/var/lib/mobyle/programs/hmmscan.xml is in mobyle-programs 5.1.2-1.
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<!-- XML Authors: Corinne Maufrais -->
<!-- 'Biological Software and Databases' Group, Institut Pasteur, Paris. -->
<!-- Distributed under LGPLv2 License. Please refer to the COPYING.LIB document. -->
<program>
<head>
<name>hmmscan</name>
<xi:include xmlns:xi="http://www.w3.org/2001/XInclude" href="Entities/hmmer_package.xml"/>
<doc>
<title>HMMSCAN</title>
<description>
<text lang="en">Search sequence(s) against pfam a profile HMM database</text>
</description>
<comment>
<text lang="en">hmmscan reads sequence(s) from seqfile and compares it against all the HMMs in pfam
database looking for significantly similar sequence matches.
The output consists of three sections: a ranked list of the best scoring HMMs,
a list of the best scoring domains in order of their occurrence in the sequence,
and alignments for all the best scoring domains. A sequence score may be higher than a
domain score for the same sequence if there is more than one domain in the sequence;
the sequence score takes into account all the domains. All sequences scoring above the
-E and -T cutoffs are shown in the first list, then every domain found in this list is shown
in the second list of domain hits. If desired, E-value and score thresholds may also be applied
to the domain list using the --domE and --domT options.
</text>
</comment>
</doc>
<category>hmm:database:search</category>
<category>database:search:hmm</category>
<command>hmmscan</command>
</head>
<parameters>
<parameter ismandatory="1" issimple="1">
<name>seqfile</name>
<prompt lang="en">Sequence file</prompt>
<type>
<datatype>
<class>Sequence</class>
</datatype>
<dataFormat>FASTA</dataFormat>
</type>
<format>
<code proglang="perl">" $value"</code>
<code proglang="python">" "+str(value)</code>
</format>
<argpos>3</argpos>
</parameter>
<parameter issimple="1">
<name>HMMDB</name>
<prompt lang="en">HMM database</prompt>
<type>
<datatype>
<class>Choice</class>
</datatype>
</type>
<vdef>
<value>Pfam-A.hmm</value>
</vdef>
<vlist>
<velem>
<value>Pfam-A.hmm</value>
<label>Pfam-A</label>
</velem>
<velem>
<value>Pfam-B.hmm</value>
<label>Pfam-B</label>
</velem>
</vlist>
<format>
<code proglang="perl">" $value"</code>
<code proglang="python">" "+str(value)</code>
</format>
<argpos>2</argpos>
</parameter>
<paragraph>
<name>thresholds_report</name>
<prompt lang="en">Options for reporting thresholds</prompt>
<argpos>1</argpos>
<parameters>
<parameter issimple="1">
<name>E_value_cutoff</name>
<prompt lang="en">E_value cutoff (-E)</prompt>
<type>
<datatype>
<class>Float</class>
</datatype>
</type>
<precond>
<code proglang="perl">not defined $Bit_cutoff and $model_specific ne '--cut_ga' and $model_specific ne '--cut_nc'</code>
<code proglang="python">Bit_cutoff is None and model_specific != '--cut_ga' and model_specific != '--cut_nc'</code>
</precond>
<vdef>
<value>10.0</value>
</vdef>
<format>
<code proglang="perl">(defined $value and $value != $vdef) ? " -E $value" : ""</code>
<code proglang="python">( "" , " -E " + str(value) )[ value is not None and value != vdef]</code>
</format>
<argpos>1</argpos>
<comment>
<text lang="en">In the per-target output, report target profiles with an E-value of <= value. The
default is 10.0, meaning that on average, about 10 false positives will be reported
per query, so you can see the top of the 'noise' and decide for yourself if it's really
noise.</text>
</comment>
</parameter>
<parameter>
<name>Bit_cutoff</name>
<prompt lang="en">Bit score cutoff (-T)</prompt>
<type>
<datatype>
<class>Float</class>
</datatype>
</type>
<precond>
<code proglang="perl">$E_value_cutoff == 10.0 and $model_specific ne '--cut_ga' and $model_specific ne '--cut_nc'</code>
<code proglang="python">E_value_cutoff == 10.0 and model_specific != '--cut_ga' and model_specific != '--cut_nc'</code>
</precond>
<format>
<code proglang="perl">(defined $value)? " -T $value" : ""</code>
<code proglang="python">( "" , " -T " + str(value) )[ value is not None ]</code>
</format>
<argpos>1</argpos>
<comment>
<text lang="en">Instead of thresholding per-profile output on E-value, instead report target profiles
with a bit score of >= value.</text>
