RNAeval - manual page for RNAeval 2.5.1
RNAeval [
OPTIONS] [
<input0>]
[
<input1>]...
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
- 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.
-
-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)
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
Ivo L Hofacker, Peter F Stadler, Ronny Lorenz
If in doubt our program is right, nature is at fault. Comments should be sent to
[email protected].