350 lines
16 KiB
HTML
Executable File
350 lines
16 KiB
HTML
Executable File
<!DOCTYPE html>
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<html>
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<head>
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<meta charset="utf-8">
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<title>beadstring - MEME Suite</title>
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<link rel="shortcut icon" type="image/x-icon" href="images/memesuite_icon.ico">
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<link rel="icon" type="image/png" href="images/memesuite_icon.png">
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<link href="css/style.css" rel="stylesheet" type="text/css">
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<script src="js/menu.js"></script>
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<script src="js/shared-doc.js"></script>
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</head>
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<body>
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<div class="memesuitelogo">
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<h1>The MEME Suite</h1>
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<h2>Motif-based sequence analysis tools</h2>
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</div>
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<h2>Beadstring (unsupported)</h2>
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<div class="usage">
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<h3>Usage:</h3>
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<code>beadstring [options] <motifs> <database></code>
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</div>
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<h3>Description</h3>
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<div class="indent">
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<p>Beadstring builds a linear hidden Markov model (HMM) from the motifs
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and motif occurences listed in the motif file, and uses that HMM to
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search a sequence database for a particular ordered series of motifs. A
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description of the algorithm is found in:</p>
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<span class="citation">
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<a href="http://bioinformatics.oxfordjournals.org/cgi/content/abstract/13/4/397">
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Grundy, Bailey, Elkan and Baker. "Meta-MEME: Motif-based Hidden Markov Models of Protein Families".
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<i>Computer Applications in the Biosciences.</i> 13(4):397-406, 1997.
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</a>
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</span>
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<p>By default, the order and spacing of motifs in the model is determined
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from the "Summary of Motifs" section of the MEME input file. Beadstring
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searches the summary for the sequence that contains the maximal number of
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distinct motif occurrences. If there is a tie, then beadstring selects the
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sequence with the smallest combined <i>p</i>-value. Beadstring then
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eliminates all but the most significant occurrence of each motif and uses
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the resulting order and spacing of motif occurrences to initialize the
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HMM. This procedure can be overridden by selecting the
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<span class="popt">--motif</span>,
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<span class="popt">--motif-e-thresh</span>,
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<span class="popt">--motif-p-thresh</span> or
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<span class="popt">--order</span> options.</p>
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<p>The command line option <span class="popt">--p-score</span> activates
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an alternative scoring mode, called "<i>p</i>-value scoring." This scoring
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method is described in:</p>
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<span class="citation">
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<a href="http://bioinformatics.oxfordjournals.org/cgi/reprint/19/suppl_2/ii16">
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Bailey and Noble. "Searching for statistically significant regulatory modules."
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<i>Bioinformatics</i> 19(Suppl 2):ii16-ii25, 2003.
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</a>
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</span>
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</div>
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<h3>Input</h3>
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<div class="indent">
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<h4>Motifs</h4>
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<p>A file of motifs from MEME (DREME does not have the
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"Summary of Motifs" section).</p>
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<h4>Database</h4>
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<p>A database of sequences in <a href="fasta-format.html">FASTA format</a>.</p>
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</div>
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<h3>Output</h3>
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<div class="indent">
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<p>Beadstring will create a directory, named <code>beadstring_out</code>
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by default. Any existing output files in the directory will be
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overwritten. The directory will contain:</p>
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<ul>
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<li>An XML file named <code>beadstring.xml</code> using the
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<a href="http://zlab.bu.edu/~phaverty/SupplementalData/CisML">CisML</a>
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schema.</li>
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<li>An XML file named <code>model.xml</code> using the MEME_HMM
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schema.</li>
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<li>An HTML file named <code>beadstring.html</code></li>
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<li>A plain text file named <code>beadstring.text</code></li>
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</ul>
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<p>The default output directory can be overridden using the
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<style class="popt">--o</style> or <style class="popt">--oc</style>
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options which are described below.</p>
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</div>
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<h3>Options</h3>
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<div class="indent">
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<table class="options">
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<thead>
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<tr>
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<th>Option</th>
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<th>Parameter</th>
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<th>Description</th>
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<th>Default Behaviour</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<th colspan="4">Input/Output</th>
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</tr>
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<tr>
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<td class="popt">--bgfile</td><td><span class="pdat">bfile</span></td>
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<td>Read background frequencies from <span class="pdat">bfile</span>.
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The file should be in
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<a href="bfile-format.html">MEME background file format</a>.
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The default is to use frequencies embedded in the application from
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the non-redundant database. If the argument is the keyword
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<code>motif-file</code>, then the frequencies will be taken from
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the motif file.</td>
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<td>Use NR frequencies.</td>
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</tr>
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<tr>
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<td class="popt">--e-thresh</td><td><span class="pdat">ev</span></td>
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<td>Only print results with E-values less than
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<span class="pdat">ev</span>.</td>
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<td>Print results with E-values less than 0.01.</td>
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</tr>
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<tr>
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<td class="popt">--max-seqs</td><td><span class="pdat">max</span></td>
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<td>Print results for no more than <span class="pdat">max</span>
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sequences.</td>
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<td>All matches are reported, up to the specified E-value
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threshold (see <span class="popt">--e-thresh</span>).
