RNAalifold − manual page for RNAalifold 2.4.11
RNAalifold [options] [<input0.aln>] [<input1.aln>]...
calculate secondary structures for a set of aligned RNAs
RNA sequences from stdin or file.aln and calculate their
minimum free energy (mfe) structure, partition function (pf)
and base pairing probability matrix. Currently, input
alignments have to be in CLUSTAL, Stockholm, FASTA, or MAF
format. The input format must be set manually in interactive
mode (default is Clustal), but will be determined
automagically from the input file, if not expplicitly set.
It returns the mfe structure in bracket notation, its
energy, the free energy of the thermodynamic ensemble and
the frequency of the mfe structure in the ensemble to
stdout. It also produces Postscript files with plots of the
resulting secondary structure graph ("alirna.ps")
and a "dot plot" of the base pairing matrix
("alidot.ps"). The file "alifold.out"
will contain a list of likely pairs sorted by credibility,
suitable for viewing with "AliDot.pl". Be warned
that output file will overwrite any existing files of the
Print help and exit
Print help, including all details and hidden options, and exit
Print help, including hidden options, and exit
Print version and exit
Command line options which alter the general behavior of this program
Be quiet. (default=off)
This option can be used to minimize the output of additional information and non−severe warnings which otherwise might spam stdout/stderr.
Split batch input into jobs and start processing in parallel using multiple threads. A value of 0 indicates to use as many parallel threads as computation cores are available.
Default processing of input data is performed in a serial fashion, i.e. one alignment at a time. Using this switch, a user can instead start the computation for many alignments in the input in parallel. RNAalifold will create as many parallel computation slots as specified and assigns input alignments of the input file(s) to the available slots. Note, that this increases memory consumption since input alignments have to be kept in memory until an empty compute slot is available and each running job requires its own dynamic programming matrices.
Do not try to keep output in order with input while parallel processing is in place.
When parallel input processing (−−jobs flag) is enabled, the order in which input is processed depends on the host machines job scheduler. Therefore, any output to stdout or files generated by this program will most likely not follow the order of the corresponding input data set. The default of RNAalifold is to use a specialized data structure to still keep the results output in order with the input data. However, this comes with a trade−off in terms of memory consumption, since all output must be kept in memory for as long as no chunks of consecutive, ordered output are available. By setting this flag, RNAalifold will not buffer individual results but print them as soon as they have been computated.
Do not automatically substitute nucleotide "T" with "U"
Produce a colored version of the consensus structure plot "alirna.ps" (default b&w only)
Produce a colored and structure annotated alignment in PostScript format in the file "aln.ps" in the current directory.
Number of columns in colored EPS alignment output.
A value less than 1 indicates that the output should not be wrapped at all.
Create a multi−Stockholm formatted output file. (default=‘RNAalifold_results’)
The default file name used for the output is "RNAalifold_results.stk". Users may change the filename to "prefix.stk" by specifying the prefix as optional argument. The file will be create in the current directory if it does not already exist. In case the file already exists, output will be appended to it. Note: Any special characters in the filename will be replaced by the filename delimiter, hence there is no way to pass an entire directory path through this option yet. (See also the "−−filename−delim" parameter)
Choose the layout algorithm. Simple radial layout if 0, or naview if 1
Do not produce postscript drawing of the mfe structure.
File format of the input multiple sequence alignment (MSA).
If this parameter is set, the input is considered to be in a particular file format. Otherwise, the program tries to determine the file format automatically, if an input file was provided in the set of parameters. In case the input MSA is provided in interactive mode, or from a terminal (TTY), the programs default is to assume CLUSTALW format. Currently, the following formats are available: ClustalW (C), Stockholm 1.0 (S), FASTA/Pearson (F), and MAF (M).
Use continuous alignment ID numbering when no alignment ID can be retrieved from input data.
Due to its past, RNAalifold produces a specific set of output file names for the first input alignment, "alirna.ps", "alidot.ps", etc. But for all further alignments in the input, it usually adopts a naming scheme based on IDs, which may be retrieved from the input alignment’s meta−data, or generated by a prefix followed by an increasing counter. Setting this flag instructs RNAalifold to use the ID naming scheme also for the first alignment.
Automatically generate an ID for each alignment.
The default mode of RNAalifold is to automatically determine an ID from the input alignment if the input file format allows to do that. Alignment IDs are, for instance, usually given in Stockholm 1.0 formatted input. If this flag is active, RNAalifold ignores any IDs retrieved from the input and automatically generates an ID for each alignment.
