MLOCARNA(1)

NAME
MLocARNA - multiple alignment of RNA

SYNOPSIS
mlocarna [options] <fasta file>

DESCRIPTION
MLocarna computes a multiple sequence-structure alignment of RNA sequences. The structure of these sequences does not have to be known but is inferred based in simultaneous alignment and folding.

Generally, mlocarna takes multiple sequences as input, given in a fasta file. The fasta file can be extended to specify structure and anchor constraints that respectively control the possible foldings and possible alignments. The main outcome is a multiple alignment together with a consensus structure.

Technically, mlocarna works as front end to the pairwise alignment tools locarna, locarna_p, and sparse (and even carna), which are employed to construct the multiple alignment progressively.

Going beyond the basic progressive alignment scheme, Mlocarna implements probabilistic consistency transformation and iterative alignment, which are available in probabilistic mode. Moreover, the LocARNA package provides an alternative multiple alignment tool "locarante", which generates alignments based on T-Coffee using (non-probabilistic) consistency transformation.

OPTIONS

  Load configurations from file

--configure=file
    Load a parameter set from a configuration file of options and option value pairs. This enables specifying (sets of) default parameters for mlocarna, which can still be modified by other options to mlocarna. Command line arguments always take precedence over this configuration. Options are specified as single entries per line; option value pairs, like option: value. Whitespace and '#'-prefixed comments are ignored.

  Major alignment modes

    By default, mlocarna performs progressive alignment, where the progressive alignment steps are computed by the pairwise aligner locarna based on sequences and dot plots (RNAfold -p); subsequently, partial alignmetns and their consensus dot plots.

--probabilistic
    In probabilistic mode, mlocarna scores alignments using match probabilities that are computed by a partition function approach [tech. details: the probability computation is implemented in locarna_p; the probability-based scoring is performed by locarna in mea mode]. This enables mlocarna to consistency-transform the probabilities (option --consistency-transform) and to compute reliabilities. The tool reliability-profile.pl is provided to visualize reliability profiles. Reliabilities can also be used for iterating the alignment with reliably aligned base pairs as structural constraints (option --it-reliable-structure).

--sparse
    Apply the sparsified alignment algorithm SPARSE for all pairwise alignments (instead of the default pairwise aligner locarna). SPARSE supports stronger sparsification for faster alignment computation and increases the structure prediction capabilities over locarna.

  Controlling Output

--tgtdir
    Target directory. All output files are written to this directory. Per default the target directory is generated from the input filename by replacing suffix fa by (or appending) out.

-v, --verbose
    Turn on verbose ouput. Shows progress of computation of all-2-all pairwise alignments for guide tree computation; shows intermediary alignments during the progressive alignment computation.

--moreverbose
    Be even more verbose: additionally shows parameters for the pairwise aligner; moreover, the calls and output of the RNA base pair probability computations as well as the pairwise aligner during progressive alignment.

-q, --quiet
    Be quiet.

--keep-sequence-order
    Preserve sequence order of the input in the final alignment. Affects output to stdout and results/result.aln.

--stockholm
    Write STOCKHOLM files of all final and intermediate alignments (in addition to CLUSTALW files).

-w,--width=columns(120)
    Output width for sequences in clustal-like and stockholm output; note that the clustalw standard format requires 60 or less.

--write-structure
    Write guidance structure in output to stdout. This provides some insight into the influence of structure into the generated pairwise alignments. The guidance structure shows the base pairs 'predicted' by each pairwise locarna (or sparse) alignment. These structures should not be mistaken as predicted consensus structures of multiple alignments. Consensus structures can be more adequately derived from the multiple alignment. For this reason, mlocarna reports the consensus structure by RNAalifold.

  Locality

--free-endgaps
    Allow free endgaps. (Corresponds to pairwise locarna option --free-endgaps "++++".)

--free-endgaps-3
    Allow free endgaps 3'.

--free-endgaps-5
    Allow free endgaps 5'.

--sequ-local=bool(false)
    Turns on/off sequence locality [def=off]. Sequence locality refers to the usual form of local alignment. If on, mlocarna bases all calculations on local pairwise alignments, which determin the best alignments of subsequences (disregarding dissimilar starts and ends). Note that truely local structure alignments as well as local multiple alignments are still a matter of research; so don't expect perfect results in all instances.

--struct-local=bool(false)
    Turns on/off structure locality [def=off]. Structural locality enables skipping entire substructures in alignments. In pairwise alignments, this allows one exclusion of some subsequence in each loop; thus, guaranteeing that the (structure locally) aligned parts of the sequences are always connected w.r.t. the predicted structure but not necessarily consecutive in the sequence. Structure locality does not imply sequence locality, but rather the two concepts are orthogonal.

