Provided by: vienna-rna_2.4.17+dfsg-2build2_amd64 
NAME
RNAalifold - manual page for RNAalifold 2.4.17
SYNOPSIS
RNAalifold [options] [<input0.aln>] [<input1.aln>]...
DESCRIPTION
RNAalifold 2.4.17
calculate secondary structures for a set of aligned RNAs
Read aligned 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 same name.
-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:
Command line options which alter the general behavior of this program
-v, --verbose
Be verbose.
(default=off)
-q, --quiet
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.
-j, --jobs[=number]
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=`0')
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.
--unordered
Do not try to keep output in order with input while parallel processing is in
place.
(default=off)
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.
--noconv
Do not automatically substitute nucleotide "T" with "U"
(default=off)
--color
Produce a colored version of the consensus structure plot "alirna.ps" (default b&w
only)
(default=off)
--aln Produce a colored and structure annotated alignment in PostScript format in the
file "aln.ps" in the current directory.
(default=off)
--aln-EPS-cols=INT
Number of columns in colored EPS alignment output.
(default=`60')
A value less than 1 indicates that the output should not be wrapped at all.
--aln-stk[=prefix]
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)
-t, --layout-type=INT
Choose the layout algorithm. Simple radial layout if 0, or naview if 1
(default=`1')
--noPS Do not produce postscript drawing of the mfe structure.
(default=off)
--noDP Do not produce dot-plot postscript file containing base pair or stack
probabilitities.
(default=off)
In combination with the -p option, this flag turns-off creation of individual
dot-plot files. Consequently, computed base pair probability output is omitted but
centroid and MEA structure prediction is still performed.
-f, --input-format=C|S|F|M
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).
-n, --continuous-ids
Use continuous alignment ID numbering when no alignment ID can be retrieved from
input data.
(default=off)
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.
--auto-id
Automatically generate an ID for each alignment.
(default=off)
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.
--id-prefix=prefix
Prefix for automatically generated IDs (as used in output file names)
(default=`alignment')
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.
--id-delim=delimiter
Change the delimiter between prefix and increasing number for automatically
generated IDs (as used in output file names)
(default=`_')
This parameter can be used to change the default delimiter "_" between
the prefix string and the increasing number for automatically generated ID.
--id-digits=INT
Specify the number of digits of the counter in automatically generated alignment
IDs.
(default=`4')
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].
--id-start=LONG
Specify the first number in automatically generated alignment IDs.
(default=`1')
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.
--filename-delim=delimiter
Change the delimiting character that is used
for sanitized filenames
(default=`ID-delimiter')
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 '>'.
Structure Constraints:
Command line options to interact with the structure constraints feature of this
program
--maxBPspan=INT
Set the maximum base pair span
(default=`-1')
-C, --constraint[=<filename>] Calculate structures subject to constraints.
The constraining structure will be read from 'stdin', the alignment has to be given
as a file name on the command line.
(default=`')
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 "|".
--batch
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.
--enforceConstraint
Enforce base pairs given by round brackets ( ) in structure constraint
(default=off)
--SS_cons
Use consensus structures from Stockholm file (#=GF SS_cons) as constraint
(default=off)
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.
--shape=file1,file2
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.
--shapeMethod=D[mX][bY]
Specify the method how to convert SHAPE reactivity data to pseudo energy
contributions
(default=`D')
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".
Algorithms:
Select additional algorithms which should be included in the calculations. The
Minimum free energy (MFE) and a structure representative are calculated in any
case.
-p, --partfunc[=INT]
Calculate the partition function and base pairing probability matrix in addition to
the mfe structure. Default is calculation of mfe structure only.
(default=`1')
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).
--MEA[=gamma]
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.
(default=`1.')
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.
--mis 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.
(default=off)
-s, --stochBT=INT
Stochastic backtrack. Compute a certain number of random structures with a
probability dependend on the partition function. See -p option in RNAsubopt.
--stochBT_en=INT
same as "-s" but also print out the energies and probabilities of the backtraced
structures.
-N, --nonRedundant
Enable non-redundant sampling strategy.
(default=off)
-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).
-c, --circ
Assume a circular (instead of linear) RNA molecule.