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</tr>
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<tr>
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<td class="popt">--model-file</td><td><span class="pdat">model file</span></td>
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<td>Creation of the HMM will be skipped, and the HMM will be read
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from the file instead.</td>
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<td>The HMM will be created.</td>
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</tr>
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<tr>
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<td class="popt">--no-search</td><td> </td>
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<td>This option turns off the search phase of beadstring.
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The HMM will be stored if the <span class="popt">--model</span>
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option is specified.</td>
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<td>The search phase runs as normal.</td>
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</tr>
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<script>
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wropt("all-o", {"ddash": true, "dir": "beadstring_out"});
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wropt("all-oc", {"ddash": true, "dir": "beadstring_out"});
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</script>
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<tr>
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<td class="popt">--progress</td><td><span class="pdat">value</span></td>
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<td>Print to standard error a progress message approximately every
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<span class="pdat">value</span> seconds.</td>
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<td>No progress message.</td>
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</tr>
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<tr>
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<td class="popt">--score-file</td><td><span class="pdat">score file</span></td>
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<td>Cause a score file (in BLAST format) to be read and used
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instead of the built-in PAM (for proteins) or
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transition/transversion (for DNA) score file. Several score files
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are provided (including BLOSUM62) in the directory
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<code>doc</code>. Other, user-provided score files may be
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specified as well, as long as they are in the proper format.</td>
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<td>Uses the built-in score file.</td>
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</tr>
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<script>wropt("all-verbosity");</script>
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</tbody>
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<tbody>
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<tr>
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<th colspan="4">Motif Selection</th>
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</tr>
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<tr>
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<td class="popt">--motif</td><td><span class="pdat">id</span></td>
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<td>Use only the motif identified by <span class="pdat">id</span>.
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This option may be repeated.</td>
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<td>Use all motifs that pass the other motif selection options.</td>
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</tr>
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<tr>
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<td class="popt">--motif-e-thresh</td><td><span class="pdat">ev</span></td>
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<td>Use only motifs with E-values less than
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<span class="pdat">ev</span>.</td>
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<td>Use all motifs that pass the other motif selection options.</td>
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</tr>
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<tr>
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<td class="popt">--motif-p-thresh</td><td><span class="pdat">pv</span></td>
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<td>Use only motifs with <i>p</i>-values less than
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<span class="pdat">pv</span>.</td>
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<td>Use all motifs that pass the other motif selection options.</td>
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</tr>
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<tr>
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<td class="popt">--order</td><td><span class="pdat">string</span></td>
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<td>The given string specifies the order and spacing of the motifs
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within the model, and has the format "l=n=l=n=...=l=n=l", where
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"l" is the length of a region between motifs, and "n" is a motif
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index. Thus, for example, the string "34=3=17=2=5" specifies a
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two-motif linear model, with motifs 3 and 2 separated by 17
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letters and flanked by 34 letters and 5 letters on the left and
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right. If the motif file contains motif occurrences on both
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strands, then the motif IDs in the order string should be
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preceded by "+" or "-" indicating the strandedness of the
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motif.</td>
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<td>The order and spacing is determined from the motif file.</td>
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</tr>
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</tbody>
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<tbody>
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<tr>
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<th colspan="4">Building The Model</th>
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</tr>
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<tr>
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<td class="popt">--fim</td><td> </td>
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<td>Gaps between motifs are not penalized. Spacer states between
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motifs are represented as free-insertion modules (FIM). A FIM is
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an insert state with 1.0 probability of self-transition and 1.0
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probability of exit transition. Thus, traversing such a state has
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zero transition cost. Specifying this option causes all spacers to
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be represented using FIMs.</td>
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<td></td>
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</tr>
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<tr>
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<td class="popt">--gap-extend</td><td><span class="pdat">cost</span></td>
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<td>This switch causes <b>all</b> spacer self-loop log-odds scores
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to be set to <span class="pdat">cost</span>. In addition, it
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causes all other transitions out of a spacer to be set to zero.
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Together with the <span class="popt">--gap-open</span> switch,
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this allows you to specify an affine gap penalty function,
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overriding the gap penalty implicit in the model (self-loop
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transition probabilities of gap states).</td>
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<td></td>
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</tr>
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<tr>
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<td class="popt">--gap-open</td><td><span class="pdat">cost</span></td>
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<td>This switch causes <b>all</b> transitions into a spacer state
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to be assigned a log-odds score equal to
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<span class="pdat">cost</span>. Together with the
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<span class="popt">--gap-extend</span> switch, this allows you to
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specify an affine gap penalty function, overriding the gap penalty
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implicit in the model (transition probabilities into and out of
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gap states).</td>
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<td></td>
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</tr>
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<tr>
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<td class="popt">--motif-pseudo</td><td>num</td>
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<td>A pseudocount to be added to each count in the motif matrix,
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after first multiplying by the corresponding background
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frequency.</td>
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<td>No pseudocount is added to motif matrix probabilities.</td>
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</tr>
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<tr>
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<td class="popt">--nspacer</td><td><span class="pdat">value</span></td>
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<td>By default each spacer is modeled using a single insert state.