--penalized=score
    Variant of sequence local alignment (cf. --sequ-local), where the specified penalty score is subtracted for each base in the local alignment. [Experimental]

  Pairwise alignment and scoring

--indel=score(-350)
    Score of each single base insertion or deletion.

--indel-opening=score(-500)
    Score of opening an insertion or deletion, i.e. score for a consecutive run of deletions or insertions. Indel opening score and indel score define the affine scoring of gaps.

-m,--match=score(50)
    Score of a base match (unless ribosum-based scoring)

-M,--mismatch=score(0)
    Score of a base mismatch (unless ribosum-based scoring)

--use-ribosum=bool(true)
    Use ribosum scores for scoring base matches and base pair matches; note that tau=0 suppresses any effect on the latter.

--ribosum-file=file
    File specifying the Ribosum base and base-pair similarities. [default: use RIBOSUM85_60 without requiring a Ribosum file.]

-s,--struct-weight=score(200)
    Maximum weight of one predicted arc, aka base pair. Note that this means that the maximum weight of an arc match is twice as high. The maximum weight is assigned to base pairs with (almost) probability 1 in the dot plot; less probable base pairs receive gradually degrading scores. The struct-weight factor balances the score contribution from structure to the score contribution from base similarity scores (e.g. ribosum scores).

-e,--exp-prob=prob
    Expected probability of a base pair.

-t,--tau=factor(0)
    Tau factor in percent. The tau factor controls the contribution of sequence-dependent scores to the score of arc matches.

-E,--exclusion=<score>(0)
    Weight of an exclusion, i.e. an ommitted subsequence in a loop, which applies only to structural local alignment.

--stacking
    Use stacking terms. In this case, stacked arcs are scored based on conditional probabilities (conditioned by their stacked inner arc) rather than unconditioned base pair probabilities. [Experimental]

--new-stacking
    Use new stacking terms; cf. --stacking. These terms directly award bonuses to stacking. [Experimental]

  Alignment heuristics
Several parameters are available to speed up the pairwise alignment computations heuristically. Choosing these parameters reasonably is necessary to achieve good trade-off between speed and accuracy, especially for large alignment instances.

-p,--min-prob=probability(0.0005)
    Minimum base pair / arc probability. Arc with lower probability in the input RNA structure ensembles are ignored.

-P, --tree-min-prob=probability
    Minimal prob for constructing guide tree. This probability can be set separately for the all-2-all comparison for constructing the guide tree and the progressive/iterative alignment steps.

--max-bps-length-ratio=factor(0.0)
    Maximal ratio of the number of base pairs divided by sequence length (default: no effect)

-D,--max-diff-am=difference
    Maximal difference for lengths of matched arcs. Two arcs that have a higher difference of their lengths are ignored. This speeds up the alignment, since less arc comparisons (i.e. less DP matrices) have to be computed. [def: off/-1]

-d,--max-diff=difference
    Maximal difference of the positions of any two bases that are considered to be aligned. Bases with higher difference are generally not aligned. This allows banding of the DP matrices and thus can result in high speed ups. Note that the semantic changes in the context of a reference alignment specified with max-diff-aln. Then, the difference to the reference alignment is restricted. [def: off/-1]

--max-diff-at-am=difference
    Same restriction as max-diff but only at the ends of arcs in arc matches. [def: off/-1]

--max-diff-aln=file
    Computes "realignment" in the environment of the given reference alignment (file in clustalw format) by constraining the maximum difference to this reference (controlled by --max-diff). The input sequences (and their names) have to be identical to these alignment sequences; however the alignment is allowed to contain extra sequences, which are ignored.

--max-diff-relax
    Relax deviation constraints (cf. --max-diff-aln) in multiple aligmnent. This option is useful if the default strategy for realignment fails.

-a,--min-am-prob=probability(0.0005)
    Minimum arc-match probability (filters output of locarna-p)

-b,--min-bm-prob=probability(0.0005)
    Minimum base-match probability (filters output of locarna-p)

  Low-level selection of pairwise alignment tools and options

--pw-aligner
    Utilize the given tool for computing pairwise alignments (def=locarna).

--pw-aligner-p=tool
    Utilize the given tool for computing partition function pairwise alignments (def=locarna_p).

--pw-aligner-options
    Additional option string for the pairwise alignment tool (def="").

--pw-aligner-p-options
    Additional option string for the partition function pairwise alignment tool (def="").

  Controlling the guide tree construction

--treefile=file
    File with guide tree in NEWICK format. The given tree is used as guide tree for the progressive alignment. This saves the calculation of pairwise all-vs-all similarities and construction of the guide tree.

--similarity-matrix=file
    File with similarity matrix. The similarities in the matrix are used to construct the guide tree for the progressive alignment. This saves the calculation of pairwise all-vs-all similarities.