(default=off)
--bppmThreshold=<value>
Set the threshold for base pair probabilities included in the postscript output
(default=`1e-6')
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.
-g, --gquad
Incoorporate G-Quadruplex formation into the structure prediction algorithm.
(default=off)
--sci Compute the structure conservation index (SCI) for the MFE consensus structure of
the alignment
(default=off)
Model Details:
-T, --temp=DOUBLE
Rescale energy parameters to a temperature of temp C. Default is 37C.
-4, --noTetra
Do not include special tabulated stabilizing energies for tri-, tetra- and hexaloop
hairpins.
(default=off)
Mostly for testing.
-d, --dangles=INT
How to treat "dangling end" energies for bases adjacent to helices in free ends and
multi-loops
(default=`2')
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).
--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)
--cfactor=DOUBLE
Set the weight of the covariance term in the energy function
(default=`1.0')
--nfactor=DOUBLE
Set the penalty for non-compatible sequences in the covariance term of the energy
function
(default=`1.0')
-E, --endgaps
Score pairs with endgaps same as gap-gap pairs.
(default=off)
-R, --ribosum_file=ribosumfile
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.
-r, --ribosum_scoring
use ribosum scoring matrix. The matrix is chosen according to the minimal and
maximal pairwise identities of the sequences in the file.
(default=off)
--old use old energy evaluation, treating gaps as characters.
(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
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.
--betaScale=DOUBLE
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.
Caveats:
Sequences are not weighted. If possible, do not mix very similar and dissimilar sequences.
Duplicate sequences, for example, can distort the prediction.
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
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
EXAMPLES
A simple call to compute consensus MFE structure, ensemble free energy, base pair
probabilities, centroid structure, and MEA structure for a multiple sequence alignment
(MSA) provided as Stockholm formatted file alignment.stk might look like:
$ RNAalifold -p --MEA alignment.stk
Consider the following MSA file for three sequences
# STOCKHOLM 1.0
#=GF AC RF01293
#=GF ID ACA59
#=GF DE Small nucleolar RNA ACA59
#=GF AU Wilkinson A
#=GF SE Predicted; WAR; Wilkinson A
#=GF SS Predicted; WAR; Wilkinson A
#=GF GA 43.00
#=GF TC 44.90
#=GF NC 40.30
#=GF TP Gene; snRNA; snoRNA; HACA-box;
#=GF BM cmbuild -F CM SEED
#=GF CB cmcalibrate --mpi CM
#=GF SM cmsearch --cpu 4 --verbose --nohmmonly -E 1000 -Z 549862.597050 CM SEQDB
#=GF DR snoRNABase; ACA59;
#=GF DR SO; 0001263; ncRNA_gene;
#=GF DR GO; 0006396; RNA processing;
#=GF DR GO; 0005730; nucleolus;
#=GF RN [1]
#=GF RM 15199136
#=GF RT Human box H/ACA pseudouridylation guide RNA machinery.
#=GF RA Kiss AM, Jady BE, Bertrand E, Kiss T
#=GF RL Mol Cell Biol. 2004;24:5797-5807.
#=GF WK Small_nucleolar_RNA
#=GF SQ 3
AL031296.1/85969-86120 CUGCCUCACAACGUUUGUGCCUCAGUUACCCGUAGAUGUAGUGAGGGUAACAAUACUUACUCUCGUUGGUGAUAAGGAACAGCU
AANU01225121.1/438-603 CUGCCUCACAACAUUUGUGCCUCAGUUACUCAUAGAUGUAGUGAGGGUGACAAUACUUACUCUCGUUGGUGAUAAGGAACAGCU
AAWR02037329.1/29294-29150 ---CUCGACACCACU---GCCUCGGUUACCCAUCGGUGCAGUGCGGGUAGUAGUACCAAUGCUAAUUAGUUGUGAGGACCAACU
#=GC SS_cons -----((((,<<<<<<<<<___________>>>>>>>>>,,,,<<<<<<<______>>>>>>>,,,,,))))::::::::::::
#=GC RF CUGCcccaCAaCacuuguGCCUCaGUUACcCauagguGuAGUGaGgGuggcAaUACccaCcCucgUUgGuggUaAGGAaCAgCU
//
Then, the above program call will produce this output:
3 sequences; length of alignment 84.
