diff clustalomega/clustal-omega-0.2.0/README @ 0:ff1768533a07

Migrated tool version 0.2 from old tool shed archive to new tool shed repository

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+
+
+CLUSTAL-OMEGA is a general purpose multiple sequence alignment program
+for proteins.
+
+
+
+INTRODUCTION
+
+Clustal-Omega is a general purpose multiple sequence alignment (MSA)
+program for proteins. It produces high quality MSAs and is capable of
+handling data-sets of hundreds of thousands of sequences in reasonable
+time.
+
+In default mode, users give a file of sequences to be aligned and
+these are clustered to produce a guide tree and this is used to guide
+a "progressive alignment" of the sequences.  There are also facilities
+for aligning existing alignments to each other, aligning a sequence to
+an alignment and for using a hidden Markov model (HMM) to help guide
+an alignment of new sequences that are homologous to the sequences
+used to make the HMM.  This latter procedure is referred to as
+"external profile alignment" or EPA.
+
+Clustal-Omega uses HMMs for the alignment engine, based on the HHalign
+package from Johannes Soeding [1].  Guide trees are optionally made
+using mBed [2] which can cluster very large numbers of sequences in
+O(N*log(N)) time.  Multiple alignment then proceeds by aligning larger
+and larger alignments using HHalign, following the clustering given by
+the guide tree.
+
+In its current form Clustal-Omega can only align protein sequences but
+not DNA/RNA sequences. It is envisioned that DNA/RNA will become
+available in a future version.
+
+
+
+SEQUENCE INPUT:
+
+-i, --in, --infile={<file>,-} 
+	Multiple sequence input file (- for stdin)
+
+--hmm-in=<file>           
+	HMM input files
+
+--dealign                 
+	Dealign input sequences
+
+--profile1, --p1=<file>   
+	Pre-aligned multiple sequence file (aligned columns will be kept fixed)
+
+--profile2, --p2=<file>   
+	Pre-aligned multiple sequence file (aligned columns will be kept fixed)
+
+
+For sequence and profile input Clustal-Omega uses the Squid library
+from Sean Eddy [3].
+
+
+Clustal-Omega accepts 3 types of sequence input: (i) a sequence file
+with un-aligned or aligned sequences, (ii) profiles (a multiple
+alignment in a file) of aligned sequences, (iii) a HMM. Valid
+combinations of the above are:
+
+(a) one file with un-aligned or aligned sequences (i); the sequences
+    will be aligned, and the alignment will be written out. For this
+    mode use the -i flag. If the sequences are aligned (all sequences
+    have the same length and at least one sequence has at least one
+    gap), then the alignment is turned into a HMM, the sequences are
+    de-aligned and the now un-aligned sequences are aligned using the
+    HMM as an External Profile for External Profile Alignment (EPA).
+    If no EPA is desired use the --dealign flag.
+
+    Use the above option to make a multiple alignment from a set of
+    sequences. A sequence file must contain more than one sequence (at
+    least two sequences).
+
+(b) two profiles (ii)+(ii); the columns in each profile will be kept
+    fixed and the alignment of the two profiles will be written
+    out. Use the --p1 and --p2 flags for this mode.
+
+    Use this option to align two alignments (profiles) together.
+
+(c) one file with un/aligned sequences (i) and one profile (ii); the
+    profile is converted into a HMM and the un-aligned sequences will
+    be multiply aligned (using the HMM background information) to form
+    a profile; this constructed profile is aligned with the input
+    profile; the columns in each profile (the original one and the one
+    created from the un-aligned sequences) will be kept fixed and the
+    alignment of the two profiles will be written out. Use the -i flag
+    in conjunction with the --p1 flag for this mode. 
+      The un/aligned sequences file (i) must contain at least two
+    sequences. If a single sequence has to be aligned with a profile
+    the profile-profile option (b) has to be used.
+
+    Use the above option to add new sequences to an existing
+    alignment.
+
+(d) one file with un-aligned sequences (i) and one HMM (iii); the
+    un-aligned sequences will be aligned to form a profile, using the
+    HMM as an External Profile. So far only one HMM can be input and
+    only HMMer2 and HMMer3 formats are allowed. The alignment will be
+    written out; the HMM information is discarded. As, at the moment,
+    only one HMM can be used, no HMM is produced if the sequences are
+    already aligned. Use the -i flag in conjunction with the --hmm-in
+    flag for this mode. Multiple HMMs can be inputted, however, in the
+    current version all but the first HMM will be ignored.
