-
-
-
MUSCLE User Guide
-
MUSCLE +User Guide
--
-
-
-
-
-
Multiple sequence comparison
-by log-expectation
-
by Robert C. Edgar
Multiple +sequence comparison by log-expectation
-by Robert C. +Edgar
-Version 3.6
-
September 2005
Version 3.8
-May 2010
-- +
-
email: muscle (at) drive5.com
-
MUSCLE is updated regularly.
-Send me an e-mail if you would like to be notified of new releases.
-
-
Citation:
Citation:
--
Edgar,
+
-
- For a complete
-description of the algorithm, see also: Edgar, Robert C (2004), MUSCLE: a multiple sequence alignment method
-with reduced time and space complexity. BMC Bioinformatics, 5(1):113. 2.8
-Refining an existing alignment4 2.9
-Using a pre-computed guide tree4 2.10
-Profile-profile alignment5 2.11
-Adding sequences to an existing alignment5 2.13
-Specifying a substitution matrix6 2.14
-Refining a long alignment6 3.1.3
-Determining sequence type7 4.7
-The profile scoring function10
-Table of Contents
+high throughput, Nucleic Acids Research 32(5), 1792-97.
+ +
For a +complete description of the algorithm, see also:
+ ++ +
Edgar, Robert C (2004), MUSCLE:
+a multiple sequence alignment method with reduced time and space complexity. BMC
+Bioinformatics, 5(1):113.
+Table
+of Contents
2.7 Refining +an existing alignment
+ +2.8 Using a +pre-computed guide tree
+ +2.9 +Profile-profile alignment
+ +2.10 Adding +sequences to an existing alignment
+ +2.11 +Specifying a protein substitution matrix
+ +2.12 +Specifying a nucleotide substitution matrix
+ +2.13 +Refining a long alignment
+ + + + + + + + + +3.1.3 +Determining sequence type
+ + + + + +3.2.2 Output +to multiple file formats
+ + + + + + + + + + + + + + + + + + + + + +4.6 The +profile scoring function
+ + + + + + + + + + + + + + + + + ++ +
MUSCLE is a program for creating multiple alignments of +
MUSCLE is a program for creating multiple alignments of amino acid or nucleotide sequences. A range of options is provided that give you the choice of optimizing accuracy, speed, or some compromise between the -two. Default parameters are those that give the best average accuracy in our -tests. Using versions current at the time of writing, my tests show that MUSCLE -can achieve both better average accuracy and better speed than CLUSTALW or T‑Coffee, -depending on the chosen options. Many command line options are provided to vary -the internals of the algorithm; some of these will primarily be of interest to -algorithm developers who wish to better understand which features of the algorithm -are important in different circumstances.
- -The MUSCLE algorithm is delivered as a command-line program -called muscle. If you are running under Linux or Unix -you will be working at a shell prompt. If you are running under Windows, you should -be in a command window (nostalgically known to us older people as a DOS prompt). -If you don't know how to use command-line programs, you should get help from a -local guru.
- -Copy the muscle binary file to a directory that is +two. Default parameters are those that gave the best average benchmark accuracy +in my tests. However, benchmark accuracy is a rather dubious measure; see:
+ ++ + + +
+ +
WARNING
+ +THE -stable OPTION +HAD A SERIOUS BUG IN VERSIONS OF MUSCLE PRIOR TO v3.8 AND IS CURRENTLY NOT +SUPPORTED. Go to this link for latest news and work-arounds:
+ ++ +
http://drive5.com/muscle/stable.html
+ ++ +
The MUSCLE algorithm is delivered as a command-line program +called muscle. If you are running under Linux or Unix you will be +working at a shell prompt. If you are running under Windows, you should be in a +command window (nostalgically known to us older people as a DOS prompt). If you +don't know how to use command-line programs, you should get help from a local +guru.
+ +Copy the muscle binary file to a directory that is
accessible from your computer. That's itthere are no configuration files,
libraries, environment variables or other settings to worry about. If you are
-using Windows, then the binary file is named muscle.exe. From now on muscle
-should be understood to mean "muscle if you are using Linux or Unix, muscle.exe if you are using Windows".
Make a FASTA file containing some sequences. (If you are not +
Make a FASTA file containing some sequences. (If you are not familiar with FASTA format, it is described in detail later in this Guide.) For now, just to make things fast, limit the number of sequence in the file to no more than 50 and the sequence length to be no more than 500. Call the input -file seqs.fa. (An example file named seqs.fa is distributed with the standard MUSCLE -package). Make sure the directory containing the muscle binary is in -your path. (If it isn't, you can run it by typing the full path name, and the -following example command lines must be changed accordingly). Now type:
- -muscle -in seqs.fa -out seqs.afa
- -You should see some progress messages. If muscle completes
-successfully, it will create a file seqs.afa
-containing the alignment. By default, output is created in "aligned
-FASTA" format (hence the .afa extension).
-This is just like regular FASTA except that gaps are added in order to align
-the sequences. This is a nice format for computers but not very readable for
-people, so to look at the alignment you will want an alignment viewer such as Belvu, or a script that converts FASTA to a more readable format.
-You can also use the clw command-line option
-to request output in CLUSTALW format, which is easier to understand for people.
-If muscle gives an error message and you don't know how to fix it,
-please read the Troubleshooting section.
The default settings are designed to give the best accuracy, +file seqs.fa. Make sure the directory containing the muscle +binary is in your path. (If it isn't, you can run it by typing the full path +name, and the following example command lines must be changed accordingly). Now +type:
+ ++ +
muscle -in seqs.fa -out seqs.afa
+ ++ +
You should see some progress messages. If muscle +completes successfully, it will create a file seqs.afa containing the +alignment. By default, output is created in "aligned FASTA" format (hence +the .afa extension). This is just like regular FASTA except that gaps +are added in order to align the sequences. This is a nice format for computers +but not very readable for people, so to look at the alignment you will want an +alignment viewer such as Belvu, or a script that converts FASTA to a more readable +format. You can also use the clw command-line option to request output +in CLUSTALW format, which is easier to understand for people. If muscle +gives an error message and you don't know how to fix it, please read the +Troubleshooting section.
+ ++ +
The default settings are designed to give the best accuracy, so this may be all you need to know.
-If you have a large number of sequences (a few thousand), or +
If you have a large number of sequences (a few thousand), or they are very long, then the default settings of may be too slow for practical use. A good compromise between speed and accuracy is to run just the first two -iterations of the algorithm. On average, this gives accuracy comparable to -T-Coffee and speeds much faster than CLUSTALW. This is done by the option maxiters -2, as in the following example.
+iterations of the algorithm. This is done by the option maxiters 2, as +in the following example. --
muscle -in seqs.fa -out seqs.afa -maxiters 2
+muscle -in seqs.fa -out seqs.afa -maxiters 2
-The diags option enables -an optimization for speed by finding common words (6-mers in a compressed amino -acid alphabet) between the two sequences as seeds for diagonals. This is -related to optimizations in programs such as BLAST and FASTA: you get faster speed, -but sometimes lower average accuracy. For large numbers of closely related -sequences, this option works very well.
+The diags option enables an optimization for speed +by finding common words (6-mers in a compressed amino acid alphabet) between +the two sequences as seeds for diagonals. This is related to optimizations in +programs such as BLAST and FASTA: you get faster speed, but sometimes lower +average accuracy. For large numbers of closely related sequences, this option +works very well.
--
If you want the fastest possible speed, then the following +
If you want the fastest possible speed, then the following example shows the applicable options for proteins.
--
muscle -in seqs.fa -out seqs.afa -maxiters 1 -diags -sv +
muscle -in seqs.fa -out seqs.afa -maxiters 1 -diags -sv -distance1 kbit20_3
--
For nucleotides, use:
+For nucleotides, use:
--
muscle -in seqs.fa -out seqs.afa -maxiters 1 -diags
+muscle -in seqs.fa -out seqs.afa -maxiters 1 -diags
--
At the time of writing, muscle with these options is faster -than any other multiple sequence alignment program -that I have tested. The alignments are not bad, especially when the sequences +
The alignments are not bad, especially when the sequences are closely related. However, as you might expect, this blazing speed comes at the cost of the lowest average accuracy of the options that muscle provides.