Prefix for automatically generated IDs (as used in output file names)
If this parameter is set, each alignment will be prefixed with the provided string. Hence, the output files will obey the following naming scheme: "prefix_xxxx_ss.ps" (secondary structure plot), "prefix_xxxx_dp.ps" (dot−plot), "prefix_xxxx_aln.ps" (annotated alignment), etc. where xxxx is the alignment number beginning with the second alignment in the input. Use this setting in conjunction with the −−continuous−ids flag to assign IDs beginning with the first input alignment.
Change the delimiter between prefix and increasing number for automatically generated IDs (as used in output file names)
This parameter can be used to change the default delimiter "_" between
the prefix string and the increasing number for automatically generated ID.
Specify the number of digits of the counter in automatically generated alignment IDs.
When alignments IDs are automatically generated, they receive an increasing number, starting with 1. This number will always be left−padded by leading zeros, such that the number takes up a certain width. Using this parameter, the width can be specified to the users need. We allow numbers in the range [1:18].
Specify the first number in automatically generated alignment IDs.
When alignment IDs are automatically generated, they receive an increasing number, usually starting with 1. Using this parameter, the first number can be specified to the users requirements. Note: negative numbers are not allowed. Note: Setting this parameter implies continuous alignment IDs, i.e. it activates the −−continuous−ids flag.
Change the delimiting character that is used
for sanitized filenames
This parameter can be used to change the delimiting character used while sanitizing filenames, i.e. replacing invalid characters. Note, that the default delimiter ALWAYS is the first character of the "ID delimiter" as supplied through the −−id−delim option. If the delimiter is a whitespace character or empty, invalid characters will be simply removed rather than substituted. Currently, we regard the following characters as illegal for use in filenames: backslash ’\’, slash ’/’, question mark ’?’, percent sign ’%’, asterisk ’*’, colon ’:’, pipe symbol ’|’, double quote ’"’, triangular brackets ’<’ and ’>’.
Command line options to interact with the structure constraints feature of this program
Set the maximum base pair span
structures subject to
The constraining structure will be read from ’stdin’, the alignment has to be given as a file name on the command line.
The program reads first the sequence, then a string containing constraints on the structure encoded with the symbols:
. (no constraint for this base)
| (the corresponding base has to be paired
x (the base is unpaired)
< (base i is paired with a base j>i)
> (base i is paired with a base j<i)
and matching brackets ( ) (base i pairs base j)
With the exception of "|", constraints will disallow all pairs conflicting with the constraint. This is usually sufficient to enforce the constraint, but occasionally a base may stay unpaired in spite of constraints. PF folding ignores constraints of type "|".
Use constraints for all alignment records. (default=off)
Usually, constraints provided from input file are only applied to a single sequence alignment. Therefore, RNAalifold will stop its computation and quit after the first input alignment was processed. Using this switch, RNAalifold processes all sequence alignments in the input and applies the same provided constraints to each of them.
Enforce base pairs given by round brackets ( ) in structure constraint
Use consensus structures from Stockholm file (#=GF SS_cons) as constraint
Stockholm formatted alignment files have the possibility to store a secondary structure string in one of if ("#=GC") column annotation meta tags. The corresponding tag name is usually "SS_cons", a consensus secondary structure. Activating this flag allows one to use this consensus secondary structure from the input file as structure constraint. Currently, only the following characters are interpreted:
( ) [mathing parenthesis: column i pairs with column j]
< > [matching angular brackets: column i pairs with column j]
All other characters are not interpreted (yet). Note: Activating this flag implies −−constraint.
Use SHAPE reactivity data to guide structure predictions
Multiple shapefiles for the individual sequences in the alignment may be specified as a comma separated list. An optional association of particular shape files to a specific sequence in the alignment can be expressed by prepending the sequence number to the filename, e.g. "5=seq5.shape,3=seq3.shape" will assign the reactivity values from file seq5.shape to the fifth sequence in the alignment, and the values from file seq3.shape to sequence 3. If no assignment is specified, the reactivity values are assigned to corresponding sequences in the order they are given.
Specify the method how to convert SHAPE reactivity data to pseudo energy contributions
Currently, the only data conversion method available is that of to Deigan et al 2009. This method is the default and is recognized by a capital ’D’ in the provided parameter, i.e.: −−shapeMethod="D" is the default setting. The slope ’m’ and the intercept ’b’ can be set to a non−default value if necessary. Otherwise m=1.8 and b=−0.6 as stated in the paper mentionen before. To alter these parameters, e.g. m=1.9 and b=−0.7, use a parameter string like this: −−shapeMethod="Dm1.9b−0.7". You may also provide only one of the two parameters like: −−shapeMethod="Dm1.9" or −−shapeMethod="Db−0.7".
Select additional algorithms which should be included in the calculations. The Minimum free energy (MFE) and a structure representative are calculated in any case.