</comment>
</parameter>
<parameter>
<name>domE</name>
<prompt lang="en">E-value cutoff for the per-domain ranked hit list (--domE)</prompt>
<type>
<datatype>
<class>Float</class>
</datatype>
</type>
<precond>
<code proglang="perl">not defined $domT and $model_specific ne '--cut_ga' and $model_specific ne '--cut_nc'</code>
<code proglang="python">domT is None and model_specific != '--cut_ga' and model_specific != '--cut_nc'</code>
</precond>
<vdef>
<value>10.0</value>
</vdef>
<format>
<code proglang="perl">(defined $value and $value != $vdef) ? " --domE $value" : ""</code>
<code proglang="python">( "" , " --domE " + str(value) )[ value is not None and value !=vdef ]</code>
</format>
<comment>
<text lang="en">In the per-domain output, for target profiles that have already satisfied the perprofile
reporting threshold, report individual domains with a conditional E-value
of <= value. The default is 10.0. A 'conditional' E-value means the expected
number of additional false positive domains in the smaller search space of those
comparisons that already satisfied the per-profile reporting threshold (and thus
must have at least one homologous domain already).</text>
</comment>
</parameter>
<parameter>
<name>domT</name>
<prompt lang="en">Bit score cutoff for the per-domain ranked hit list (--domT)</prompt>
<type>
<datatype>
<class>Float</class>
</datatype>
</type>
<precond>
<code proglang="perl">$domE == 10.0 and $model_specific ne '--cut_ga' and $model_specific ne '--cut_nc'</code>
<code proglang="python">domE == 10.0 and model_specific != '--cut_ga' and model_specific != '--cut_nc'</code>
</precond>
<format>
<code proglang="perl">(defined $value) ? " --domT $value" : ""</code>
<code proglang="python">( "" , " --domT " + str(value) )[ value is not None ]</code>
</format>
<comment>
<text lang="en">Instead of thresholding per-domain output on E-value, instead report domains with
a bit score of >= value.</text>
</comment>
</parameter>
<paragraph>
<name>thresholds_inclusion</name>
<prompt lang="en">Options controlling inclusion (significance) thresholds.</prompt>
<argpos>1</argpos>
<comment>
<text lang="en">'Inclusion' thresholds are stricter than reporting thresholds. Inclusion thresholds
control which hits are considered to be reliable enough to be included in an output alignment or a
subsequent search round. In hmmscan, which does not have any alignment output nor any iterative
search steps, inclusion thresholds have little effect. They only affect what domains get
marked as significant ('!') or questionable ('?') in domain output.</text>
</comment>
<parameters>
<parameter>
<name>incE</name>
<prompt lang="en">Include sequences lower than this E-value threshold (--incE)</prompt>
<type>
<datatype>
<class>Float</class>
</datatype>
</type>
<precond>
<code proglang="perl">not defined $incT and $model_specific ne '--cut_ga' </code>
<code proglang="python">incT is None and model_specific != '--cut_ga' </code>
</precond>
<vdef>
<value>0.01</value>
</vdef>
<format>
<code proglang="perl">(defined $value and value != vdef) ? " --incE $value" : ""</code>
<code proglang="python">( "" , " --incE " + str(value) )[ value is not None and value != vdef]</code>
</format>
<comment>
<text lang="en">Use an E-value of <= value as the per-target inclusion threshold. The default is
0.01, meaning that on average, about 1 false positive would be expected in every
100 searches with different query sequences.</text>
</comment>
</parameter>
<parameter>
<name>incdomE</name>
<prompt lang="en">Include domains lower than this E-value threshold (--incdomE)</prompt>
<type>
<datatype>
<class>Float</class>
</datatype>
</type>
<precond>
<code proglang="perl">defined $incdomT and not defined model_specific</code>
<code proglang="python">incdomT is not None and model_specific is None</code>
</precond>
<vdef>
<value>0.01</value>
</vdef>
<format>
<code proglang="perl">(defined $value and value != vdef) ? " --incdomE $value" : ""</code>
<code proglang="python">( "" , " --incdomE " + str(value) )[ value is not None and value != vdef]</code>
</format>
<comment>
<text lang="en">Use a conditional E-value of <= value as the per-domain inclusion threshold, in
targets that have already satisfied the overall per-target inclusion threshold. The