-If you have a very large number of sequences (several -thousand), or they are very long, then the kbit20_3 option may cause -problems because it needs a relatively large amount of memory. Better is to use -the default distance measure, which is roughly 2× or 3× slower but needs less -memory, like this:
+If you have thousands of sequences, then attempting to +create a multiple alignment is dubious for many technical reasons. It may be +better to cluster first, then align the reduced set of sequences. Clustering +can be done using UCLUST, which is an algorithm implemented in the USEARCH +program:
--
muscle -in seqs.fa -out seqs.afa -maxiters 1 -diags1 -sv
+ --
Why do I keep using the clumsy phrase "average
-accuracy" instead of just saying "accuracy"? That's because the
-quality of alignments produced by MUSCLE varies, as do those produced other programs
-such as CLUSTALW and T-Coffee. The state of the art leaves plenty of room for
-improvement. Sometimes the fastest speed options to muscle give
-alignments that are better than T-Coffee, though the reverse will more often be
-the case. With challenging sets of sequences, it is a good idea to make several
-different alignments using different muscle options and to try other programs
-too. Regions where different alignments agree are more believable than regions
-where they disagree.
At the time of writing (May 2010), I'm working on methods +for leveraging a combination of UCLUST and MUSCLE to create very large but +still reasonably accurate alignments. If you're interested, email me and let's discuss.
-Input can be taken from standard input, and output can be +
Input can be taken from standard input, and output can be written to standard output. This is the default, so our first example would also work like this:
--
muscle < seqs.fa > seqs.afa
+muscle < seqs.fa > seqs.afa
-You can ask muscle to try to improve an existing +
You can ask muscle to try to improve an existing alignment by using the refine option. The input file must then be a FASTA file containing an alignment. All sequences must be of equal length, gaps -can be specified using dots "." or dashes "". For example:
+can be specified using dots "." or dashes "". For example: --
muscle -in seqs.afa -out refined.afa -refine
+muscle -in seqs.afa -out refined.afa -refine
-The usetree option allows -you to provide your own guide tree. For example,
+The usetree option allows you to provide your own +guide tree. For example,
--
muscle -in seqs.fa -out seqs.afa -usetree mytree.phy
+muscle -in seqs.fa -out seqs.afa -usetree mytree.phy
--
The tree must by in Newick format, -as used by the Phylip package (hence the .phy extension). The Newick -format is described here:
+The tree must by in Newick format, as used by the Phylip +package (hence the .phy extension). The Newick format is described here:
--
http://evolution.genetics.washington.edu/phylip/newicktree.html
+http://evolution.genetics.washington.edu/phylip/newicktree.html
--
WARNING. Do not use this -option just because you believe that you have an accurate evolutionary tree for -your sequences. The best guide tree for multiple alignment -is not in general the correct evolutionary tree. This can be understood -by the following argument. Alignment accuracy decreases with lower sequence -identity. It follows that given a set of profiles, the -two that can be aligned most accurately will tend to be the pair with the -highest identity, i.e. at the shortest evolutionary distance. This is exactly -the pair selected by the nearest-neighbor criterion which MUSCLE uses by -default. When mutation rates are variable, the evolutionary neighbor may -not be the nearest neighbor. This explains why a nearest-neighbor tree -may be superior to the true evolutionary tree for guiding a progressive alignment.
+WARNING. Do not use this option just because you +believe that you have an accurate evolutionary tree for your sequences. The +best guide tree for multiple alignment is not in general the correct +evolutionary tree. This can be understood by the following argument. Alignment +accuracy decreases with lower sequence identity. It follows that given a set of +profiles, the two that can be aligned most accurately will tend to be the pair +with the highest identity, i.e. at the shortest evolutionary distance. This is +exactly the pair selected by the nearest-neighbor criterion which MUSCLE uses +by default. When mutation rates are variable, the evolutionary neighbor +may not be the nearest neighbor. This explains why a nearest-neighbor +tree may be superior to the true evolutionary tree for guiding a progressive +alignment.
--
You will get a warning if you use the usetree -option. To disable the warning, use usetree_nowarn -instead,
+You will get a warning if you use the usetree +option. To disable the warning, use usetree_nowarn instead,
-e.g.:
+e.g.:
--
muscle -in seqs.fa -out seqs.afa -usetree_nowarn mytree.phy
+muscle -in seqs.fa -out seqs.afa -usetree_nowarn mytree.phy
-A fundamental step in the MUSCLE algorithm is aligning two +
A fundamental step in the MUSCLE algorithm is aligning two multiple sequence alignments. This operation is sometimes called -"profile-profile alignment". If you have two existing alignments of +"profile-profile alignment". If you have two existing alignments of related sequences you can use the profile option of MUSCLE to align those two sequences. Typical usage is:
--
muscle -profile -in1 one.afa -in2 two.afa -out both.afa
+muscle -profile -in1 one.afa -in2 two.afa -out both.afa
--
The alignments in one.afa -and two.afa, which must be in aligned FASTA -format, are aligned to each other, keeping input columns intact and inserting -columns of gaps where needed. Output is stored in both.afa.
+The alignments in one.afa and two.afa, which +must be in aligned FASTA format, are aligned to each other, keeping input +columns intact and inserting columns of gaps where needed. Output is stored in both.afa.
--
MUSCLE does not compute a similarity measure or measure of +
MUSCLE does not compute a similarity measure or measure of statistical significance (such as an E-value), so this option is not useful for -discriminating homologs from unrelated sequences. For this task, I recommend Sadreyev & Grishin's COMPASS -program.
+discriminating homologs from unrelated sequences. For this task, I recommend +Sadreyev & Grishin's COMPASS program. -To add a sequence to an existing alignment that you wish to +
To add a sequence to an existing alignment that you wish to keep intact, use profile-profile alignment with the new sequence as a profile. -For example, if you have an existing alignment existing_aln.afa -and want to add a new sequence in new_seq.fa, -use the following commands:
+For example, if you have an existing alignment existing_aln.afa and want +to add a new sequence in new_seq.fa, use the following commands: --
muscle -profile -in1 existing_aln.afa -in2 new_seq.fa -out
-combined.afa
muscle -profile -in1 existing_aln.afa -in2 new_seq.fa -out +combined.afa
--
If you have more than one new sequences, -you can align them first then add them, for example:
+If you have more than one new sequences, you can align them +first then add them, for example:
--
muscle -in new_seqs.fa -out new_seqs.afa
+muscle -in new_seqs.fa -out new_seqs.afa
-muscle -profile -in1 existing_aln.afa -in2 new_seqs.fa -out +
muscle -profile -in1 existing_aln.afa -in2 new_seqs.afa -out combined.afas
-The first stage in MUSCLE is a fast clustering algorithm. -This may be of use in other applications. Typical usage is:
+You can specify your own substitution matrix by using the -matrix +option. This reads a protein substitution matrix in NCBI or WU-BLAST format. +The alphabet is assumed to be amino acid, and sum-of-pairs scoring is used. The +-gapopen, -gapextend and -center parameters should be +specified; normally you will specify a zero value for the center. Note that gap +penalties MUST be negative. The environment variable MUSCLE_MXPATH can be used +to specify a path where the matrices are stored. For example,
-muscle -cluster -in seqs.fa -tree1 tree.phy -maxiters 1
+-
muscle -in seqs.fa -out seqs.afa -matrix /data/matrix/blosum62
-The sequences will be clustered, and a tree written to tree.phy. Options weight1, distance1, -cluster1 and root1 can be applied if desired. Note that by -default, UPGMA clustering is used. You can use
+-gapopen -12.0 -gapextend -1.0 -center 0.0
-neighborjoining if you prefer, but note that this is -substantially slower than UPGMA for large numbers of sequences, and is also -slightly less accurate. See discussion of usetree -above.
+-
Example matrices can be downloaded from the NCBI FTP site. +At the time of writing they are found here:
-You can specify your own substitution matrix by using the -matrix -option. This reads a protein substitution matrix in NCBI or WU-BLAST format. -The alphabet is assumed to be amino acid, and sum-of-pairs scoring is used. The --gapopen, -gapextend -and -center parameters should be specified; normally you will specify a -zero value for the center. Note that gap penalties MUST be negative. The -environment variable MUSCLE_MXPATH can be used to specify a path where the -matrices are stored. For example,
+-
ftp://ftp.ncbi.nih.gov/blast/matrices/
-muscle -in seqs.fa -out seqs.afa -matrix blosum62 -gapopen -12.0
+-gapextend -1.0 -center 0.0
+MUSCLE isn't really designed to support a nucleotide matrix, +but you can hack it by pretending that AGCT are amino acids and making a 20x20 +matrix out of the original 4x4 matrix. You MUST specify the -seqtype protein +option to fool MUSCLE into believing that it is aligning amino acid sequences. For +more information, see:
--
You can hack a nucleotide matrix by pretending that AGCT are
-amino acids and making a 20x20 matrix out of the original 4x4 matrix. Let me
-know if this isn't clear, I can help you through it.
http://drive5.com/muscle/nucmx.html
-A long alignment can be refined using the refinew option, which is primarily designed for -refining whole-genome nucleotide alignments. Usage is:
+A long alignment can be refined using the refinew +option, which is primarily designed for refining whole-genome nucleotide +alignments. Usage is:
--
muscle -in input.afa -out output.afa
+muscle -refinew -in input.afa -out output.afa
--
MUSCLE divides the input alignment into non-overlapping +
MUSCLE divides the input alignment into non-overlapping
windows and re-aligns each window from scratch, i.e. all gap characters are
-discarded. The refinewindow option may be
-used to change the window length, which is 200 columns
-by default.
