Provided by: vienna-rna_2.5.1+dfsg-1build3_amd64 
NAME
RNAeval - manual page for RNAeval 2.5.1
SYNOPSIS
RNAeval [OPTIONS] [<input0>] [<input1>]...
DESCRIPTION
RNAeval 2.5.1
Determine the free energy of a (consensus) secondary structure for (an alignment of) RNA sequence(s)
Evaluates the free energy of a particular (consensus) secondary structure for an (an alignment of) RNA
molecule(s). The energy unit is kcal/mol and contains a covariance pseudo-energy term for multiple
sequence alignments (--msa option) and corresponding consensus structures. The program will continue to
read new sequences and structures until a line consisting of the single character "@" or an end of file
condition is encountered. If the input sequence or structure contains the separator character "&" the
program calculates the energy of the co-folding of two RNA strands, where the "&" marks the boundary
between the two strands.
-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
--noconv
Do not automatically substitude nucleotide "T" with "U"
(default=off)
-v, --verbose
Print out energy contribution of each loop in the structure.
(default=off)
-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 sequence at a time.
Using this switch, a user can instead start the computation for many sequences in the input in
parallel. RNAeval will create as many parallel computation slots as specified and assigns input
sequences 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 RNAeval 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, RNAeval will not buffer individual results but print them as
soon as they have been computated.
-i, --infile=<filename>
Read a file instead of reading from stdin
The default behavior of RNAeval is to read input from stdin or the file(s) that follow(s) the
RNAeval command. Using this parameter the user can specify input file names where data is read
from. Note, that any additional files supplied to RNAeval are still processed as well.
-a, --msa
Input is multiple sequence alignment in Stockholm 1.0 format
(default=off)
Using this flag indicates that the input is a multiple sequence alignment (MSA) instead of (a)
single sequence(s). Note, that only STOCKHOLM format allows one to specify a consensus structure.
Therefore, this is the only supported MSA format for now!
--auto-id
Automatically generate an ID for each sequence. (default=off)
The default mode of RNAeval is to automatically determine an ID from the input sequence data if
the input file format allows to do that. Sequence IDs are usually given in the FASTA header of
input sequences. If this flag is active, RNAeval ignores any IDs retrieved from the input and
automatically generates an ID for each sequence. This ID consists of a prefix and an increasing
number. This flag can also be used to add a FASTA header to the output even if the input has none.
--id-prefix=prefix
Prefix for automatically generated IDs (as used in output file names)
(default=`sequence')
If this parameter is set, each sequence will be prefixed with the provided string. Note: Setting
this parameter implies --auto-id.
--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]. This option implies --auto-id.
--id-start=LONG
Specify the first number in automatically generated alignment IDs.
(default=`1')
When sequence 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 to ignore any IDs
retrieved from the input data, i.e. it activates the --auto-id flag.
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.
Mostly for testing.
(default=off)
-d, --dangles=INT
How to treat "dangling end" energies 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. 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.
-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.
-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.
-c, --circ
Assume a circular (instead of linear) RNA molecule.
(default=off)
-g, --gquad
Incoorporate G-Quadruplex formation into the structure prediction algorithm
(default=off)
--logML
Recalculate energies of structures using a logarithmic energy function for multi-loops before
output.
(default=off)
This option does not effect structure generation, only the energies that are printed out. Since
logML lowers energies somewhat, some structures may be missing.
--shape=SHAPE file
Use SHAPE reactivity data in the folding recursions (does not work for PF yet)
--shapeMethod=[D/Z/W] + [optional parameters]
Specify the method how to convert SHAPE
reactivity data to pseudo energy
contributions
(default=`D')
The following methods can be used to convert SHAPE reactivities into pseudo energy contributions.
'D': Convert by using a linear equation according to Deigan et al 2009. The calculated pseudo
energies will be applied for every nucleotide involved in a stacked pair. This method 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. 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".
'Z': Convert SHAPE reactivities to pseudo energies according to Zarringhalam et al 2012. SHAPE
reactivities will be converted to pairing probabilities by using linear mapping. Aberration from
the observed pairing probabilities will be penalized during the folding recursion. The magnitude
of the penalties can affected by adjusting the factor beta (e.g. --shapeMethod="Zb0.8").
'W': Apply a given vector of perturbation energies to unpaired nucleotides according to Washietl
et al 2012. Perturbation vectors can be calculated by using RNApvmin.
--shapeConversion=M/C/S/L/O
+ [optional parameters] Specify the method used to convert SHAPE
reactivities to pairing probabilities when
using the SHAPE approach of Zarringhalam et al.
(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. '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)
--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)
--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')
-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)
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 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
AUTHOR
Ivo L Hofacker, Peter F Stadler, 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.
RNAeval 2.5.1 April 2024 RNAEVAL(1)