+
+    Use this option to make a new multiple alignment of sequences from
+    the input file and use the HMM as a guide (EPA).
+
+
+Invalid combinations of the above are: 
+
+(v) an un/aligned sequence file containing just one sequence (i)
+
+(w) an un/aligned sequence file containing just one sequence and a profile
+    (i)+(ii)
+
+(x) an un/aligned sequence file containing just one sequence and a HMM
+    (i)+(iii)
+
+(y) two or more HMMs (iii)+(iii)+... cannot be aligned to one another.
+
+(z) one profile (ii) cannot be aligned with a HMM (iii)
+
+
+The following MSA file formats are allowed: 
+
+    a2m=fasta, (vienna)
+    clustal,
+    msf,
+    phylip,
+    selex,
+    stockholm
+
+
+Prior to MSA, Clustal-Omega de-aligns all sequence input (i). However,
+alignment information is automatically converted into a HMM and used
+during MSA, unless the --dealign flag is specifically set.  Profiles
+(ii) are not de-aligned.
+
+The Clustal-Omega alignment engine can at the moment not process
+DNA/RNA. If a sequence input file (i) or a profile (ii) is interpreted
+as DNA/RNA the program will terminate during the file input stage.
+
+
+
+CLUSTERING:
+
+  --distmat-in=<file>       
+	Pairwise distance matrix input file (skips distance computation)
+
+  --distmat-out=<file>      
+	Pairwise distance matrix output file
+
+  --guidetree-in=<file>     
+	Guide tree input file 
+	(skips distance computation and guide tree clustering step)
+
+  --guidetree-out=<file>    
+	Guide tree output file
+
+  --mbed                    
+	Fast, Mbed-like clustering for guide tree calculation
+
+  --mbed-iter               
+	Use Mbed-like clustering also during iteration
+                            
+
+In order to produce a multiple alignment Clustal-Omega requires a
+guide tree which defines the order in which sequences/profiles are
+aligned. A guide tree in turn is constructed, based on a distance
+matrix. Conventionally, this distance matrix is comprised of all the
+pair-wise distances of the sequences. The distance measure
+Clustal-Omega uses for pair-wise distances of un-aligned sequences is
+the k-tuple measure [4], which was also implemented in clustal1.83 and
+clustalW2 [5,6].  If the sequences inputted via -i are aligned
+Clustal-Omega uses the Kimura-corrected pairwise aligned identities
+[7]. The computational effort (time/memory) to calculate and store a
+full distance matrix grows quadratically with the number of
+sequences. Clustal-Omega can improve this scalability to N*log(N) by
+employing a fast clustering algorithm called mBed [2]; this option is
+invoked by specifying the --mbed flag.
+
+Clustal-Omega uses Muscle's [8] fast UPGMA implementation to construct
+its guide trees from the distance matrix. By default, the distance
+matrix is used internally to construct the guide tree and is then
+discarded. By specifying --distmat-out the internal distance matrix
+can be written to file.  The guide trees by default are used
+internally to guide the multiple alignment and are then discarded. By
+specifying the --guidetree-out option these internal guide trees can
+be written out to file. Conversely, the distance calculation and/or
+guide tree building stage can be skipped, by reading in a
+pre-calculated distance matrix and/or pre-calculated guide tree. These
+options are invoked by specifying the --distmat-in and/or
+--guidetree-in flags, respectively. However, distance matrix reading
+is disabled in the current version. By default, distance matrix and
+guide tree files are not over-written, if a file with the specified
+name already exists. In this case Clustal-Omega aborts during the
+command-line processing stage. To force over-writing of already
+existing files use the --force flag (see MISCELLANEOUS).
+
+Guide trees can be iterated to refine the alignment (see section
+ITERATION). Clustal-Omega takes the alignment, that was produced
+initially and constructs a new distance matrix from this
+alignment. The distance measure used at this stage is the Kimura
+distance [7]. By default, Clustal-Omega constructs a full distance
+matrix at this stage, which will then be used to create an improved
+(iterated) new guide tree. To use mBed like clustering at this stage
+the --mbed-iter flag has to be set. While Kimura distances in general
+are much faster to calculate than k-tuple distances, time and memory
+requirements still scale quadratically with the number of sequences
+and mBed-type clustering should be considered for large cases.