MUSCLE uses FASTA format for both input and output. For
-output only, it also offers CLUSTALW, MSF, HTML, Phylip
-sequential and Phylip interleaved formats. See the
-following command-line options: ‑clw, ‑clwstrict, msf,
-html, phys, phyi, ‑clwout, ‑clwstrictout,
-msfout, htmlout,
-physout and phyiout.
MUSCLE uses FASTA format for both input and output. For +output only, it also offers CLUSTALW, MSF, HTML, Phylip sequential and Phylip +interleaved formats. See the following command-line options: ‑clw, +‑clwstrict, msf, html, phys, phyi, +‑clwout, ‑clwstrictout, msfout, htmlout, +physout and phyiout.
+ ++ +
Input files must be in FASTA format. These are plain text -files (word processing files such as Word documents are not understood!). Unix, Windows and DOS text files are supported (end-of-line -may be NL or CR NL). There is no explicit limit on the length of a sequence, -however if you are running a 32-bit version of muscle then the maximum -will be very roughly 10,000 letters due to maximum addressable size of tables -required in memory. Each sequence starts with an annotation line, which is -recognized by having a greater-than symbol ">" as its first -character. There is no limit on the length of an annotation line (this is new -as of version 3.5), and there is no requirement that the annotation be unique. The -sequence itself follows on one or more subsequent lines, and is terminated -either by the next annotation line or by the end of the file.
- -The standard single-letter amino acid alphabet is used. Upper +
Input files must be in FASTA format. These are plain text +files (word processing files such as Word documents are not understood!). Unix, +Windows and DOS text files are supported (end-of-line may be NL or CR NL). There +is no explicit limit on the length of a sequence, however if you are running a +32-bit version of muscle then the maximum will be very roughly 10,000 letters +due to maximum addressable size of tables required in memory. Each sequence +starts with an annotation line, which is recognized by having a greater-than +symbol ">" as its first character. There is no limit on the length +of an annotation line (this is new as of version 3.5), and there is no +requirement that the annotation be unique. The sequence itself follows on one +or more subsequent lines, and is terminated either by the next annotation line +or by the end of the file.
+ +The standard single-letter amino acid alphabet is used. Upper and lower case is allowed, the case is not significant. The special characters -X, B, Z and U are understood. X means "unknown amino acid", B is D or -N, Z is E or Q. U is understood to be the 21st amino acid Selenocysteine. -White space (spaces, tabs and the end-of-line characters CR and NL) is allowed -inside sequence data. Dots "." and dashes "" in sequences -are allowed and are discarded unless the input is expected to be aligned (e.g. -for the refine option).
- -The usual letters A, G, C, T and U stand for nucleotides. +X, B, Z and U are understood. X means "unknown amino acid", B is D or +N, Z is E or Q. U is understood to be the 21st amino acid Selenocysteine. White +space (spaces, tabs and the end-of-line characters CR and NL) is allowed inside +sequence data. Dots "." and dashes "" in sequences are +allowed and are discarded unless the input is expected to be aligned (e.g. for +the refine option).
+ +The usual letters A, G, C, T and U stand for nucleotides. The letters T and U are equivalent as far as MUSCLE is concerned. N is the -wildcard meaning "unknown nucleotide". R means A or G, Y means C or +wildcard meaning "unknown nucleotide". R means A or G, Y means C or T/U. Other wildcards, such as those used by RFAM, are not understood in this version and will be replaced by Ns. If you would like support for other DNA / RNA alphabets, please let me know.
-By default, MUSCLE looks at the first 100 letters in the +
By default, MUSCLE looks at the first 100 letters in the input sequence data (excluding gaps). If 95% or more of those letters are valid nucleotides (AGCTUN), then the file is treated as nucleotides, otherwise as amino acids. This method almost always guesses correctly, but you can make sure -by specifying the sequence type on the command line. This is done using the seqtype option, which can take the following values:
+by specifying the sequence type on the command line. This is done using the seqtype +option, which can take the following values: + +-
seqtype protein + Amino +acid
-seqtype protein Amino acid
+seqtype dna + + + DNA +(ACGT alphabet)
-seqtype nucleo Nucleotide
+seqtype rna + + + DNA +(ACGT alphabet)
- seqtype auto Automatic
-detection (default).
seqtype auto + Automatic +detection (default).
-By default, output is also written in FASTA format. All -letters are upper-case and gaps are represented by dashes "". Output +
By default, output is also written in FASTA format. All +letters are upper-case and gaps are represented by dashes "". Output is written to the following destination(s):
--
If no other -output option is given, then standard output.
+If no other output option is given, then standard +output.
-If -out <filename> -is given, to the specified file.
+If -out <filename> is given, to +the specified file.
- For all of the -xxxout options
-(e.g. -fastaout, -clwout),
-to the specified files.
For all of the -xxxout options (e.g. -fastaout, +-clwout), to the specified files.
-By default, MUSCLE re-arranges sequences so that similar +
By default, MUSCLE re-arranges sequences so that similar sequences are adjacent in the output file. (This is done by ordering sequences according to a prefix traversal of the guide tree). This makes the alignment easier to evaluate by eye. If you want to the sequences to be output in the same order as the input file, you can use the stable option.
-+ +
WARNING
+ +THE -stable OPTION +HAD A SERIOUS BUG IN VERSIONS OF MUSCLE PRIOR TO v3.8 AND IS CURRENTLY NOT +SUPPORTED.
+ +You can request output to more than one file format by using -the -xxxout options. For example, to get both -FASTA and CLUSTALW formats:
+You can request output to more than one file format by using +the -xxxout options. For example, to get both FASTA and CLUSTALW +formats:
--
muscle -in seqs.fa -fastaout seqs.afa -clwout seqs.aln
muscle -in seqs.fa -fastaout seqs.afa -clwout seqs.aln
-You can request CLUSTALW output by using the clw option. This should be compatible with CLUSTALW, -with the exception of the program name in the file header. You can ask MUSCLE -to impersonate CLUSTALW by writing "CLUSTAL W (1.81)" as the program -name by using clwstrict or ‑clwstrictout. Note that MUSCLE allows duplicate -sequence labels, while CLUSTALW forbids duplicates. If you use the stable -option of muscle, then the order of the input sequences is preserved and +
You can request CLUSTALW output by using the clw
+option. This should be compatible with CLUSTALW, with the exception of the
+program name in the file header. You can ask MUSCLE to impersonate CLUSTALW by
+writing "CLUSTAL W (1.81)" as the program name by using clwstrict
+or ‑clwstrictout. Note that MUSCLE allows duplicate sequence
+labels, while CLUSTALW forbids duplicates. If you use the stable option
+of muscle, then the order of the input sequences is preserved and
sequences can be unambiguously identified even if the labels differ. If you
have problems parsing MUSCLE output with scripts designed for CLUSTALW, please
-let me know and I'll do my best to provide a fix.
MSF format, as used in the GCG package, is requested by -using the msf option. As with CLUSTALW -format, this is easier for people to read than FASTA. As of MUSCLE 3.52, the -MSF format has been tweaked to be more compatible with GCG. The following -differences remain.
+MSF format, as used in the GCG package, is requested by +using the msf option. As with CLUSTALW format, this is easier for +people to read than FASTA. As of MUSCLE 3.52, the MSF format has been tweaked +to be more compatible with GCG. The following differences remain.
--
(a) MUSCLE truncates at the first white space or after 63 +
(a) MUSCLE truncates at the first white space or after 63 characters, which ever comes first. The GCG package apparently truncates after 10 characters. If this is a problem for you, please let me know and I'll add an option to truncate after 10 in a future version.