>ACA59
CUGCCUCACAACAUUUGUGCCUCAGUUACCCAUAGAUGUAGUGAGGGUAACAAUACUUACUCUCGUUGGUGAUAAGGAACAGCU
...((((((.(((((((((...........))))))))).))))))..........(((((......)))))............ (-12.54 = -12.77 + 0.23)
...((((((.(((((((((...........))))))))).)))))){{,.......{{{{,......}))))............ [-14.38]
...((((((.(((((((((...........))))))))).))))))..........((((........))))............ {-12.44 = -12.33 + -0.10 d=10.94}
...((((((.(((((((((...........))))))))).))))))..........((((........))))............ {-12.44 = -12.33 + -0.10 MEA=66.65}
frequency of mfe structure in ensemble 0.368739; ensemble diversity 17.77
Here, the first line is written to stderr and simply states the number of sequences and
the length of the alignment. This line can be suppressed using the --quiet option. The
main output then consists of 7 lines, where the first two resemble the FASTA header with
the ID as read from the input data set, followed by the consensus sequence in the second
line. The third line consists of the consensus secondary structure in dot-bracket notation
followed by the averaged minimum free energy in parenthesis. This energy is composed of
two major contributions, the actual free energies derived from the Nearest Neighbor model,
and the covariance pseudo-energy term, which are both displayed after the equal sign. The
fourth line shows the base pair propensity in pseudo dot-bracket notation followed by the
ensemble free energy dG = -kT ln(Z) in square brackets. Similarly, the next two lines
state the controid- and the MEA structure in dot-bracket notation, followed by their
corresponding free energy contributions, the mean distance (d) to the ensemble as well as
the maximum expected accuracy (MEA). Again, the free energies are split into Nearest
Neighbor contribution and the covariance pseudo-energy term.
Furthermore, RNAalifold will produce three output files: ACA59_ss.ps, ACA59_dp.ps, and
ACA59_ali.out that contain the secondary structure drawing, the base pair probability dot-
plot, and a detailed table of base pair probabilities, respectively.
THE ALIOUT FILE
When computing base pair probabilities (--partfunc option), RNAalifold will produce a file
with the suffix `ali.out`. This file contains the base pairing probabilities between
different alignment columns together with some detailed statistics for the individual
sequences within the alignment. The file is a simple text file with a two line header that
states the number of sequences and length of the alignment. The first couple of lines of
this file may look like:
3 sequence; length of alignment 84
alifold output
14 36 0 92.7% 0.212 CG:1 UA:2
13 37 0 92.7% 0.218 GU:1 AU:2
12 38 0 92.7% 0.231 CG:3
15 35 0 91.9% 0.239 UG:3
16 34 0 85.2% 0.434 UA:2 --:1
8 42 0 80.7% 0.526 AU:3 +
9 41 0 80.4% 0.542 CG:3 +
7 43 1 80.1% 0.541 CG:2 +
Starting with the third row, there are at least six and at most 13 columns separated by
whitespaces stating: (1) the i-position and (2) the j-position of a potential base pair
(i, j), followed by (3) the number of counter examples, i.e. the number of sequences in
the alignment that can't form a canonical base pair with their respective sequence
positions. Next is (4) the base pair probabilitiy in percent, (5) a pseudo entropy
measure S_ij = S_i + S_j - p_ij ln(p_ij), where S_i and S_j are the positional entropies
for the two alignment columns i and j, and p_ij is the base pair probability. Finally, the
last columns (6-12) state the number of particular base pairs for the individual sequences
in the alignment. Here, we distinguish the base pairs "GC","CG","AU","UA","GU","UG", and
the special case "--" that represents gaps at both positions i and j. Finally, base pairs
that are not part of the MFE structure are marked by an additional "+" sign in the last
column.
AUTHOR
Ivo L Hofacker, Stephan Bernhart, 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.
SEE ALSO
The ALIDOT package http://www.tbi.univie.ac.at/RNA/Alidot/