+
+
+
+ALIGNMENT OUTPUT:
+
+  -o, --out, --outfile={file,-} Multiple sequence alignment output file (default: stdout)
+
+  --outfmt={a2m=fa[sta],clu[stal],msf,phy[lip],selex,st[ockholm],vie[nna]} MSA output file format (default: fasta)
+                            
+
+By default Clustal-Omega writes its results (alignments) to stdout. An
+output file can be specified with the -o flag. Output to stdout is not
+possible in verbose mode (-v, see MISCELLANEOUS) as verbose/debugging
+messages would interfere with the alignment output.  By default,
+alignment files are not over-written, if a file with the specified
+name already exists. In this case Clustal-Omega aborts during the
+command-line processing stage. To force over-writing of already
+existing files use the --force flag (see MISCELLANEOUS).
+
+Clustal-Omega can output alignments in various formats by setting the
+--outfmt flag:
+
+  * for Fasta format set: --outfmt=a2m  or  --outfmt=fa  or  --outfmt=fasta
+
+  * for Clustal format set: --outfmt=clu  or  --outfmt=clustal
+
+  * for Msf format: set --outfmt= msf
+
+  * for Phylip format set: --outfmt=phy  or  --outfmt=phylip
+
+  * for Selex format set: --outfmt=selex
+
+  * for Stockholm format set: --outfmt=st  or  --outfmt=stockholm
+
+  * for Vienna format set: --outfmt=vie  or  --outfmt=vienna
+
+
+ITERATION:
+
+  --iterations, --iter=<n>  Number of (combined guide tree/HMM) iterations
+
+  --max-guidetree-iterations=<n> Maximum guide tree iterations
+
+  --max-hmm-iterations=<n>  Maximum number of HMM iterations
+                            
+
+By default, Clustal-Omega calculates (or reads in) a guide tree and
+performs a multiple alignment in the order specified by this guide
+tree. This alignment is then outputted. Clustal-Omega can 'iterate'
+its guide tree. The hope is that the (Kimura) distances, that can be
+derived from the initial alignment, will give rise to a better guide
+tree, and by extension, to a better alignment.
+
+A similar rationale applies to HMM-iteration. MSAs in general are very
+'vulnerable' at their early stages. Sequences that are aligned at an
+early stage remain fixed for the rest of the MSA. Another way of
+putting this is: 'once a gap, always a gap'. This behaviour can be
+mitigated by HMM iteration. An initial alignment is created and turned
+into a HMM. This HMM can help in a new round of MSA to 'anticipate'
+where residues should align. This is using the HMM as an External
+Profile and carrying out iterative EPA.  In practice, individual
+sequences and profiles are aligned to the External HMM, derived after
+the initial alignment. Pseudo-count information is then transferred to
+the (internal) HMM, corresponding to the individual
+sequence/profile. The now somewhat 'softened' sequences/profiles are
+then in turn aligned in the order specified by the guide
+tree. Pseudo-count transfer is reduced with the size of the
+profile. Individual sequences attain the greatest pseudo-count
+transfer, larger profiles less so. Pseudo-count transfer to profiles
+larger than, say, 10 is negligible. The effect of HMM iteration is
+more pronounced in larger test sets (that is, with more sequences).
+
+Both, HMM- and guide tree-iteration come at a cost of increasing the
+run-time. One round of guide tree iteration adds on (roughly) the time
+it took to construct the initial alignment. If, for example, the
+initial alignment took 1min, then it will take (roughly) 2min to
+iterate the guide tree once, 3min to iterate the guide tree twice, and
+so on. HMM-iteration is more costly, as each round of iteration adds
+three times the time required for the alignment stage. For example, if
+the initial alignment took 1min, then each additional round of HMM
+iteration will add on 3min; so 4 iterations will take 13min
+(=1min+4*3min). The factor of 3 stems from the fact that at every
+stage both intermediate profiles have to be aligned with the
+background HMM, and finally the (softened) HMMs have to be aligned as
+well. All times are quoted for single processors.