--
(b) MUSCLE allows duplicate sequence labels, while GCG +
(b) MUSCLE allows duplicate sequence labels, while GCG forbids duplicates. If you use the stable option of muscle, then the order of the input sequences is preserved and sequences can be unambiguously identified even if the labels differ.
--
Thanks to Eric Martel for help with improving GCG
-compatibility.
Thanks to Eric Martel for help with improving GCG +compatibility.
-I've added an experimental feature starting in version 3.4. To +
I added an experimental feature starting in version 3.4. To get a Web page as output, use the html option. The alignment is colored -using a color scheme from Eric Sonnhammer's Belvu editor, which is my personal favorite. A drawback of -this option is that the Web page typically contains a very large number of HTML -tags, which can be slow to display in the Internet Explorer browser. The -Netscape browser works much better. If you have any ideas about good ways to -make Web pages, please let me know.
- -The Phylip package supports two
-different multiple sequence alignment file formats, called sequential and
-interleaved respectively.
In this section we give more details of the MUSCLE algorithm
-and the more important options offered by the muscle implementation.
I won't give a complete description of the MUSCLE algorithm +using a color scheme from Eric Sonnhammer's Belvu editor, which is my personal +favorite. A drawback of this option is that the Web page typically contains a +very large number of HTML tags, which can be slow to display in the Internet +Explorer browser. The Netscape browser works much better. If you have any ideas +about good ways to make Web pages, please let me know.
+ +The Phylip package supports two different multiple sequence +alignment file formats, called sequential and interleaved respectively.
+ +In this section we give more details of the MUSCLE algorithm +and the more important options offered by the muscle implementation.
+ +I won't give a complete description of the MUSCLE algorithm herefor that, you will have to read the papers. (See citations on title page above). But hopefully a summary will help explain what some of the command-line options do and how they might be useful in your work.
--
The first step is to calculate a tree. In CLUSTALW, this is +
The first step is to calculate a tree. In CLUSTALW, this is
done as follows. Each pair of input sequences is aligned, and used to compute
the pair-wise identity of the pair. Identities are converted to a measure of
distance. Finally, the distance matrix is converted to a tree using a
clustering method (CLUSTALW uses neighbor-joining). If you have 1,000
-sequences, there are (1,000 ´ 999)/2 = 499,500 pairs, so aligning every pair can take
-a while. MUSCLE uses a much faster, but somewhat more approximate, method to
-compute distances: it counts the number of short sub-sequences (known as k-mers, k-tuples or words)
-that two sequences have in common, without constructing an alignment. This is
-typically around 3,000 times faster that CLUSTALW's
-method, but the trees will generally be less accurate. We call this step "k-mer clustering".
The second step is to use the tree to construct what is +sequences, there are (1,000 ´ 999)/2 = +499,500 pairs, so aligning every pair can take a while. MUSCLE uses a much +faster, but somewhat more approximate, method to compute distances: it counts +the number of short sub-sequences (known as k-mers, k-tuples or +words) that two sequences have in common, without constructing an alignment. +This is typically around 3,000 times faster that CLUSTALW's method, but the trees +will generally be less accurate. We call this step "k-mer +clustering".
+ ++ +
The second step is to use the tree to construct what is known as a progressive alignment. At each node of the binary tree, a pair-wise alignment is constructed, progressing from the leaves towards the root. The first alignment will be made from two sequences. Later alignments will be one of the three following types: sequence-sequence, profile-sequence or -profile-profile, where "profile" means the multiple alignment of the sequences under a given internal node of -the tree. This is very similar to what CLUSTALW does once it has built a tree.
+profile-profile, where "profile" means the multiple alignment of the sequences +under a given internal node of the tree. This is very similar to what CLUSTALW +does once it has built a tree. --
Now we have a multiple +
Now we have a multiple alignment, which has been built very quickly compared with conventional -methods, mainly because of the distance calculation using k-mers rather than alignments. The quality of this alignment -is typically pretty goodit will often tie or beat a T-Coffee alignment on our -tests. However, on average, we find that it can be improved by proceeding -through the following steps.
- -From the multiple alignment, we can now compute the pair-wise identities of -each pair of sequences. This gives us a new distance matrix, from which we -estimate a new tree. We compare the old and new trees, and re-align subgroups -where needed to produce a progressive multiple alignment from the new tree. If -the two trees are identical, there is nothing to do; if there are no subtrees -that agree (very unusual), then the whole progressive alignment procedure must -be repeated from scratch. Typically we find that the tree is pretty stable near -the leaves, but some re-alignments are needed closer the root. This procedure -(compute pair-wise identities, estimate new tree, compare trees, re-align) is -iterated until the tree stabilizes or until a specified maximum number of -iterations has been done. We call this process "tree refinement", -although it also tends to improve the alignment.
- -We now keep the tree fixed +methods, mainly because of the distance calculation using k-mers rather +than alignments. The quality of this alignment is typically pretty goodit will +often tie or beat a T-Coffee alignment on our tests. However, on average, we +find that it can be improved by proceeding through the following steps.
+ ++ +
From the multiple alignment, +we can now compute the pair-wise identities of each pair of sequences. This +gives us a new distance matrix, from which we estimate a new tree. We compare +the old and new trees, and re-align subgroups where needed to produce a +progressive multiple alignment from the new tree. If the two trees are +identical, there is nothing to do; if there are no subtrees that agree (very unusual), +then the whole progressive alignment procedure must be repeated from scratch. +Typically we find that the tree is pretty stable near the leaves, but some +re-alignments are needed closer the root. This procedure (compute pair-wise +identities, estimate new tree, compare trees, re-align) is iterated until the +tree stabilizes or until a specified maximum number of iterations has been +done. We call this process "tree refinement", although it also tends +to improve the alignment.
+ ++ +
We now keep the tree fixed and move to a new procedure which is designed to improve the multiple alignment. The set of sequences is divided into two subsets (i.e., we make a bipartition on the set of sequences). A profile is constructed for each of the -two subsets based on the current multiple alignment. -These two profiles are then re-aligned to each other using the same pair-wise -alignment algorithm as used in the progressive stage. If this improves an -"objective score" that measures the quality of the alignment, then -the new multiple alignment is kept, otherwise it is -discarded. By default, the objective score is the classic sum-of-pairs score -that takes the (sequence weighted) average of the pair-wise alignment score of -every pair of sequences in the alignment. Bipartitions are chosen by deleting -an edge in the guide tree, each of the two resulting subtrees defines a subset -of sequences. This procedure is called "tree dependent refinement". One iteration of tree dependent refinement tries +two subsets based on the current multiple alignment. These two profiles are +then re-aligned to each other using the same pair-wise alignment algorithm as +used in the progressive stage. If this improves an "objective score" +that measures the quality of the alignment, then the new multiple alignment is +kept, otherwise it is discarded. By default, the objective score is the classic +sum-of-pairs score that takes the (sequence weighted) average of the pair-wise +alignment score of every pair of sequences in the alignment. Bipartitions are +chosen by deleting an edge in the guide tree, each of the two resulting +subtrees defines a subset of sequences. This procedure is called "tree +dependent refinement". One iteration of tree dependent refinement tries bipartitions produced by deleting every edge of the tree in depth order moving from the leaves towards the center of the tree. Iterations continue until convergence or up to a specified maximum.
--
For convenience, the major -steps in MUSCLE are described as "iterations", though the first three +
For convenience, the major +steps in MUSCLE are described as "iterations", though the first three iterations all do quite different things and may take very different lengths of time to complete. The tree-dependent refinement iterations 3, 4 ... are true iterations and will take similar lengths of time.
--
|
- Iteration
|
There are two types of command-line options: value options +
There are two types of command-line options: value options
and flag options. Value options are followed by the value of the given
parameter, for example in <filename>; flag options just stand for
-themselves, such as msf. All options are a
-dash (not two dashes!) followed by a long name; there are no single-letter
-equivalents. Value options must be separated from their values by white space
-in the command line. Thus, muscle does not follow Unix,
-Linux or Posix standards, for which we apologize. The
+themselves, such as msf. All options are a dash (not two dashes!)
+followed by a long name; there are no single-letter equivalents. Value options
+must be separated from their values by white space in the command line. Thus, muscle
+does not follow Unix, Linux or Posix standards, for which we apologize. The
order in which options are given is irrelevant unless two options contradict,
-in which case the right-most option silently wins.