Calculate the partition function and base pairing probability matrix in addition to the mfe structure. Default is calculation of mfe structure only.
In addition to the MFE structure we print a coarse representation of the pair probabilities in form of a pseudo bracket notation, followed by the ensemble free energy, as well as the centroid structure derived from the pair probabilities together with its free energy and distance to the ensemble. Finally it prints the frequency of the mfe structure.
An additionally passed value to this option changes the behavior of partition function calculation: −p0 deactivates the calculation of the pair probabilities, saving about 50% in runtime. This prints the ensemble free energy −kT ln(Z).
Calculate an MEA (maximum expected accuracy) structure, where the expected accuracy is computed from the pair probabilities: each base pair (i,j) gets a score 2*gamma*p_ij and the score of an unpaired base is given by the probability of not forming a pair.
The parameter gamma tunes the importance of correctly predicted pairs versus unpaired bases. Thus, for small values of gamma the MEA structure will contain only pairs with very high probability. Using −−MEA implies −p for computing the pair probabilities.
Output "most informative sequence" instead of simple consensus: For each column of the alignment output the set of nucleotides with frequency greater than average in IUPAC notation.
Stochastic backtrack. Compute a certain number of random structures with a probability dependend on the partition function. See −p option in RNAsubopt.
same as "−s" but also print out the energies and probabilities of the backtraced structures.
−S, −−pfScale=scaling factor
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).
Assume a circular (instead of linear) RNA molecule.
Set the threshold for base pair probabilities included in the postscript output
By setting the threshold the base pair probabilities that are included in the output can be varied. By default only those exceeding 1e−5 in probability will be shown as squares in the dot plot. Changing the threshold to any other value allows for increase or decrease of data.
Incoorporate G−Quadruplex formation into the structure prediction algorithm.
Compute the structure conservation index (SCI) for the MFE consensus structure of the alignment
Rescale energy parameters to a temperature of temp C. Default is 37C.
Do not include special tabulated stabilizing energies for tri−, tetra− and hexaloop hairpins.
Mostly for testing.
How to treat "dangling end" energies for bases adjacent to helices in free ends and multi−loops
With −d2 dangling energies will be added for the bases adjacent to a helix on both sides
in any case.
The option −d0 ignores dangling ends altogether (mostly for debugging).
Produce structures without lonely pairs (helices of length 1).
For partition function folding this only disallows pairs that can only occur isolated. Other pairs may still occasionally occur as helices of length 1.
Do not allow GU pairs
Do not allow GU pairs at the end of helices
Set the weight of the covariance term in the energy function
Set the penalty for non−compatible sequences in the covariance term of the energy function
Score pairs with endgaps same as gap−gap pairs.
use specified Ribosum Matrix instead of normal
energy model. Matrixes to use should be 6x6
matrices, the order of the terms is AU, CG, GC, GU, UA, UG.
use ribosum scoring matrix. The matrix is chosen according to the minimal and maximal pairwise identities of the sequences in the file.
use old energy evaluation, treating gaps as characters.
Read energy parameters from paramfile, instead of using the default parameter set.
A sample parameter file should accompany your distribution. See the RNAlib documentation for details on the file format.
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.
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.
Set the scaling of the Boltzmann factors (default=‘1.’)
The argument provided with this option enables to scale the thermodynamic temperature used in the Boltzmann factors independently from the temperature used to scale the individual energy contributions of the loop types. The Boltzmann factors then become exp(−dG/(kTn*betaScale)) where k is the Boltzmann constant, dG the free energy contribution of the state, T the absolute temperature and n the number of sequences.
Sequences are not weighted. If possible, do not mix very similar and dissimilar sequences. Duplicate sequences, for example, can distort the prediction.
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
The algorithm is a variant of the dynamic programming algorithms of M. Zuker and P. Stiegler (mfe) and J.S. McCaskill (pf) adapted for sets of aligned sequences with covariance information.
Ivo L. Hofacker, Martin Fekete, and Peter F. Stadler (2002), "Secondary Structure Prediction for Aligned RNA Sequences", J.Mol.Biol.: 319, pp 1059-1066.
Stephan H. Bernhart, Ivo L. Hofacker, Sebastian Will, Andreas R. Gruber, and Peter F. Stadler (2008), "RNAalifold: Improved consensus structure prediction for RNA alignments", BMC Bioinformatics: 9, pp 474
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
Ivo L Hofacker, Stephan Bernhart, Ronny Lorenz
If in doubt our program is right, nature is at fault. Comments should be sent to email@example.com.
The ALIDOT package http://www.tbi.univie.ac.at/RNA/Alidot/