+
+By default, guide tree iteration and HMM-iteration are coupled. This
+means, at each iteration step both, guide tree and HMM, are
+re-calculated. This is invoked by setting the --iter flag. For
+example, if --iter=1, then first an initial alignment is produced
+(without external HMM background information and using k-tuple
+distances to calculate the guide tree). This initial alignment is then
+used to re-calculate a new guide tree (using Kimura distances) and to
+create a HMM. The new guide tree and the HMM are then used to produce
+a new MSA.
+
+Iteration of guide tree and HMM can be de-coupled. This means that the
+number of guide tree iterations and HMM iterations can be
+different. This can be done by combining the --iter flag with the
+--max-guidetree-iterations and/or the --max-hmm-iterations flag.  The
+number of guide tree iterations is the minimum of --iter and
+--max-guidetree-iterations, while the number of HMM iterations is the
+minimum of --iter and --max-hmm-iterations.  If, for example, HMM
+iteration should be performed 5 times but guide tree iteration should
+be performed only 3 times, then one should set --iter=5 and
+--max-guidetree-iterations=3. All three flags can be specified at the
+same time (however, this makes no sense). It is not sufficient just to
+specify --max-guidetree-iterations and --max-hmm-iterations but not
+--iter. If any iteration is desired --iter has to be set.
+
+
+LIMITS (will exit early, if exceeded):
+
+  --maxnumseq=<n>           Maximum allowed number of sequences
+
+  --maxseqlen=<l>           Maximum allowed sequence length
+
+Limits can be imposed on the number of sequences in the input file
+and/or the lengths of the sequences. This cap can be set with the
+--maxnumseq and --maxseqlen flags, respectively. Clustal-Omega will
+exit early, if these limits are exceeded.
+                            
+
+MISCELLANEOUS:
+
+  --auto                    Set options automatically (might overwrite some of your options)
+
+  --threads=<n>             Number of processors to use
+
+  -h, --help                Print help and exit
+
+  -v, --verbose             Verbose output (increases if given multiple times)
+
+  --version                 Print version information and exit
+
+  --long-version            Print long version information and exit
+
+  --force                   Force file overwriting
+
+
+Users may feel unsure which options are appropriate in certain
+situations. The --auto flag tries to alleviate this problem and selects
+accuracy/speed flags according to the number of sequences. For less
+than 1,000 sequences mBed-clustering is unnecessary and the --mbed
+flag is turned off. In this case the iteration is also turned off as
+the effect of iteration is more noticeable for 'larger' problems. For
+1,000 to 10,000 sequences full distance matrix calculation may become
+to burdensome and the --mbed flag is turned on. Iterations are set to
+1 as experience has shown that accuracy can be boosted in this
+regime. However, for more than 10,000 sequences iterations are turned
+off again. Improvement in accuracy may be substantial, however, the
+computational overhead might be too costly for average users. In this
+regime the --mbed flag remains turned on as full distance matrix
+calculation may become prohibitive. Expert users may want to avoid
+this flag and exercise more fine tuned control by selecting the
+appropriate options manually.
+
+Certain parts of the MSA calculation have been parallelised. Most
+noticeably, the distance matrix calculation, and certain aspects of
+the HMM building stage. Clustal-Omega uses OpenMP. By default,
+Clustal-Omega will attempt to use as many threads as possible. For
+example, on a 4-core machine Clustal-Omega will attempt to use 4
+threads. The number of threads can be limited by setting the --threads
+flag. This may be desirable, for example, in the case of
+benchmarking/timing.
+
+Help is available by specifying the -h flag.
+
+By default Clustal-Omega does not print any information to stdout
+(other than the final alignment, if no output file is
+specified). Information concerning the progress of the alignment can
+be obtained by specifying one verbosity flag (-v). This may be
+desirable, to verify what Clustal-Omega is actually doing at the
+moment. If two verbosity flags (-v -v) are specified, command-line
+flags (explicitly and implicitly set) are printed in addition to the
+progress report.  Triple verbose level (-v -v -v) is the most verbose
+level. In addition to single- and double-verbose information much more
+information is displayed: input sequences and names, details of the
+tree construction and intermediate alignments. Tree construction
+information includes pairwise distances. The number of pairwise
+distances scales with the square of the number of sequences, and
+double verbose mode is probably only useful for a small number of
+sequences.
+
+The current version number of Clustal-Omega can be displayed by
+setting the --version flag.