You can control the number of iterations that MUSCLE does by +
You can control the number of iterations that MUSCLE does by specifying the maxiters option. If you specify 1, 2 or 3, then this is exactly the number of iterations that will be performed. If the value is greater than 3, then muscle will continue up to the maximum you specify or until convergence is reached, which ever happens sooner. The default is 16. If you have a large number of sequences, refinement may be rather slow.
-This option controls the maximum number of new trees to +
This option controls the maximum number of new trees to create in iteration 2. Our experience suggests that a point of diminishing returns is typically reached after the first tree, so the default value is 1. If a larger value is given, the process will repeat until convergence or until this number of trees has been created, which ever comes first.
-If you have a large alignment, muscle may take a long -time to complete. It is sometimes convenient to say "I want the best -alignment I can get in 24 hours" rather than specifying a set of options -that will take an unknown length of time. This is done by using maxhours, which specifies a floating-point number of -hours. If this time is exceeded, muscle will write out current alignment -and stop. For example,
+If you have a large alignment, muscle may take a long +time to complete. It is sometimes convenient to say "I want the best +alignment I can get in 24 hours" rather than specifying a set of options +that will take an unknown length of time. This is done by using maxhours, +which specifies a floating-point number of hours. If this time is exceeded, muscle +will write out current alignment and stop. For example,
--
muscle -in huge.fa -out huge.afa -maxiters 9999 -maxhours 24.0
+muscle -in huge.fa -out huge.afa -maxiters 9999 -maxhours 24.0
--
Note that the actual time may exceed the specified limit by +
Note that the actual time may exceed the specified limit by a few minutes while muscle finishes up on a step. It is also possible for no alignment to be produced if the time limit is too small.
-If the amount of memory needed by MUSCLE exceeds available -physical RAM, then the operating system will probably begin paging (i.e., -swapping memory to and from hard disk), causing MUSCLE to run very slowly. This -is especially problematic when MUSCLE is used for batch processing, where one or -two very large alignments can cause a batch to effectively hang. Starting in -version 3.52, MUSCLE attempts to limit the amount of memory used. If the limit -is exceeded, MUSCLE quits, saving the best alignment so far produced (if any). -MUSCLE attempts to determine the amount of physical RAM by making an -appropriate operating system call. Under Linux and Windows, this works well. On -other systems, particularly other flavors of Unix, -MUSCLE doesn't know how to query the system and assumes that there is 500 Mb of -RAM. To override this default, you can specify the maximum number of megabytes -to allocate by using the maxmb option, for -example to set a limit of 1.5 Gb:
- -muscle -in huge.fa -out huge.afa -maxhours 1.0 -maxmb 1500
- -This feature has been hacked on top of code that wasn't
-really designed for it. So it doesn't always work perfectly, but is better than
-nothing. The ideal solution would be to implement linear space dynamic
-programming code (e.g., the Myers-Miller algorithm) for situations where memory
-is tight. One day I might do this if there is sufficient interest. If you are
-interested in contributing the code, e.g. for a class project, please let me
-know, I'll be glad to provide support.
Three different protein profile scoring functions are +
Three different protein profile scoring functions are
supported, the log-expectation score (le option) and a sum of pairs
-score using either the PAM200 matrix (sp) or the VTML240 matrix (sv). The log-expectation score is the default as it
-gives better results on our tests, but is typically somewhere between two or
-three times slower than the sum-of-pairs score. For nucleotides, spn is currently the only option (which is of course
-the default for nucleotide data, so you don't need to specify this option).
Creating a pair-wise alignment by dynamic programming -requires computing an L1 ´ L2 -matrix, where L1 and L2 are the sequence -lengths. A trick used in algorithms such as BLAST is to reduce the size of this -matrix by using fast methods to find "diagonals", i.e. short regions -of high similarity between the two sequences. This speeds up the algorithm at -the expense of some reduction in accuracy. MUSCLE uses a technique called k-mer extension to find diagonals. It is disabled by default -because of the slight reduction in average accuracy and can be turned on by -specifying the diags option. To enable -diagonal optimization in the first iteration, use diags1, to enable -diagonal optimization in the second iteration, use diags2. These are -provided separately because it would be a reasonable strategy to enable +
Creating a pair-wise alignment by dynamic programming +requires computing an L1 ´ +L2 matrix, where L1 and L2 +are the sequence lengths. A trick used in algorithms such as BLAST is to reduce +the size of this matrix by using fast methods to find "diagonals", also +called "gapless high-scoring segment pairs", i.e. short regions of +high similarity between the two sequences. This speeds up the algorithm at the +expense of some reduction in accuracy. MUSCLE uses a technique called k-mer +extension to find diagonals, which is described in this paper:
+ ++ + + +
+ +
It is disabled by default because of the slight reduction in
+average accuracy and can be turned on by specifying the diags option.
+To enable diagonal optimization in the first iteration, use diags1, to
+enable diagonal optimization in the second iteration, use diags2. These
+are provided separately because it would be a reasonable strategy to enable
diagonals in the first iteration but not the second (because the main goal of
the first iteration is to construct a multiple alignment quickly in order to
improve the distance matrix, which is not very sensitive to alignment quality;
whereas the goal of the second iteration is to make the best possible
-progressive alignment).
Tree-dependent refinement (iterations 3, 4 ... ) can be speeded up by dividing the alignment vertically -into blocks. Block boundaries are found by identifying high-scoring columns -(e.g., a perfectly conserved column of Cs or Ws would be a candidate). Each -vertical block is then refined independently before reassembling the complete -alignment, which is faster because of the L2 factor in -dynamic programming (e.g., suppose the alignment is split into two vertical -blocks, then 2 ´ -0.52 = 0.5, so the dynamic programming time is roughly halved). The -noanchors option is used to disable this -feature. This option has no effect if maxiters 1 or maxiters 2 +
Tree-dependent refinement (iterations 3, 4 ... ) can be
+speeded up by dividing the alignment vertically into blocks. Block boundaries
+are found by identifying high-scoring columns (e.g., a perfectly conserved
+column of Cs or Ws would be a candidate). Each vertical block is then refined
+independently before reassembling the complete alignment, which is faster
+because of the L2 factor in dynamic programming (e.g.,
+suppose the alignment is split into two vertical blocks, then 2 ´ 0.52 = 0.5, so the dynamic
+programming time is roughly halved). The noanchors option is used to disable
+this feature. This option has no effect if maxiters 1 or maxiters 2
is specified. On benchmark tests, enabling anchors has little or no effect on
accuracy, but if you want to be very conservative and are striving for the best
-possible accuracy then noanchors is a
-reasonable choice.
You can specify a log file by using log <filename> -or loga <filename>. Using log -causes any existing file to be deleted, loga -appends to any existing file. A message will be written to the log file when muscle -starts and stops. Error and warning messages will also be written to the log. -If verbose is specified, then more information will be written, -including the command line used to invoke muscle, the resulting internal -parameter settings, and also progress messages. The content and format of -verbose log file output is subject to change in future versions.
- -The use of a log file may seem contrary to Unix conventions for using standard output and standard -error. I like these conventions, but never found a fully satisfactory way to -use them. I like progress messages (see below), but they mess up a file if you -re-direct standard error and there are errors or warning messages too. I could -try to detect whether a standard file handle is a tty device or a disk file and change behavior -accordingly, but I regard this as too complicated and too hard for the user to -understand. On Windows it can be hard to re-direct standard file handles, -especially when working in a GUI debugger. Maybe one day I will figure out a -better solution (suggestions welcomed).
- -I highly recommend using verbose and log[a], +
You can specify a log file by using log <filename> +or loga <filename>. Using log causes any existing file to +be deleted, loga appends to any existing file. A message will be +written to the log file when muscle starts and stops. Error and warning +messages will also be written to the log. If verbose is specified, then +more information will be written, including the command line used to invoke muscle, +the resulting internal parameter settings, and also progress messages. The +content and format of verbose log file output is subject to change in future +versions.
+ ++ +
The use of a log file may seem contrary to Unix conventions for +using standard output and standard error. I like these conventions, but never +found a fully satisfactory way to use them. I like progress messages (see +below), but they mess up a file if you re-direct standard error and there are +errors or warning messages too. I could try to detect whether a standard file +handle is a tty device or a disk file and change behavior accordingly, +but I regard this as too complicated and too hard for the user to understand. On +Windows it can be hard to re-direct standard file handles, especially when +working in a GUI debugger. Maybe one day I will figure out a better solution +(suggestions welcomed).
+ ++ +
I highly recommend using verbose and log[a],
especially when running muscle in a batch mode. This enables you to
verify whether a particular alignment was completed and to review any errors or
-warnings that occurred.