--graphkernel
    Use the graphkernel for constructing the guide tree.

--svmsgdnspdk[=program]
    Specify the svmsgdnspdk program (potentially including path). Default: use "svmsgdnspdk" in path.

--fasta2shrep=program
    Program "fasta2shrep" for generating graphs from the input sequences for use with the graph kernel guide tree generation (potentially including path). Default: use "fasta2shrep_gspan.pl" in path.

--fasta2shrep-options=argument-string
    Command line arguments for fasta2shrep. Default: "-wins 200 -shift 50 -stack -t 3 -M 3".

  Controlling multiple alignment construction

--alifold-consensus-dp
    Employs RNAalifold -p for generating consensus dotplot after each progressive alignment step. This replaces the default consensus dotplot computation, which averages over the input dot plots. This method should be used with care in combination with structural constraints, since it ignores them for all but the pairwise alignments of single sequences. Furthermore, note that it does not support --stacking or --new-stacking.

--local-progressive
    Align only the subalignment of locally aligned subsequences in subsequent steps of the progressive multiple alignment. Note: this is only effective if local alignment is turned on. (Default for sequence local alignment; turn off by --global-progressive)

--global-progressive
    Use alignments including "locality gaps" in subsequent steps of the progressive multiple alignment. Note: this is only effective if local alignment is turned on. (Opposite of --local-progressive)

--consistency-transformation
    Apply probabilistic consistency transformation (only possible in probabilistic mode).

--iterate
    Refine iteratively after progressive alignment. Currently, iterative refinement optimizes the SCI or RELIABILITY (not the locarna score)! Iterative refinement realigns all binary splits along the guide tree.

--iterations=number
    Refine iteratively for given number of iterations (or stop at convergence).

--extlib
    Use library extension for base pair probabilities (experimental/not functional).

--it-reliable-structure=number
    Iterate alignment <num> times with reliable structure. This works only in probabilistic mode, when reliabilities can be computed.

  Further options for probabilistic mode

--pf-only-basematch-probs
    Use only base match probabilities (no base pair match probabilities).

--pf-scale=<scale>
    Scale of partition function; use for avoiding overflow in larger instances.

--fast-mea
    Compute base match probabilities using Gotoh PF-algorithm.

--mea-alpha
    Weight of unpaired probabilities in fast mea mode.

--mea-beta
    Weight of base pair match contribution in probabilistic mode.

--mea-gamma
    Reserved parameter for fast-mea mode.

--mea-gapcost
    Turn on gap penalties in probabilistic/mea mode (default: off).

--no-write-bm-probs / --write-bm-probs
    Don't write / Write base match probabilities to files in target dir (default: write).

--no-write-am-probs / --write-am-probs
    Don't write / Write arc match probabilities to files in target dir (default: write).

  Miscallaneous modes of operation

--dp-cache=directory
    Use directory <dir> as cache for dp files (useful for avoiding multiple computation).

--only-dps
    Compute only the missing dp files, don't align (useful for filling the dp-cache).

--evaluate=file
    Evaluate the given multiple alignment (clustalw aln format, or use --eval-fasta). This requires that probailities are already computed (mlocarna --probabilistic) and present in the target directory (--tgtdir).

--eval-fasta
    Assume that alignment for evaluation (cf. --evaluate) is in fasta format.

  Constraints

--anchor-constraints=<file>
    Read anchor constraints from bed format specification.

    Anchor constraints in four-column bed format specify positions of named anchor regions per sequence. The 'contig' names have to correspond to the fasta input sequence names. Anchor names must be unique per sequence and regions of the same name for different sequences must have the same length. This constrains the alignment to align all regions of the same name.

    The specification of anchors via this option removes all anchor definitions that may be given directly in the fasta input file!

--ignore-constraints
    Ignore all constraints (anchor and structure constraints) even if given.

  Rna folding (RNAfold/RNAplfold)

--noLP / --LP
    Disallow/Allow lonely pairs (default: Disallow).

--maxBPspan
    Limit maximum span of base pairs (default off).

--plfold-span=span
    Use RNAplfold with span.

--plfold-winsize=ws
    Use RNAplfold with window of size ws (default=2*span).

--rnafold-parameter=<file>
    Parameter file for RNAfold (RNAfold's -P option)

--rnafold-temperature=<temp>
    Temperature for RNAfold (RNAfold's -T option)

--skip-pp
    Skip computation of pair probs if the probabilities are already existing. Non-existing ones are still computed.

--no-bpp-precomputation
    Switch off precomputation of base pair probabilties. Overwrite potentially existing input files. (compare skip-pp). For use with special pairwise aligners (e.g. locarna_n) that recompute the base pair probabilities at each invokation.