default is 0.01.</text>
</comment>
</parameter>
<parameter>
<name>incT</name>
<prompt lang="en">Include sequences upper than this score threshold (--incT)</prompt>
<type>
<datatype>
<class>Float</class>
</datatype>
</type>
<precond>
<code proglang="perl">$incE == 0.01 and $model_specific ne '--cut_ga'</code>
<code proglang="python">incE == 0.01 and model_specific != '--cut_ga'</code>
</precond>
<format>
<code proglang="perl">(defined $value) ? " --incT $value" : ""</code>
<code proglang="python">( "" , " --incT " + str(value) )[ value is not None ]</code>
</format>
<comment>
<text lang="en">Instead of using E-values for setting the inclusion threshold, instead use a bit score
of >= the value as the per-target inclusion threshold. It would be unusual to use bit
score thresholds with hmmscan, because you don't expect a single score threshold
to work for different profiles; different profiles have slightly different expected score
distributions.</text>
</comment>
</parameter>
<parameter>
<name>incdomT</name>
<prompt lang="en">Include domans upper than this score threshold (--incdomT)</prompt>
<type>
<datatype>
<class>Float</class>
</datatype>
</type>
<precond>
<code proglang="perl">$incdomE == 0.01 and not defined $model_specific </code>
<code proglang="python">incdomE == 0.01 and model_specific is None</code>
</precond>
<format>
<code proglang="perl">(defined $value) ? " --incdomT $value" : ""</code>
<code proglang="python">( "" , " --incdomT " + str(value) )[ value is not None ]</code>
</format>
<comment>
<text lang="en">Instead of using E-values, instead use a bit score of >= value as the per-domain
inclusion threshold. As with --incT above, it would be unusual to use a single bit
score threshold in hmmscan.</text>
</comment>
</parameter>
</parameters>
</paragraph>
<parameter>
<name>model_specific</name>
<prompt lang="en">Options for model-specific thresholding</prompt>
<type>
<datatype>
<class>Choice</class>
</datatype>
</type>
<precond>
<code proglang="perl">not defined $Bit_cutoff and not $E_value_cutoff == 10.0 and not defined $incdomT and $incdomE == 0.01</code>
<code proglang="python">not Bit_cutoff and E_value_cutoff == 10.0 and incdomT is None and incdomE == 0.01</code>
</precond>
<vdef>
<value>null</value>
</vdef>
<vlist>
<velem undef="1">
<value>null</value>
<label>No profile</label>
</velem>
<velem>
<value>--cut_ga</value>
<label>use profile's GA gathering cutoffs (cut_ga)</label>
</velem>
<velem>
<value>--cut_nc</value>
<label>use profile's NC noise cutoffs (cut_nc)</label>
</velem>
<velem>
<value>--cut_tc</value>
<label>use profile's TC trusted cutoffs (cut_tc)</label>
</velem>
</vlist>
<format>
<code proglang="perl">(defined $value and $value ne $vdef) ? " $value" : ""</code>
<code proglang="python">( "" , " " + str(value) )[ value is not None and value != vdef]</code>
</format>
<comment>
<text lang="en">Curated profile databases may define specific bit score thresholds for each profile, superseding any thresholding
based on statistical significance alone. To use these options, the profile must contain the appropriate
(GA, TC, and/or NC) optional score threshold annotation; this is picked up by hmmbuild from Stockholm
format alignment files. Each thresholding option has two scores: the per-sequence threshold x1 value and the
per-domain threshold x2 value. These act as if -T x1 --incT x1 --domT x2 --incdomT x2 has been
applied specifically using each model's curated thresholds.</text>
<text lang="en">cut ga: Use the GA (gathering) bit scores in the model to set per-sequence (GA1) and
per-domain (GA2) reporting and inclusion thresholds. GA thresholds are generally
considered to be the reliable curated thresholds defining family membership; for
example, in Pfam, these thresholds define what gets included in Pfam Full alignments
based on searches with Pfam Seed models.</text>
<text lang="en">cut_nc: Use the NC (noise cutoff) bit score thresholds in the model to set per-sequence
(NC1) and per-domain (NC2) reporting and inclusion thresholds. NC thresholds
are generally considered to be the score of the highest-scoring known false positive.</text>
<text lang="en">cut_tc: Use the NC (trusted cutoff) bit score thresholds in the model to set per-sequence