By default, muscle writes progress messages to +
By default, muscle writes progress messages to standard error periodically so that you know it's doing something and get some feedback about the time and memory requirements for the alignment. Here is a typical progress message.
--
00:00:23 25 Mb (5%) Iter -2 87.20% Build guide tree
+00:00:23 25 Mb (5%) Iter 2 87.20% Build guide tree
--
The fields are as follows.
+The fields are as follows.
--
|
- 00:00:23 +
|
-
The quiet command-line option disables writing +
The quiet command-line option disables writing progress messages to standard error. If the verbose command-line option -is specified, a progress message will be written to the log file when each iteration completes. So quiet and verbose -are not contradictory.
+is specified, a progress message will be written to the log file when each +iteration completes. So quiet and verbose are not +contradictory. -The muscle code tries to deal gracefully with -low-memory conditions by using the following technique. A block of "emergency -reserve" memory is allocated when muscle starts. If a later request +
The muscle code tries to deal gracefully with
+low-memory conditions by using the following technique. A block of "emergency
+reserve" memory is allocated when muscle starts. If a later request
to allocate memory fails, this reserve block is made available, and muscle
attempts to save the current alignment. With luck, the reserved memory will be
enough to allow muscle to save the alignment and exit gracefully with an
-informative error message. See also the maxmb
-option.
Here is some general advice on what to do if muscle +
Here is some general advice on what to do if muscle fails and you don't understand what happened. The code is designed to fail gracefully with an informative error message when something goes wrong, but there will no doubt be situations I haven't anticipated (not to mention bugs).
--
Check the MUSCLE web site for updates, bug reports and other +
Check the MUSCLE web site for updates, bug reports and other relevant information.
-- + -
-
Check the input file to make sure it is in valid FASTA +
Check the input file to make sure it is in valid FASTA format. Try giving it to another sequence analysis program that can accept -large FASTA files (e.g., the NCBI formatdb -utility) to see if you get an informative error message. Try dividing the file -into two halves and using each half individually as input. If one half fails -and the other does not, repeat until the problem is -localized as far as possible.
+large FASTA files (e.g., the NCBI formatdb utility) to see if you get an +informative error message. Try dividing the file into two halves and using each +half individually as input. If one half fails and the other does not, repeat +until the problem is localized as far as possible. --
Use log or loga -and verbose and check the log file to see if there are any messages -that give you a hint about the problem. Look at the peak memory requirements -(reported in progress messages) to see if you may be exceeding the physical or -virtual memory capacity of your computer.
+Use log or loga and verbose and +check the log file to see if there are any messages that give you a hint about the +problem. Look at the peak memory requirements (reported in progress messages) +to see if you may be exceeding the physical or virtual memory capacity of your +computer.
--
If muscle crashes without giving an error message, or +
If muscle crashes without giving an error message, or hangs, then you may need to refer to the source code or use a debugger. A -"debug" version, muscled, may be provided. This is built from +"debug" version, muscled, may be provided. This is built from the same source code but with the DEBUG macro defined and without compiler optimizations. This version runs much more slowly (perhaps by a factor of three or more), but does a lot more internal checking and may be able to catch something that is going wrong in the code. The core option specifies that muscle should not catch exceptions. When core is specified, an exception may result in a debugger trap or a core dump, depending on the -execution environment. The nocore option has -the opposite effect. In muscle, nocore -is the default, core is the default in muscled.
+execution environment. The nocore option has the opposite effect. In muscle, +nocore is the default, core is the default in muscled. -I am happy to provide support. But I am busy, and am +
I am happy to provide support. But I am busy, and am offering this program at no charge, so I ask you to make a reasonable effort to -figure things out for yourself before contacting me.
+figure things out for yourself before contacting +me. --
|
- Value option | ||||||
|
+ Value option |
-
- Legal values |
+ Legal values |
-
- Default |
+ Default |
-
- Description |
+ Description |
|
- anchorspacing | ||||||
|
+ anchorspacing |
-
- Integer + |
+ Integer |
-
- 32 |
+ 32 |
-
- Minimum spacing between + |
+ Minimum spacing between anchor columns. -
|
|
- center | ||||||
|
+ center |
-
- Floating point + |
+ Floating point |
-
- [1] |
+ [1] |
-
- Center parameter. Should be + |
+ Center parameter. Should be negative. -
|
|
- cluster1 cluster2 |
-
- upgma upgmb neighborjoining |
-
- upgmb |
-
- Clustering method. cluster1 is used in iteration 1 and 2, cluster2 in later - iterations. - | |||
|
+ cluster1 +cluster2 + |
+
+ upgma +upgmb +neighborjoining + |
+
+ upgmb + |
+
+ Clustering method. cluster1 + is used in iteration 1 and 2, cluster2 in later iterations. +
|
|||
|
- clwout |
-
- File name |
-
- None |
-
- Write output in CLUSTALW + | |||
|
+ clwout + |
+
+ File name + |
+
+ None + |
+
+ Write output in CLUSTALW format to given file name. |
|||
|
- clwout | ||||||
|
+ clwout |
-
- File name |
+ File name |
-
- None |
+ None |
-
- As -clwout, - except that header is strictly compatible with CLUSTALW 1.81. - |
+ As -clwout, except + that header is strictly compatible with CLUSTALW 1.81. +
|
|
- diagbreak | ||||||
|
+ diagbreak |
-
- Integer |
+ Integer |
-
- 1 + |
+ 1 |
-
- Maximum distance between two diagonals that allows them to + |
+ Maximum distance between two diagonals that allows them to merge into one diagonal. -
|
|
- diaglength | ||||||
|
+ diaglength |
-
- Integer |
+ Integer |
-
- 24 |
+ 24 |
-
- Minimum length of diagonal. - |
+ Minimum length of diagonal. +
|
|
- diagmargin | ||||||
|
+ diagmargin |
-
- Integer |
+ Integer |
-
- 5 |
+ 5 |
-
- Discard this many positions + |
+ Discard this many positions at ends of diagonal. -
|
|
- distance1 |
-
- kmer6_6 kmer20_3 kmer20_4 kbit20_3 kmer4_6 |
-
- Kmer6_6 - (amino) or Kmer4_6 (nucleo) - |
-
- Distance measure for iteration 1. + | |||
|
+ distance1 +
|
- ||||||
|
- distance2 |
-
- kmer6_6 kmer20_3 kmer20_4 kbit20_3 pctid_kimura pctid_log |
-
- pctid_kimura - |
-
- Distance measure for iterations 2, 3 ... - |
+ kmer6_6 +kmer20_3 +kmer20_4 +kbit20_3 +kmer4_6 ++ |
+
+ Kmer6_6 + (amino) or Kmer4_6 (nucleo) + |
+
+ Distance measure for iteration 1. |
|
- fastaout | ||||||
|
+ distance2 +
|
-
- File
- name |
+ pctid_kimura +pctid_log +
|
-
- None |
+ pctid_kimura |
-
- Write output in FASTA format to the given file. - |
+ Distance measure for iterations 2, 3 ... ++ + +
|
|
- gapopen | ||||||
|
+ fastaout |
-
- Floating point + |
+ File + name |
-
- [1] |
+ None |
-
- The gap open score. Must be - negative. - |
+ Write output in FASTA format to the given file. +
|
|
- hydro | ||||||
|
+ gapopen |
-
- Integer |
+ Floating point |
-
- 5 |
+ [1] |
-
- Window size for determining whether a region is - hydrophobic. - |
+ The gap open score. Must be negative. +
|
|
- hydrofactor | ||||||
|
+ hydro |
-
- Floating point + |
+ Integer |