+
+The current version number of Clustal-Omega as well as the code-name
+and the build date can be displayed by setting the --long-version
+flag.
+
+By default, Clustal-Omega does not over-write files. These can be (i)
+alignment output, (ii) distance matrix and (iii) guide
+tree. Overwriting can be forced by setting the --force flag.
+
+
+EXAMPLES:
+
+./clustalo -i globin.fa
+
+Clustal-Omega reads the sequence file globin.fa, aligns the sequences
+and prints the result to screen in fasta/a2m format.
+
+
+./clustalo -i globin.fa -o globin.sto --outfmt=st
+
+If the file globin.sto does not exist, then Clustal-Omega reads the
+sequence file globin.fa, aligns the sequences and prints the result to
+globin.sto in Stockholm format. If the file globin.sto does exist
+already, then Clustal-Omega terminates the alignment process before
+reading globin.fa.
+
+
+./clustalo -i globin.fa	-o globin.aln --outfmt=clu --force
+
+Clustal-Omega reads the sequence file globin.fa, aligns the sequences
+and prints the result to globin.aln in Clustal format, overwriting the
+file globin.aln, if it already exists.
+
+
+./clustalo -i globin.fa --distmat-out=globin.mat --guidetree-out=globin.dnd --force
+
+Clustal-Omega reads the sequence file globin.fa, aligns the sequences,
+prints the result to screen in fasta/a2m format (default), the guide
+tree to globin.dnd and the distance matrix to globin.mat, overwriting
+those files if they already exist.
+
+
+./clustalo -i globin.fa	--guidetree-in=globin.dnd
+
+Clustal-Omega reads the files globin.fa and globin.dnd, skipping
+distance calculation and guide tree creation, using instead the guide
+tree specified in globin.dnd.
+
+
+./clustalo -i globin.fa --hmm-in=PF00042.hmm
+
+Clustal-Omega reads the sequence file globin.fa and the HMM file
+PF00042.hmm (in HMMer2 or HMMer3 format).  It then performs the
+alignment, transferring pseudo-count information contained in
+PF00042.hmm to the sequences/profiles during the MSA.
+
+
+./clustalo -i globin.sto
+
+Clustal-Omega reads the file globin.sto (of aligned sequences in
+Stockholm format). It converts the alignment into a HMM, de-aligns the
+sequences and re-aligns them, transferring pseudo-count information to
+the sequences/profiles during the MSA. The guide tree is constructed
+using a full distance matrix of Kimura distances.
+
+
+./clustalo -i globin.sto  --dealign
+
+Clustal-Omega reads the file globin.sto (of aligned sequences in
+Stockholm format). It de-aligns the sequences and then re-aligns
+them. No HMM is produced in the process, no pseudo-count information
+is transferred. Consequently, the output must be the same as for
+unaligned output (like in the first example ./clustalo -i globin.fa)
+
+
+./clustalo -i globin.fa --iter=2 
+
+Clustal-Omega reads the file globin.fa, creates a UPGMA guide tree
+built from k-tuple distances, and performs an initial alignment. This
+initial alignment is converted into a HMM and a new guide tree is
+built from the Kimura distances of the initial alignment. The
+un-aligned sequences are then aligned (for the second time but this
+time) using pseudo-count information from the HMM created after the
+initial alignment (and using the new guide tree). This second
+alignment is then again converted into a HMM and a new guide tree is
+constructed. The un-aligned sequences are then aligned (for a third
+time), again using pseudo-count information of the HMM from the
+previous step and the most recent guide tree. The final alignment is
+written to screen.
+
+
+./clustalo -i globin.fa --iter=5 --max-guidetree-iterations=1
+
+Clustal-Omega reads the file globin.fa, creates a UPGMA guide tree
+built from k-tuple distances, and performs an initial alignment. This
+initial alignment is converted into a HMM and a new guide tree is
+built from the Kimura distances of the initial alignment. The
+un-aligned sequences are then aligned (for the second time but this
+time) using pseudo-count information from the HMM created after the
+initial alignment (and using the new guide tree). For the last 4
+iterations the guide tree is left unchanged and only HMM iteration is
+performed. This means that intermediate alignments are converted to
+HMMs, and these intermediate HMMs are used to guide the MSA during
+subsequent iteration stages.
