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RNAPVMIN(1) User Commands RNAPVMIN(1)NAMERNApvmin - manual page for RNApvmin 2.4.18SYNOPSISRNApvmin[options] _file.shape_DESCRIPTIONRNApvmin 2.4.18 Calculate a perturbation vector that minimizes discripancies between predicted and observed pairing probabilities The program reads a RNA sequence from stdin and uses an iterative mini- mization process to calculate a perturbation vector that minimizes the discripancies between predicted pairing probabilites and observed pair- ing probabilities (deduced from given shape reactivities). Experimental data is read from a given SHAPE file and normalized to pairing proba- bilities. The experimental data has to be provided in a multiline plain text file where each line has the format '[position] [nucleotide] [ab- solute shape reactivity]' (e.g. '3 A 0.7'). The objective function used for the minimization may be weighted by choosing appropriate values for sigma and tau. The minimization progress will be written to stderr. Once the minimiza- tion has terminated, the obtained perturbation vector is written to stdout.-h,--helpPrint help and exit--detailed-helpPrint help, including all details and hidden options, and exit--full-helpPrint help, including hidden options, and exit-V,--versionPrint version and exitGeneralOptions:Below are command line options which alter the general behavior of this program-j,--numThreads=INTSet the number of threads used for calculations.--shapeConversion=STRINGSpecify the method used to convert SHAPE reactivities to pairing probabilities. (default=`O') The following methods can be used to convert SHAPE reactivities into the probability for a certain nucleotide to be unpaired. 'M': Use linear mapping according to Zarringhalam et al. 2012 'C': Use a cutoff-approach to divide into paired and unpaired nucleotides (e.g. "C0.25") 'S': Skip the normalizing step since the input data already rep- resents probabilities for being unpaired rather than raw reac- tivity values 'L': Use a linear model to convert the reactivity into a proba- bility for being unpaired (e.g. "Ls0.68i0.2" to use a slope of 0.68 and an intercept of 0.2) 'O': Use a linear model to convert the log of the reactivity into a probability for being unpaired (e.g. "Os1.6i-2.29" to use a slope of 1.6 and an intercept of-2.29)--tauSigmaRatio=DOUBLERatio of the weighting factors tau and sigma. (default=`1.0') A high ratio will lead to a solution as close as possible to the experimental data, while a low ratio will lead to results close to the thermodynamic prediction without guiding pseudo energies.--objectiveFunction=INTThe energies of the perturbation vector and the discripancies between predicted and observed pairing probabilities contribute to the objective function. This parameter defines, which func- tion is used to process the contributions before summing them up. 0 square 1 absolute. (default=`0')--sampleSize=INTThe iterative minimization process requires to evaluate the gra- dient of the objective function. (default=`1000') A sample size of 0 leads to an analytical evaluation which scales as O(N^4). Choosing a sample size >0 estimates the gra- dient by sampling the given number of sequences from the ensem- ble, which is much faster.-N,--nonRedundantEnable non-redundant sampling strategy. (default=off)--intermediatePath=STRINGWrite an output file for each iteration of the minimization process. Each file contains the used perturbation vector and the score of the objective function. The number of the iteration will be ap- pended to the given path.--initialVector=DOUBLESpecify the vector of initial pertubations. (default=`0') Defines the initial perturbation vector which will be used as starting vector for the minimization process. The value 0 re- sults in a null vector. Every other value x will be used to pop- ulate the initial vector with random numbers from the interval [-x,x].--minimizer=ENUMSet the minimizing algorithm used for finding an appropriate perturbation vector. (possible values="conjugate_fr", "conju- gate_pr", "vector_bfgs", "vector_bfgs2", "steepest_descent", "default" default=`default') The default option uses a custom implementation of the gradient descent algorithms while all other options represent various al- gorithms implemented in the GNU Scientific Library. When the GNU Scientific Library can not be found, only the default minimizer is available.--initialStepSize=DOUBLEThe initial stepsize for the minimizer methods. (de- fault=`0.01')--minStepSize=DOUBLEThe minimal stepsize for the minizimer methods. (de- fault=`1e-15')--minImprovement=DOUBLEThe minimal improvement in the default minizimer method that has to be surpassed to considered a new result a better one. (de- fault=`1e-3')--minimizerTolerance=DOUBLEThe tolerance to be used in the GSL minimizer methods. (default=`1e-3')ModelDetails:-S,--pfScale=DOUBLESet scaling factor for Boltzmann factors to prevent under/over- flows. In the calculation of the pf use scale*mfe as an estimate for the ensemble free energy (used to avoid overflows). The default is 1.07, useful values are 1.0 to 1.2. Occasionally needed for long sequences. You can also recompile the program to use dou- ble precision (see the README file).