(TC1) and per-domain (TC2) reporting and inclusion thresholds. TC thresholds are
generally considered to be the score of the lowest-scoring known true positive that
is above all known false positives.</text>
</comment>
</parameter>
</parameters>
</paragraph>
<paragraph>
<name>acceleration</name>
<prompt lang="en">Options controlling acceleration heuristics</prompt>
<argpos>1</argpos>
<comment>
<text lang="en">HMMER3 searches are accelerated in a three-step filter pipeline: the MSV filter, the Viterbi filter, and
the Forward filter. The first filter is the fastest and most approximate; the last is the full Forward scoring
algorithm. There is also a 'bias filter' step between MSV and Viterbi. Targets that pass all the steps
in the acceleration pipeline are then subjected to 'postprocessing' -- domain identification and scoring
using the Forward/Backward algorithm. Changing filter thresholds only removes or includes targets from
consideration; changing filter thresholds does not alter bit scores, E-values, or alignments, all of which are
determined solely in 'postprocessing'.</text>
</comment>
<parameters>
<parameter>
<name>max</name>
<prompt lang="en">Turn all heuristic filters off (less speed, more power) (--max)</prompt>
<type>
<datatype>
<class>Boolean</class>
</datatype>
</type>
<vdef>
<value>0</value>
</vdef>
<format>
<code proglang="perl">($value) ? " --max" : ""</code>
<code proglang="python">( "" , " --max " )[ value ]</code>
</format>
<comment>
<text lang="en">Turn off all filters, including the bias filter, and run full Forward/Backward postprocessing
on every target. This increases sensitivity somewhat, at a large cost in speed.</text>
</comment>
</parameter>
<parameter>
<name>F1</name>
<prompt>Stage 1 (MSV) threshold</prompt>
<type>
<datatype>
<class>Float</class>
</datatype>
</type>
<precond>
<code proglang="perl">not max</code>
<code proglang="python">not max</code>
</precond>
<vdef>
<value>0.02</value>
</vdef>
<format>
<code proglang="perl">(defined $value and $value != $vdef ) ? " --F1 $value" : ""</code>
<code proglang="python">( "" , " --F1 " + str(value) )[ value is not None and value != vdef]</code>
</format>
<comment>
<text lang="en">Set the P-value threshold for the MSV filter step. The default is 0.02, meaning that
roughly 2% of the highest scoring nonhomologous targets are expected to pass the filter.</text>
</comment>
</parameter>
<parameter>
<name>F2</name>
<prompt>Stage 1 (Vit) threshold</prompt>
<type>
<datatype>
<class>Float</class>
</datatype>
</type>
<precond>
<code proglang="perl">not max</code>
<code proglang="python">not max</code>
</precond>
<vdef>
<value>0.001</value>
</vdef>
<format>
<code proglang="perl">(defined $value and $value != $vdef ) ? " --F2 $value" : ""</code>
<code proglang="python">( "" , " --F2 " + str(value) )[ value is not None and value != vdef]</code>
</format>
<comment>
<text lang="en">Set the P-value threshold for the Viterbi filter step. The default is 0.001.</text>
</comment>
</parameter>
<parameter>
<name>F3</name>
<prompt>Stage 1 (Fwd) threshold</prompt>
<type>
<datatype>
<class>Float</class>
</datatype>
</type>
<precond>
<code proglang="perl">not max</code>
<code proglang="python">not max</code>
</precond>
<vdef>
<value>0.00001</value>
</vdef>
<format>
<code proglang="perl">(defined $value and $value != $vdef ) ? " --F3 $value" : ""</code>
<code proglang="python">( "" , " --F3 " + str(value) )[ value is not None and value != vdef]</code>
</format>
<comment>
<text lang="en">Set the P-value threshold for the Forward filter step. The default is 1e-5.</text>
</comment>
</parameter>
<parameter>
<name>nobias</name>
<prompt lang="en">Turn off composition bias filter (--nobias)</prompt>
<type>
<datatype>
<class>Boolean</class>
</datatype>
</type>
<precond>
<code proglang="perl">not max</code>
<code proglang="python">not max</code>
</precond>
<vdef>
<value>0</value>
</vdef>
<format>
<code proglang="perl">($value) ? " --nobias" : ""</code>
<code proglang="python">( "" , " --nobias " )[ value ]</code>
</format>
<comment>
<text lang="en">Turn off the bias filter. This increases sensitivity somewhat, but can come at a
high cost in speed, especially if the query has biased residue composition (such