+
+
+./clustalo -i globin.fa -o globin.a2m -v
+
+In case the file globin.a2m does not exist, Clustal-Omega reads the
+file globin.fa, prints a progress report to screen and writes the
+alignment in (default) Fasta format to globin.a2m. The progress report
+consists of the number of threads used, the number of sequences read,
+the current progress in the k-tuple distance calculation, completion
+of the guide tree computation and current progress of the MSA stage.
+If the file globin.a2m already exists Clustal-Omega aborts before
+reading the file globin.fa. Note that in verbose mode an output file
+has to be specified, because progress/debugging information, which is
+printed to screen, would interfere with the alignment being printed to
+screen.
+
+
+./clustalo -i PF00042_full.fa --dealign --mbed --outfmt=vie -o PF00042_full.vie --force 
+
+Clustal-Omega reads the file PF00042_full.fa. This file contains
+several thousand aligned sequences. --dealign tells Clustal-Omega to
+erase all alignment information and re-align the sequences from
+scratch. As there are several thousand sequences calculating a full
+distance matrix may be slow. It may therefore be desirable to use the
+--mbed option. Clustal-Omega now will calculate pairwise distances to
+a small number of reference sequences only. This will give a
+significant speed-up. The speed-up is greater for larger families
+(more sequences). The alignment is then written out in Vienna format
+(fasta format all on one line, no line breaks per sequence) to file
+PF00042_full.vie.
+
+
+./clustalo --p1=globin.sto --p2=PF00042_full.vie -o globin+pf00042.fa
+
+Clustal-Omega reads files globin.sto and PF00042_full.vie of aligned
+sequences (profiles). Both profiles are then aligned. The relative
+positions of residues in both profiles are not changed during this
+alignment, however, columns of gaps may be inserted into the profiles,
+respectively. The final alignment is written to file globin+pf00042.fa
+in fasta format.
+
+
+./clustalo -i globin.fa --p1=PF00042_full.vie -o pf00042+globin.fa
+
+Clustal-Omega reads file globin.fa of un-aligned sequences and the
+profile (of aligned sequences) in file PF00042_full.vie. A HMM is
+created from the profile. This HMM is used to guide the alignment of
+the un-aligned sequences in globin.fa. The profile that was generated
+during this alignment of un-aligned globin.fa sequences is then
+aligned to the input profile PF00042_full.vie. The relative positions
+of residues in profile PF00042_full.vie is not changed during this
+alignment, however, columns of gaps may be inserted into the
+profile. The final alignment is output to file pf00042+globin.fa in
+fasta format. The alignment in this example may be slightly different
+from the alignment in the previous example, because no HMM guidance
+was used generate the profile globin.sto. In this example HMM guidance
+was used to align the sequences in globin.fa; the hope being that this
+intermediate alignment will have profited from the bigger profile.
+
+
+
+LITERATURE:
+
+[1] Johannes Soding (2005) Protein homology detection by HMM-HMM
+    comparison. Bioinformatics 21 (7): 951–960.
+
+[2] Blackshields G, Sievers F, Shi W, Wilm A, Higgins DG.  Sequence
+    embedding for fast construction of guide trees for multiple
+    sequence alignment.  Algorithms Mol Biol. 2010 May 14;5:21.
+
+[3] http://www.genetics.wustl.edu/eddy/software/#squid
+
+[4] Wilbur and Lipman, 1983; PMID 6572363
+
+[5] Thompson JD, Higgins DG, Gibson TJ.  (1994). CLUSTAL W: improving
+    the sensitivity of progressive multiple sequence alignment through
+    sequence weighting, position-specific gap penalties and weight
+    matrix choice. Nucleic Acids Res., 22, 4673-4680.
+
+[6] Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA,
+    McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R, Thompson JD,
+    Gibson TJ, Higgins DG.  (2007). Clustal W and Clustal X version
+    2.0. Bioinformatics, 23, 2947-2948.
+
+[7] Kimura M (1980). "A simple method for estimating evolutionary
+    rates of base substitutions through comparative studies of
+    nucleotide sequences". Journal of Molecular Evolution 16: 111–120.
+
+[8] Edgar, R.C. (2004) MUSCLE: multiple sequence alignment with high
+    accuracy and high throughput.Nucleic Acids Res. 32(5):1792-1797.
+