-
- 1.2 |
+ 5 |
-
- Multiplier for gap open/close penalties in hydrophobic - regions. - |
+ Window size for determining whether a region is hydrophobic. +
|
|
- in | ||||||
|
+ hydrofactor |
-
- Any file name + |
+ Floating point |
-
- standard input + |
+ 1.2 |
-
- Where to find the input sequences. - |
+ Multiplier for gap open/close penalties in hydrophobic + regions. +
|
|
- in1 | ||||||
|
+ in |
-
- Any file name + |
+ Any file name |
-
- None + |
+ standard input |
-
- Where to find an input alignment. - |
+ Where to find the input sequences. +
|
|
- in2 | ||||||
|
+ in1 |
-
- Any file name + |
+ Any file name |
-
- None + |
+ None |
-
- Where to find an input alignment. - |
+ Where to find an input alignment. +
|
|
- log | ||||||
|
+ in2 |
-
- File name |
+ Any file name |
-
- None. |
+ None |
-
- Log file name (delete existing file). - |
+ Where to find an input alignment. +
|
|
- loga | ||||||
|
+ log |
-
- File name + |
+ File name |
-
- None. + |
+ None. |
-
- Log file name (append to existing file). - |
+ Log file name (delete existing file). +
|
|
- matrix | ||||||
|
+ loga |
-
- File name + |
+ File name |
-
- None + |
+ None. |
-
- File name for substitution matrix in NCBI or WU-BLAST - format. If you specify your own matrix, you should also specify: --gapopen <g>, -gapextend <e> -center 0.0 -Note that <g> and <e> MUST be negative. - |
+ Log file name (append to existing file). +
|
|
- maxhours | ||||||
|
+ matrix |
-
- Floating point + |
+ File name |
-
- None. + |
+ None |
-
- Maximum time to run in hours. The actual time may exceed - the requested limit by a few minutes. Decimals are allowed, so 1.5 means one hour - and 30 minutes. - |
+ File name for substitution matrix in NCBI or WU-BLAST + format. If you specify your own matrix, you should also specify: ++ -gapopen <g>, -gapextend <e> -center 0.0 ++ Note that <g> and <e> MUST be negative. +
|
|
- maxiters | ||||||
|
+ maxhours |
-
- Integer 1, 2 ... + |
+ Floating point |
-
- 16 |
+ None. |
-
- Maximum number of iterations. - |
+ Maximum time to run in hours. The actual time may exceed + the requested limit by a few minutes. Decimals are allowed, so 1.5 means one + hour and 30 minutes. +
|
|
- maxmb | ||||||
|
+ maxiters |
-
- Integer + |
+ Integer 1, 2 ... |
-
- 80%
- of Physical RAM, or 500 Mb if not known. |
+ 16 |
-
- Maximum memory to allocate in Mb. + |
+ Maximum number of iterations. +
|
|
- maxtrees | ||||||
|
+ maxtrees |
-
- Integer + |
+ Integer |
-
- 1 |
+ 1 |
-
- Maximum number of new trees to build in iteration 2. - |
+ Maximum number of new trees to build in iteration 2. +
|
|
- minbestcolscore | ||||||
|
+ minbestcolscore |
-
- Floating point + |
+ Floating point |
-
- [1] + |
+ [1] |
-
- Minimum score a column must + |
+ Minimum score a column must have to be an anchor. -
|
|
- minsmoothscore | ||||||
|
+ minsmoothscore |
-
- Floating point + |
+ Floating point |
-
- [1] + |
+ [1] |
-
- Minimum smoothed score a + |
+ Minimum smoothed score a column must have to be an anchor. -
|
|
- msaout | ||||||
|
+ msaout |
-
- File name + |
+ File name |
-
- None + |
+ None |
-
- Write output to given file + |
+ Write output to given file name in MSF format. -
|
|
- objscore |
-
- sp ps dp xp spf spm |
-
- spm |
-
- Objective score used by tree dependent refinement. -sp=sum-of-pairs score. -spf=sum-of-pairs score (dimer - approximation) -spm=sp for < 100 seqs, otherwise spf -dp=dynamic programming score. -ps=average profile-sequence score. -xp=cross profile score. - | |||
|
+ objscore + |
+
+ sp +ps +dp +xp +spf +spm + |
+
+ spm + |
+
+ Objective score used by tree dependent refinement. +sp=sum-of-pairs score. +spf=sum-of-pairs score (dimer approximation) +spm=sp for < 100 seqs, otherwise spf +dp=dynamic programming score. +ps=average profile-sequence score. +xp=cross profile score. +
|
|||
|
- out | ||||||
|
+ out |
-
- File name + |
+ File name |
-
- standard output + |
+ standard output |
-
- Where to write the alignment. - |
+ Where to write the alignment. +
|
|
- phyiout | ||||||
|
+ phyiout |
-
- File name + |
+ File name |
-
- None + |
+ None |
-
- Write output in Phylip - interleaved format to given file name. - |
+ Write output in Phylip interleaved format to given file + name. +
|
|
- physout | ||||||
|
+ physout |
-
- File name + |
+ File name |
-
- None + |
+ None |
-
- Write output in Phylip - sequential format to given file name. - |
+ Write output in Phylip sequential format to given file + name. +
|
|
- refinewindow | ||||||
|
+ refinewindow |
-
- Integer + |
+ Integer |
-
- 200 + |
+ 200 |
-
- Length of window for -refinew. - |
+ Length of window for -refinew. +
|
|
- root1 root2 |
-
- pseudo midlongestspan minavgleafdist |
-
- psuedo |
-
- Method used to root tree; root1 is used in iteration 1 and + | |||
|
+ root1 +root2 + |
+
+ pseudo +midlongestspan +minavgleafdist + |
+
+ psuedo + |
+
+ Method used to root tree; root1 is used in iteration 1 and 2, root2 in later iterations. -+
|
|||
|
- scorefile | ||||||
|
+ scorefile |
-
- File
- name |
+ File + name |
-
- None |
+ None |
-
- File name where to write a score file. This contains one + |
+ File name where to write a score file. This contains one line for each column in the alignment. The line contains the letters in the column followed by the average BLOSUM62 score over pairs of letters in the column. -
|
|
- seqtype |
-
- protein nucleo auto |
-
- auto |
-
- Sequence type. + | |||
|
+ seqtype + |
+
+ protein +dna +rna +auto ++ |
+
+ auto + |
+
+ Sequence type. |
|||
|
- smoothscoreceil | ||||||
|
+ smoothscoreceil |
-
- Floating point + |
+ Floating point |
-
- [1] + |
+ [1] |
-
- Maximum value of column score for - smoothing purposes. - |
+ Maximum value of column score for smoothing purposes. +
|
|
- smoothwindow | ||||||
|
+ smoothwindow |
-
- Integer |
+ Integer |
-
- 7 |
+ 7 |
-
- Window used for anchor column smoothing. - |
+ Window used for anchor column smoothing. +
|
|
- spscore | ||||||
|
+ spscore |
-
- File name |
+ File name |
-
- |
+
|
-
- Compute SP objective score of multiple alignment. - |
+ Compute SP objective score of multiple alignment. +
|
|
- SUEFF | ||||||
|
+ SUEFF |
-
- Floating point value between 0 and 1. - |
+ Floating point value between 0 and 1. +
|
-
- 0.1 |
+ 0.1 |
-
- Constant used in UPGMB clustering. Determines the relative
- fraction of average linkage (SUEFF) vs. nearest-neighbor linkage (1 SUEFF). |
+ Constant used in UPGMB clustering. Determines the relative
+ fraction of average linkage (SUEFF) vs. nearest-neighbor linkage (1 SUEFF). |
|
- tree1 tree2 | ||||||
|
+ tree1 +tree2 |
-
- File name + |
+ File name |
-
- None |
+ None |
-
- Save tree produced in first or second iteration to given - file in Newick (Phylip-compatible) - format. - |
+ Save tree produced in first or second iteration to given + file in Newick (Phylip-compatible) format. +
|
|
- usetree | ||||||
|
+ usetree |
-
- File name + |
+ File name |
-
- None |
+ None |
-
- Use given tree as guide tree. Must by in Newick (Phyip-compatible) - format. - |
+ Use given tree as guide tree. Must by in Newick + (Phyip-compatible) format. +
|
|
- weight1 weight2 |
-
- none henikoff henikoffpb gsc clustalw threeway - |
-
- clustalw |
-
- Sequence weighting scheme. -weight1 - is used in iterations 1 and 2. -weight2 - is used for tree-dependent refinement. -none=all - sequences have equal weight. -henikoff=Henikoff & + | |||
|
+ weight1 +weight2 + |
+
+ none +henikoff +henikoffpb +gsc +clustalw +threeway + |
+
+ clustalw ++ |
+
+ Sequence weighting scheme. +weight1 is used in + iterations 1 and 2. +weight2 is used for + tree-dependent refinement. +none=all sequences have + equal weight. +henikoff=Henikoff & Henikoff weighting scheme. -henikoffpb=Modified + henikoffpb=Modified Henikoff scheme as used in PSI-BLAST. -clustalw=CLUSTALW method. -threeway=Gotoh three-way + clustalw=CLUSTALW method. +threeway=Gotoh three-way method. -