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The distribution of spacer lengths produced by a single insert
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state is exponential in form. A more reasonable distribution would
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be a bell-shaped curve such as a Gaussian. Modeling the length
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distribution explicitly is computationally expensive; however, a
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Gaussian distribution can be approximated using multiple insert
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states to represent a single spacer region. The
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<span class="popt">--nspacer</span> option specifies the number of
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insert states used to represent each spacer.</td>
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<td>A single insert state is used.</td>
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</tr>
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<tr>
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<td class="popt">--spacer-pseudo</td><td><span class="pdat">value</span></td>
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<td>Specify the value of the pseudocount used in converting
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transition counts to spacer self-loop probabilities.</td>
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<td>No pseudocount is added to self-loop probabilities.</td>
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</tr>
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<tr>
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<td class="popt">--trans-pseudo</td><td><span class="pdat">value</span></td>
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<td>Specify the value of the pseudocount used in converting
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transition counts to transition probabilities.</td>
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<td>A pseudocount of 0.1 is added to transition probabilities.</td>
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</tr>
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<tr>
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<td class="popt">--zselo</td><td> </td>
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<td>Spacer emission log-odds scores to be set to zero. This
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prevents regions of unusual base/residue composition matching
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spacers well when the spacer emission frequencies are different
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than the background frequencies. It is particularly useful with
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DNA models.</td>
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<td></td>
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</tr>
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</tbody>
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<tbody>
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<tr>
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<th colspan="4">Scoring</th>
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</tr>
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<tr>
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<td class="popt">--allow-weak-motifs</td><td> </td>
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<td>In p-value score mode, weak motifs are defined as ones where
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the best possible hit has a p-value greater than the
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<i>p</i>-value threshold. Such motifs cannot contribute to a match
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in p-value score mode. By default, the program rejects any search
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results containing weak motifs, unless the
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<span class="popt">--allow-weak-motifs</span> switch is given. In
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that case, the search will proceed, but the weak motifs will never
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appear in any matches. <b>Note</b>:This switch only applies to
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<i>p</i>-value score mode.</td>
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<td></td>
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</tr>
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<tr>
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<td class="popt">--global</td><td> </td>
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<td>Scores are computed for the match between the entire sequence
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and the model.</td>
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<td>Use the maximal local score.</td>
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</tr>
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<tr>
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<td class="popt">--pam</td><td><span class="pdat">distance</span></td>
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<td>By default, target probabilities are derived from the
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distance-250 PAM matrix for proteins, and from a
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<span class="pdat">distance</span>-1 transition/transversion
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matrix for DNA. With the <span class="popt">-pam</span> switch,
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you can specify a different <b>integer</b> distance from 1 to 500.
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(This can be overridden with the
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<span class="popt">--score-file</span> switch below). The
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<span class="pdat">distance</span>-1 transition/transversion joint
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probability matrix for DNA is given below:
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<pre>
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A C G T
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A .990 .002 .006 .002
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C .002 .990 .002 .006
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G .006 .002 .990 .002
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T .002 .006 .002 .990
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</pre>
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</td>
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<td></td>
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</tr>
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<tr>
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<td class="popt">--paths</td><td><span class="popt">single</span>|<span class="popt">all</span></td>
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<td>This option determines how the program computes raw scores.
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With the <span class="popt">single</span> option, the program
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computes the Viterbi score, which is the log-odds score associated
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with the single most likely match between the sequence and the
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model. The <span class="popt">all</span> option yields the total
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log-odds score, which is the sum of the log-odds of all
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sequence-to-model matches.</td>
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<td>Viterbi scoring is used.</td>
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</tr>
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<tr>
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<td class="popt">--p-score</td><td><span class="popt">num</span></td>
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<td>The <code>--p-score</code> switch activates <i>p</i>-value
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score mode with the given threshold. In p-value score mode, motif
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match scores are converted to their p-values. They are then
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converted to bit scores as follows:
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<div style="margin-left: 2em">S = -log<sub>2</sub>(p/T)</div>
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where S is the bit score of the hit, p is the p-value of the
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log-odds score, and T is the p-value threshold. In this way, only
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hits more significant than the p-value threshold get positive
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scores. The p-value threshold, T, must be in the range 0<T≤1.</td>
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<td>log-odds score mode is used.</td>
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</tr>
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</tbody>
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</table>
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</div>
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</body>
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</html>
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