--in-loop-probabilities
    Turn on precomputation of in loop probabilties. For use with special pairwise aligners (e.g. locarna_n) that use such probabilities.

  Multithreading

--threads, --cpus=number
    Use the given number of threads for computing pair probabilities and all-2-all alignments in parallel (multicore/processor support).

  Getting Help

--help
    Brief help message

--man
    Full documentation

The sequences are given in input file <file> in mfasta format. All results are written to a target directory <dir>. If the file tree is given, contained tree (in NEWICK-tree format) is used as guide tree for the progressive alignment. The final results are collected in <tgtdir>/results. The final multiple alignment is <tgtdir>/results/result.aln.

EXAMPLES

  Calling mlocarna
Sequences are typically given in plain fasta format like

  example.fa:
  ----------------------------------------
  >fruA
  CCUCGAGGGGAACCCGAAAGGGACCCGAGAGG
  >fdhA
  CGCCACCCUGCGAACCCAAUAUAAAAUAAUACAAGGGAGCAGGUGGCG
  >vhuU
  AGCUCACAACCGAACCCAUUUGGGAGGUUGUGAGCU
  ----------------------------------------

To align these sequences, simply call

  mlocarna example.fa

Usually, it makes sense to set additional options; this is either done on the command line or via configuration files. A reasonable small configuration for global alignment of large instances would be

  short-example.cfg
  ----------------------------------------
  max-diff-am: 25
  max-diff:    60
  min-prob:    0.01
  plfold-span: 100
  indel:       -50
  indel-open:  -750
  threads:     8   # <- adapt to your hardware
  alifold-consensus-dp
  ----------------------------------------

To use it, call

  mlocarna --config short-example.cfg example.fa

which is equivalent to

  mlocarna --max-diff-am 25 --max-diff 60 --min-prob 0.01 \
           --indel -50 --indel-open -750 \
           --plfold-span 100 --threads 8 --alifold-consensus-dp \
           example.fa

For probabilistic alignment with consistency transformation, call

  mlocarna --probabilistic --consistency-transform example.fa

In both cases, mlocarna writes the main results to stdout and more detailed results to the target directory example.out. The results directory is overwritten if it exists already. To avoid this, one can specify the target directory (--tgtdir).

  Use of constraints
Mlocarna supports structure constraints for folding and anchor constraints for alignment. Both types of constraints can be specified in extension of the standard fasta format via 'constraint lines'. Fasta-ish input with constraints looks like this

  example-w-constraints.fa
  ----------------------------------------
  >A
  GACCCUGGGAACAUUAACUACUCUCGUUGGUGAUAAGGAACA
  ..((.(....xxxxxx...................))).xxx #S
  ..........000000.......................111 #1
  ..........123456.......................123 #2
  >B
  ACGGAGGGAAAGCAAGCCUUCUGCGACA
  .(((....xxxxxx.......))).xxx #S
  ........000000...........111 #1
  ........123456...........123 #2
  ----------------------------------------

The same anchor constraints (like by the lines tagged #1, #2) can alternatively be specified in bed format by the entries

  example-anchors.bed
  ----------------------------------------
  A     10      16      first_box
  B     8       14      first_box
  A     39      42      ACA-box
  B     25      28      ACA-box
  ----------------------------------------

where anchor regions (boxes) have arbitrary but matching names and contig/sequence names correspond to the sequence names of the fasta(-like) input.

Given, e.g.

  example-wo-anchors.fa
  ----------------------------------------
  >A
  GACCCUGGGAACAUUAACUACUCUCGUUGGUGAUAAGGAACA
  ..((.(....xxxxxx...................))).xxx #S
  >B
  ACGGAGGGAAAGCAAGCCUUCUGCGACA
  .(((....xxxxxx.......))).xxx #S
  ----------------------------------------

once calls

  mlocarna --anchor-constraints example-anchors.bed  example-wo-anchors.fa

The LocARNA distribution provides files of these examples and other examples in Data/Examples.

AUTHORS
Sebastian Will, Christina Otto, Milad Miladi

ONLINE INFORMATION
For download and online information, see <http://www.bioinf.uni-freiburg.de/Software/LocARNA>

REFERENCES
Sebastian Will, Kristin Reiche, Ivo L. Hofacker, Peter F. Stadler, and Rolf Backofen. Inferring non-coding RNA families and classes by means of genome-scale structure-based clustering. PLOS Computational Biology, 3 no. 4 pp. e65, 2007. doi: 10.1371/journal.pcbi.0030065

Sebastian Will, Tejal Joshi, Ivo L. Hofacker, Peter F. Stadler, and Rolf Backofen. LocARNA-P: Accurate boundary prediction and improved detection of structural RNAs. RNA, 18 no. 5 pp. 900-14, 2012. doi: 10.1261/rna.029041.111