|
-
|
- Flag option | ||||
|
+ Flag option |
-
- Set by default? |
+ Set by default? |
-
- Description |
+ Description |
|
- anchors |
-
- yes |
-
- Use anchor optimization in + | ||
|
+ anchors + |
+
+ yes + |
+
+ Use anchor optimization in tree dependent refinement iterations. -
|
||
|
- brenner |
-
- no - |
-
- Use Steven Brenner's method + | ||
|
+ brenner + |
+
+ no + |
+
+ Use Steven Brenner's method for computing the root alignment. -
|
||
|
- cluster |
-
- no - |
-
- Perform fast clustering of + | ||
|
+ cluster + |
+
+ no + |
+
+ Perform fast clustering of input sequences. Use the tree1 option to save the tree. -
|
||
|
- dimer |
-
- no - |
-
- Use dimer approximation for + | ||
|
+ dimer + |
+
+ no + |
+
+ Use dimer approximation for the SP score (faster, slightly less accurate). -
|
||
|
- clw |
-
- no |
-
- Write output in CLUSTALW + | ||
|
+ clw + |
+
+ no + |
+
+ Write output in CLUSTALW format (default is FASTA). -
|
||
|
- clwstrict |
-
- no - |
-
- Write output in CLUSTALW - format with the "CLUSTAL W (1.81)" header rather than the MUSCLE + | ||
|
+ clwstrict + |
+
+ no + |
+
+ Write output in CLUSTALW + format with the "CLUSTAL W (1.81)" header rather than the MUSCLE version. This is useful when a post-processing step is picky about the file header. -
|
||
|
- core |
-
- yes in muscle, -no
- in muscled. |
-
- Do not catch exceptions. - | ||
|
+ core + |
+
+ yes in muscle, +no in muscled. + |
+
+ Do not catch exceptions. ++
|
||
|
- diags |
-
- no |
-
- Use diagonal optimizations. + | ||
|
+ diags + |
+
+ no + |
+
+ Use diagonal optimizations. Faster, especially for closely related sequences, but may be less accurate. -
|
||
|
- diags1 |
-
- no - |
-
- Use diagonal optimizations + | ||
|
+ diags1 + |
+
+ no + |
+
+ Use diagonal optimizations in first iteration. -
|
||
|
- diags2 |
-
- no - |
-
- Use diagonal optimizations + | ||
|
+ diags2 + |
+
+ no + |
+
+ Use diagonal optimizations in second iteration. -
|
||
|
- fasta |
-
- yes |
-
- Write output in FASTA + | ||
|
+ fasta + |
+
+ yes + |
+
+ Write output in FASTA format. -
|
||
|
- group |
-
- yes |
-
- Group similar sequences + | ||
|
+ group + |
+
+ yes + |
+
+ Group similar sequences together in the output. This is the default. See also stable. -
|
||
|
- html |
-
- no |
-
- Write output in HTML format + | ||
|
+ html + |
+
+ no + |
+
+ Write output in HTML format (default is FASTA). -
|
||
|
- le + | ||||
|
+ le |
-
- maybe |
+ maybe |
-
- Use log-expectation profile score (VTML240). Alternatives
- are to use sp or sv. This is the
- default for amino acid sequences. |
+ Use log-expectation profile score (VTML240). Alternatives + are to use sp or sv. This is the default for amino acid + sequences. +
|
|
- msf |
-
- no |
-
- Write output in MSF format (default is FASTA). Designed to + | ||
|
+ msf + |
+
+ no + |
+
+ Write output in MSF format (default is FASTA). Designed to be compatible with the GCG package. -
|
||
|
- noanchors |
-
- no |
-
- Disable anchor optimization. Default is anchors. | ||
|
+ noanchors + |
+
+ no + |
+
+ Disable anchor optimization. Default is anchors. +
|
||
|
- nocore |
-
- no in muscle, -yes in muscled. |
-
- Catch exceptions and give an error message if possible. - | ||
|
+ nocore + |
+
+ no in muscle, +yes in muscled. + |
+
+ Catch exceptions and give an error message if possible. ++
|
||
|
- phyi |
-
- no |
-
- Write output in Phylip - interleaved format. - | ||
|
+ phyi + |
+
+ no + |
+
+ Write output in Phylip interleaved format. +
|
||
|
- phys | ||||
|
+ phys |
-
- no + |
+ no |
-
- Write output in Phylip - sequential format. - |
+ Write output in Phylip sequential format. +
|
|
- profile |
-
- no |
-
- Compute profile-profile alignment. Input alignments must + | ||
|
+ profile + |
+
+ no + |
+
+ Compute profile-profile alignment. Input alignments must be given using in1 and in2 options. -
|
||
|
- quiet | ||||
|
+ quiet |
-
- no |
+ no |
-
- Do not display progress messages. - |
+ Do not display progress messages. +
|
|
- refine |
-
- no |
-
- Input file is already aligned, skip first two iterations + | ||
|
+ refine + |
+
+ no + |
+
+ Input file is already aligned, skip first two iterations and begin tree dependent refinement. -
|
||
|
- refinew |
-
- no |
-
- Refine an alignment by dividing it into non-overlapping + | ||
|
+ refinew + |
+
+ no + |
+
+ Refine an alignment by dividing it into non-overlapping windows and re-aligning each window. Typically used for whole-genome nucleotide alignments. -
|
||
|
- sp |
-
- no |
-
- Use sum-of-pairs protein profile score (PAM200). Default
- is le. | ||
|
+ sp + |
+
+ no + |
+
+ Use sum-of-pairs protein profile score (PAM200). Default + is le. +
|
||
|
- spscore |
-
- no - |
-
- Compute alignment score of profile-profile alignment. + | ||
|
+ spscore + |
+
+ no + |
+
+ Compute alignment score of profile-profile alignment. Input alignments must be given using in1 and in2 options. These must be pre-aligned with gapped columns as needed, i.e. must be of the same length (have same number of columns). -
|
||
|
- spn |
-
- maybe - |
-
- Use sum-of-pairs nucleotide profile score. This is the + | ||
|
+ spn + |
+
+ maybe ++ |
+
+ Use sum-of-pairs nucleotide profile score. This is the only option for nucleotides, and is therefore the default. The substitution - scores and gap penalty scores are "borrowed" from BLASTZ. -
|
||
|
- stable |
-
- no |
-
- Preserve input order of sequences in output file. Default + | ||
|
+ stable + |
+
+ no + |
+
+ Preserve input order of sequences in output file. Default is to group sequences by similarity (group). -WARNING THIS OPTION WAS + BUGGY AND IS NOT SUPPORTED IN v3.8. Go to this link for more + information: http://drive5.com/muscle/stable.html +
|
||
|
- sv |
-
- no |
-
- Use sum-of-pairs profile score (VTML240). Default is le. - | ||
|
+ sv + |
+
+ no + |
+
+ Use sum-of-pairs profile score (VTML240). Default is le. +
|
||
|
- termgaps4 |
-
- yes |
-
- Use 4-way test for treatment of terminal gaps. (Cannot be + | ||
|
+ termgaps4 + |
+
+ yes + |
+
+ Use 4-way test for treatment of terminal gaps. (Cannot be disabled in this version). -
|
||
|
- termgapsfull |
-
- no |
-
- Terminal gaps penalized with full penalty. -[1] Not fully supported in this version. - | ||
|
+ termgapsfull + |
+
+ no + |
+
+ Terminal gaps penalized with full penalty. +[1] Not fully supported in this version. +
|
||
|
- termgapshalf |
-
- yes |
-
- Terminal gaps penalized with half penalty. -[1] Not fully supported in this version. - | ||
|
+ termgapshalf + |
+
+ yes + |
+
+ Terminal gaps penalized with half penalty. +[1] Not fully supported in this version. +
|
||
|
- termgapshalflonger |
-
- no |
-
- Terminal gaps penalized with half penalty if gap relative + | ||
|
+ termgapshalflonger + |
+
+ no + |
+
+ Terminal gaps penalized with half penalty if gap relative to -longer sequence, otherwise with - full penalty. -[1] Not fully supported in this version. -longer sequence, otherwise with full penalty. +[1] Not fully supported in this version. +
|
||
|
- verbose |
-
- no |
-
- Write parameter settings and progress messages to log + | ||
|
+ verbose + |
+
+ no + |
+
+ Write parameter settings and progress messages to log file. -
|
||
|
- version | ||||
|
+ version |
-
- no |
+ no |
-
- Write version string to stdout - and exit. + |
+ Write version string to stdout and exit. |
-
Notes
Notes
-[1] Default depends on the profile scoring function. To +
[1] Default depends on the profile scoring function. To determine the default, use verbose log and check the log file.
-