    int zsc,
    double min_z
    )
Deprecated Use vrna_mfe_window_zscore() instead!
float vrna_mfe_window (
    vrna_fold_compound_t* vc,
    FILE* file
    )
Local MFE prediction using a sliding window approach.

Computes minimum free energy structures using a sliding window approach, where base pairs may not span outside the window. In contrast to vrna_mfe() , where a maximum base pair span may be set using the vrna_md_t.max_bp_span attribute and one globally optimal structure is predicted, this function uses a sliding window to retrieve all locally optimal structures within each window. The size of the sliding window is set in the vrna_md_t.window_size attribute, prior to the retrieval of the vrna_fold_compound_t using vrna_fold_compound() with option VRNA_OPTION_WINDOW

The predicted structures are written on-the-fly, either to stdout, if a NULL pointer is passed as file parameter, or to the corresponding filehandle.

SWIG Wrapper Notes This function is attached as method mfe_window() to objects of type fold_compound

Parameters:

vc The vrna_fold_compound_t with preallocated memory for the DP matrices
file The output file handle where predictions are written to (maybe NULL)
float vrna_mfe_window_zscore (
    vrna_fold_compound_t* vc,
    double min_z,
    FILE* file
    )
Local MFE prediction using a sliding window approach (with z-score cut-off)

Computes minimum free energy structures using a sliding window approach, where base pairs may not span outside the window. This function is the z-score version of vrna_mfe_window() , i.e. only predictions above a certain z-score cut-off value are printed. As for vrna_mfe_window() , the size of the sliding window is set in the vrna_md_t.window_size attribute, prior to the retrieval of the vrna_fold_compound_t using vrna_fold_compound() with option VRNA_OPTION_WINDOW .

The predicted structures are written on-the-fly, either to stdout, if a NULL pointer is passed as file parameter, or to the corresponding filehandle.

Parameters:

vc The vrna_fold_compound_t with preallocated memory for the DP matrices
min_z The minimal z-score for a predicted structure to appear in the output
file The output file handle where predictions are written to (maybe NULL)