-T,--temp=DOUBLERescale energy parameters to a temperature in degrees centi- grade. (default=`37.0')-4,--noTetraDo not include special tabulated stabilizing energies for tri-, tetra- and hexaloop hairpins. (default=off) Mostly for testing.-d,--dangles=INTSpecify "dangling end" model for bases adjacent to helices in free ends and multi-loops. (default=`2') With-d1only unpaired bases can participate in at most one dan- gling end. With-d2this check is ignored, dangling energies will be added for the bases adjacent to a helix on both sides in any case; this is the default for mfe and partition function folding (-p). The option-d0ignores dangling ends altogether (mostly for debugging). With-d3mfe folding will allow coaxial stacking of adjacent helices in multi-loops. At the moment the implementation will not allow coaxial stacking of the two inte- rior pairs in a loop of degree 3 and works only for mfe folding. Note that with-d1and-d3only the MFE computations will be us- ing this setting while partition function uses-d2setting, i.e. dangling ends will be treated differently.--noLPProduce structures without lonely pairs (helices of length 1). (default=off) For partition function folding this only disallows pairs that can only occur isolated. Other pairs may still occasionally oc- cur as helices of length 1.--noGUDo not allow GU pairs. (default=off)--noClosingGUDo not allow GU pairs at the end of helices. (default=off)-P,--paramFile=paramfileRead energy parameters from paramfile, instead of using the de- fault parameter set. Different sets of energy parameters for RNA and DNA should ac- company your distribution. See the RNAlib documentation for de- tails on the file format. When passing the placeholder file name "DNA", DNA parameters are loaded without the need to actually specify any input file.--nsp=STRINGAllow other pairs in addition to the usual AU,GC,and GU pairs. Its argument is a comma separated list of additionally allowed pairs. If the first character is a "-" then AB will imply that AB and BA are allowed pairs. e.g. RNAfold-nsp-GAwill allow GA and AG pairs. Nonstandard pairs are given 0 stacking energy.-e,--energyModel=INTSet energy model. Rarely used option to fold sequences from the artificial ABCD... alphabet, where A pairs B, C-D etc. Use the energy parameters for GC (-e1) or AU (-e2) pairs.--maxBPspan=INTSet the maximum base pair span. (default=`-1')REFERENCESIfyouusethisprograminyourworkyoumightwanttocite:R. Lorenz, S.H. Bernhart, C. Hoener zu Siederdissen, H. Tafer, C. Flamm, P.F. Stadler and I.L. Hofacker (2011), "ViennaRNA Package 2.0", Algorithms for Molecular Biology: 6:26 I.L. Hofacker, W. Fontana, P.F. Stadler, S. Bonhoeffer, M. Tacker, P. Schuster (1994), "Fast Folding and Comparison of RNA Secondary Struc- tures", Monatshefte f. Chemie: 125, pp 167-188 R. Lorenz, I.L. Hofacker, P.F. Stadler (2016), "RNA folding with hard and soft constraints", Algorithms for Molecular Biology 11:1 pp 1-13 S. Washietl, I.L. Hofacker, P.F. Stadler, M. Kellis (2012) "RNA folding with soft constraints: reconciliation of probing data and thermodynam- ics secondary structure prediction" Nucl Acids Res: 40(10), pp 4261-4272Theenergyparametersaretakenfrom:D.H. Mathews, M.D. Disney, D. Matthew, J.L. Childs, S.J. Schroeder, J. Susan, M. Zuker, D.H. Turner (2004), "Incorporating chemical modifica- tion constraints into a dynamic programming algorithm for prediction of RNA secondary structure", Proc. Natl. Acad. Sci. USA: 101, pp 7287-7292 D.H Turner, D.H. Mathews (2009), "NNDB: The nearest neighbor parameter database for predicting stability of nucleic acid secondary structure", Nucleic Acids Research: 38, pp 280-282EXAMPLESRNApvmin acceptes a SHAPE file and a corresponding nucleotide sequence, which is read form stdin. RNApvmin sequence.shape < sequence.fasta > sequence.pv The normalized SHAPE reactivity data has to be stored in a text file, where each line contains the position and the reactivity for a certain nucleotide ([position] [nucleotide] [SHAPE reactivity]). 1 A 1.286 2 U 0.383 3 C 0.033 4 C 0.017 ... ... 98 U 0.234 99 G 0.885 The nucleotide information in the SHAPE file is optional and will be used to cross check the given input sequence if present. If SHAPE re- activities could not be determined for every nucleotide, missing values can simply be omited. The progress of the minimization will be printed to stderr. Once a so- lution was found, the calculated perturbation vector will be print to stdout and can then further be used to constrain RNAfold's MFE/parti- tion function calculation by applying the perturbation energies as soft constraints. RNAfold --shape=sequence.pv --shapeMethod=W < sequence.fastaAUTHORDominik Luntzer, Ronny LorenzREPORTING BUGSIf in doubt our program is right, nature is at fault. Comments should be sent to rna@tbi.univie.ac.at. RNApvmin 2.4.18 April 2021 RNAPVMIN(1)

NAME | SYNOPSIS | DESCRIPTION | REFERENCES | EXAMPLES | AUTHOR | REPORTING BUGS

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