Provided by: vienna-rna_2.5.1+dfsg-1_amd64 bug

NAME

       RNApvmin - manual page for RNApvmin 2.5.1

SYNOPSIS

       RNApvmin [options] <file.shape>

DESCRIPTION

       RNApvmin 2.5.1

       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 minimization process  to
       calculate a perturbation vector that minimizes the discripancies between predicted pairing
       probabilites and observed pairing probabilities (deduced from given  shape  reactivities).
       Experimental data is read from a given SHAPE file and normalized to pairing probabilities.
       The experimental data has to be provided in a multiline plain text file  where  each  line
       has the format '[position] [nucleotide] [absolute 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 minimization has terminated,
       the obtained perturbation vector is written to stdout.

       -h, --help
              Print help and exit

       --detailed-help
              Print help, including all details and hidden options, and exit

       --full-help
              Print help, including hidden options, and exit

       -V, --version
              Print version and exit

   General Options:
              Below are command line options which alter the general behavior of this program

       -j, --numThreads=INT
              Set the number of threads used for calculations.

       --shapeConversion=STRING
              Specify 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  represents
              probabilities for being unpaired rather than raw reactivity values

              'L': Use a linear model to convert the reactivity  into  a  probability  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=DOUBLE
              Ratio 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=INT
              The energies of the perturbation vector and the discripancies between predicted and
              observed pairing probabilities contribute to the objective function. This parameter
              defines, which function is used to process the contributions  before  summing  them
              up.  0 square 1 absolute.  (default=`0')

       --sampleSize=INT
              The  iterative  minimization  process  requires  to  evaluate  the  gradient 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 gradient by sampling the given number of
              sequences from the ensemble, which is much faster.

       -N, --nonRedundant
              Enable non-redundant sampling strategy.  (default=off)

       --intermediatePath=STRING Write 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 appended to the given path.

       --initialVector=DOUBLE
              Specify 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 results in a null vector. Every other value x
              will  be  used to populate the initial vector with random numbers from the interval
              [-x,x].

       --minimizer=ENUM
              Set the minimizing algorithm used for finding an appropriate  perturbation  vector.
              (possible  values="conjugate_fr",  "conjugate_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  algorithms  implemented  in the GNU
              Scientific Library. When the GNU Scientific Library can  not  be  found,  only  the
              default minimizer is available.

       --initialStepSize=DOUBLE
              The initial stepsize for the minimizer methods.  (default=`0.01')

       --minStepSize=DOUBLE
              The minimal stepsize for the minizimer methods.  (default=`1e-15')

       --minImprovement=DOUBLE
              The minimal improvement in the default minizimer method that has to be surpassed to
              considered a new result a better one.  (default=`1e-3')

       --minimizerTolerance=DOUBLE
              The tolerance to be used in the GSL minimizer

       methods.
              (default=`1e-3')

   Model Details:
       -S, --pfScale=DOUBLE
              Set scaling factor for Boltzmann factors to prevent under/overflows.

              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 double precision (see the README file).

       -T, --temp=DOUBLE
              Rescale energy parameters to a temperature in degrees centigrade.  (default=`37.0')

       -4, --noTetra
              Do not include special tabulated stabilizing energies for tri-, tetra- and hexaloop
              hairpins.  (default=off)

              Mostly for testing.

       -d, --dangles=INT
              Specify "dangling end" model for  bases  adjacent  to  helices  in  free  ends  and
              multi-loops.  (default=`2')

              With -d1 only unpaired bases can participate in at most one dangling end.  With -d2
              this 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  -d0  ignores  dangling  ends  altogether  (mostly  for
              debugging).   With  -d3 mfe folding will allow coaxial stacking of adjacent helices
              in multi-loops. At the moment the implementation will not allow coaxial stacking of
              the two interior pairs in a loop of degree 3 and works only for mfe folding.

              Note  that  with  -d1  and -d3 only the MFE computations will be using this setting
              while partition function uses -d2 setting,  i.e.  dangling  ends  will  be  treated
              differently.

       --noLP Produce 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 occur as helices of length 1.

       --noGU Do not allow GU pairs.  (default=off)

       --noClosingGU
              Do not allow GU pairs at the end of helices.  (default=off)

       -P, --paramFile=paramfile
              Read energy parameters from paramfile, instead of using the default parameter set.

              Different sets  of  energy  parameters  for  RNA  and  DNA  should  accompany  your
              distribution.   See  the  RNAlib documentation for details 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=STRING
              Allow 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  -GA   will  allow  GA  and  AG  pairs. Nonstandard pairs are given 0
              stacking energy.

       -e, --energyModel=INT
              Set 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 (-e 1) or AU (-e 2) pairs.

       --maxBPspan=INT
              Set the maximum base pair span.  (default=`-1')

REFERENCES

       If you use this program in your work you might want to cite:

       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 Structures", 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  thermodynamics  secondary  structure
       prediction" Nucl Acids Res: 40(10), pp 4261-4272

       The energy parameters are taken from:

       D.H.  Mathews,  M.D.  Disney, D. Matthew, J.L. Childs, S.J. Schroeder, J. Susan, M. Zuker,
       D.H. Turner (2004),  "Incorporating  chemical  modification  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
       280-282

EXAMPLES

       RNApvmin 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 reactivities 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 solution was found, the
       calculated perturbation vector will be print to stdout and can then  further  be  used  to
       constrain  RNAfold's  MFE/partition  function  calculation  by  applying  the perturbation
       energies as soft constraints.

         RNAfold --shape=sequence.pv --shapeMethod=W < sequence.fasta

AUTHOR

       Dominik Luntzer, Ronny Lorenz

REPORTING BUGS

       If in doubt our program is right,  nature  is  at  fault.   Comments  should  be  sent  to
       rna@tbi.univie.ac.at.