as a repetitive sequence region, or if it is a membrane protein with large regions
of hydrophobicity). Without the bias filter, too many sequences may pass the filter
with biased queries, leading to slower than expected performance as the computationally
intensive Forward/Backward algorithms shoulder an abnormally heavy
load.</text>
</comment>
</parameter>
</parameters>
</paragraph>
<paragraph>
<name>expert</name>
<prompt lang="en">Other expert options</prompt>
<argpos>1</argpos>
<parameters>
<parameter>
<name>nonull2</name>
<prompt lang="en">Turn off biased composition score corrections (--nonull2)</prompt>
<type>
<datatype>
<class>Boolean</class>
</datatype>
</type>
<vdef>
<value>0</value>
</vdef>
<format>
<code proglang="perl">($value) ? " --nonull2" : ""</code>
<code proglang="python">( "" , " --nonull2 " )[ value ]</code>
</format>
<comment>
<text lang="en">Turn off the 'null2' score corrections for biased composition.</text>
</comment>
</parameter>
<parameter>
<name>E_value_calculation</name>
<prompt lang="en">Control of E_value calculation (-Z)</prompt>
<type>
<datatype>
<class>Integer</class>
</datatype>
</type>
<format>
<code proglang="perl">(defined $value) ? " -Z $value" : ""</code>
<code proglang="python">( "" , " -Z " + str(value) )[ value is not None ]</code>
</format>
<argpos>1</argpos>
<comment>
<text lang="en">Assert that the total number of targets in your searches is the value, for the purposes of
per-sequence E-value calculations, rather than the actual number of targets seen.</text>
</comment>
</parameter>
<parameter>
<name>domZ</name>
<prompt lang="en">Set Z score of significant sequences, for domain E-value calculation (--domZ)</prompt>
<type>
<datatype>
<class>Float</class>
</datatype>
</type>
<format>
<code proglang="perl">(defined $value) ? " --domZ $value" : ""</code>
<code proglang="python">( "" , " --domZ " + str(value) )[ value is not None ]</code>
</format>
<comment>
<text lang="en">Assert that the total number of targets in your searches is the value, for the purposes
of per-domain conditional E-value calculations, rather than the number of targets
that passed the reporting thresholds.</text>
</comment>
</parameter>
<parameter>
<name>seed</name>
<prompt lang="en">Set RNG seed number (--seed)</prompt>
<type>
<datatype>
<class>Integer</class>
</datatype>
</type>
<vdef>
<value>42</value>
</vdef>
<format>
<code proglang="perl">(defined $value and $value != $vdef) ? " --seed $value " : ""</code>
<code proglang="python">( "" , " --seed " + str(value) )[ value is not None and value !=vdef ]</code>
</format>
<comment>
<text lang="en">Set the random number seed to value. Some steps in postprocessing require Monte
Carlo simulation. The default is to use a fixed seed (42), so that results are exactly
reproducible. Any other positive integer will give different (but also reproducible)
results. A choice of 0 uses a 'randomly chosen' seed.</text>
</comment>
<ctrl>
<message>
<text lang="en">Enter a value >= 0</text>
</message>
<code proglang="perl">0 <= $value</code>
<code proglang="python">0 <= value</code>
</ctrl>
</parameter>
</parameters>
</paragraph>
<paragraph>
<name>controlOutput</name>
<prompt lang="en">Options controlling output</prompt>
<parameters>
<parameter>
<name>outfile_name</name>
<prompt lang="en">Name of the sequence(s) file (-o)</prompt>
<type>
<datatype>
<class>Filename</class>
</datatype>
</type>
<format>
<code proglang="perl">(defined $value ) ? " -o $value" : ""</code>
<code proglang="python">( " " , " -o " + str(value) )[ value is not None ]</code>
</format>
<argpos>1</argpos>
</parameter>
<parameter isout="1">
<name>output_file_name</name>
<prompt lang="en">Output file</prompt>
<type>
<datatype>
<class>Text</class>
</datatype>
</type>
<precond>
<code proglang="perl">defined $outfile_name</code>
<code proglang="python">outfile_name is not None</code>
</precond>
<filenames>
<code proglang="perl">$outfile_name</code>
<code proglang="python">str(outfile_name)</code>
</filenames>
</parameter>
<parameter>
<name>perseqfile_name</name>
<prompt lang="en">File name of parseable table of per-sequence hits (--tblout)</prompt>
<type>
<datatype>
<class>Filename</class>
</datatype>
</type>
<format>
<code proglang="perl">(defined $value) ? " --tblout $value" : ""</code>
<code proglang="python">( "" , " --tblout " + str(value) )[ value is not None ]</code>
</format>
<comment>
<text lang="en">Save a simple tabular (space-delimited) file summarizing the 'per-target' output,
with one data line per homologous target model found</text>
</comment>
<argpos>1</argpos>
</parameter>
<parameter isout="1">
<name>output_perseqfile_name</name>
<prompt lang="en">Output parseable table of per-sequence hits</prompt>
<type>
<datatype>
<class>Text</class>
</datatype>
</type>
<precond>
<code proglang="perl">$perseqfile_name</code>
<code proglang="python">perseqfile_name</code>
</precond>
<filenames>
<code proglang="perl">$perseqfile_name</code>
<code proglang="python">str(perseqfile_name)</code>
</filenames>
</parameter>
<parameter>
<name>perdomfile_name</name>
<prompt lang="en">File name of parseable table of per-domain hits (--domtblout)</prompt>
<type>
<datatype>
<class>Filename</class>
</datatype>
</type>
<format>
<code proglang="perl">(defined $value) ? " --domtblout $value" : ""</code>
<code proglang="python">( "" , " --domtblout " + str(value) )[ value is not None ]</code>
</format>
<argpos>1</argpos>
<comment>
<text lang="en">Save a simple tabular (space-delimited) file summarizing the 'per-domain' output,
with one data line per homologous domain detected in a query sequence for each
homologous model.</text>
</comment>
</parameter>
<parameter>
<name>acc</name>
<prompt lang="en">Prefer accessions over names in output</prompt>
<type>
<datatype>
<class>Boolean</class>
</datatype>
</type>
<vdef>
<value>0</value>
</vdef>
<format>
<code proglang="perl">($value) ? " --acc " : ""</code>
<code proglang="python">( "" , " --acc " )[ value ]</code>
</format>
<comment>
<text lang="en">Use accessions instead of names in the main output, where available for profiles
and/or sequences</text>
</comment>
</parameter>
<parameter>
<name>noali</name>
<prompt lang="en">Don't output alignments, so output is smaller</prompt>
<type>
<datatype>
<class>Boolean</class>
</datatype>
</type>
<vdef>
<value>0</value>
</vdef>
<format>
<code proglang="perl">($value) ? " --noali " : ""</code>
<code proglang="python">( "" , " --noali " )[ value ]</code>
</format>
<comment>
<text lang="en">Omit the alignment section from the main output. This can greatly reduce the
output volume.</text>
</comment>
</parameter>
<parameter>
<name>notextw</name>
<prompt lang="en">Unlimit ASCII text output line width (--notextw)</prompt>
<type>
<datatype>
<class>Boolean</class>
</datatype>
</type>
<precond>
<code proglang="perl">textw == 120</code>
<code proglang="python">textw == 120</code>
</precond>
<vdef>
<value>0</value>
</vdef>
<format>
<code proglang="perl">($value) ? " --notextw " : ""</code>
<code proglang="python">( "" , " --notextw " )[ value ]</code>
</format>
<comment>
<text lang="en">Unlimit the length of each line in the main output. The default is a limit of 120
characters per line, which helps in displaying the output cleanly on terminals and
in editors, but can truncate target profile description lines.</text>
</comment>
</parameter>
<parameter>
<name>textw</name>
<prompt lang="en">Set max width of ASCII text output lines (--textw)</prompt>
<type>
<datatype>
<class>Integer</class>
</datatype>
</type>
<vdef>
<value>120</value>
</vdef>
<format>
<code proglang="perl">(defined $value and $value != $vdef) ? " --textw $value " : ""</code>
<code proglang="python">( "" , " --textw " + str(value) )[ value is not None and value !=vdef ]</code>
</format>
<comment>
<text lang="en">Set the main output's line length limit to value> characters per line. The default is
120.</text>
</comment>
</parameter>
<parameter isout="1">
<name>output_perdomfile_name</name>
<prompt lang="en">Output parseable table of per-domain hits</prompt>
<type>
<datatype>
<class>Text</class>
</datatype>
</type>
<precond>
<code proglang="perl">$perdomfile_name</code>
<code proglang="python">perdomfile_name</code>
</precond>
<filenames>
<code proglang="perl">$perdomfile_name</code>
<code proglang="python">str(perdomfile_name)</code>
</filenames>
</parameter>
</parameters>
</paragraph>
</parameters>
</program>
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