comparison cmsearch.xml @ 2:fac157e22e1b draft

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1:55bb96edfc07

<tool id="infernal_cmsearch" name="Search covariance model(s)" version="1.1.0.2">
    <description>against a sequence database (cmsearch)</description>
    <parallelism method="multi" split_inputs="seqdb" split_mode="to_size" split_size="100" shared_inputs="" merge_outputs="outfile,multiple_alignment_output"></parallelism>
    <requirements>
        <requirement type="package">infernal</requirement>
        <requirement type="package" version="1.1">infernal</requirement>
        <requirement type="package" version="8.21">gnu_coreutils</requirement>
    </requirements>
    <command>
        ## a temp file is needed, because the standard tabular output from infernal is not usefull in Galaxy
        ## it will be converted to a tab delimited file and piped to Galaxy
        temp_tabular_output=\$(mktemp);

        cmsearch 
            ## Infernal Options
            --cpu "\${GALAXY_SLOTS:-12}"
            -o /dev/null
            --tformat $seqdb.ext ##target format: fasta, embl, genbank, ddbj, stockholm, pfam, a2m, afa, clustal, and phylip 
            $bottomonly
            $toponly
            $cyk
            $notrunc
            $max

                $cm_opts.cmfile
            #end if

            ## sequence file
            $seqdb
            2>&1
            ;

            ## 1. replace all lines starting # (comment lines)
            ## 2. replace the first 18 spaces with tabs, 18th field is a free text field (can contain spaces)
            sed -e 's/#.*$//' -e '/^$/d' -e 's/\s\+/\t/g' -e 's/\t/ /18g' \$temp_tabular_output > $outfile

    </command>
        <inputs>

            <param name="seqdb" type="data" format="fasta" label="Sequence database"/>

                <when value="histdb">
                    <param name="cmfile" type="data" format="cm" label="Covariance models file from the history."/>
                </when>
            </conditional>

            <param name="g" truevalue="-g" falsevalue="" checked="False" type="boolean" 
                label="Turn on the glocal alignment algorithm" help="... global with respect to the query model and local with respect to the target database."/>

            <param name="bottomonly" truevalue="--bottomonly" falsevalue="" checked="False" type="boolean" 
                label="Only search the bottom (Crick) strand of target sequences" help="in the sequence database"/>
            <param name="toponly" truevalue="--toponly" falsevalue="" checked="False" type="boolean" 
                label="Only search the top (Watson) strand of target sequences" help="in the sequence database"/>

            <param name="cyk" truevalue="--cyk" falsevalue="" checked="False" type="boolean" 
                label="Use the CYK algorithm, not Inside, to determine the final score of all hits" help=""/>
            <param name="--acyk" truevalue="--cyk" falsevalue="" checked="False" type="boolean" 
                label="Use the CYK algorithm to align hits" help="By default, the Durbin/Holmes optimal accuracy algorithm is used, which finds the alignment that maximizes the expected accuracy of all aligned residues."/>

            <param name="notrunc" truevalue="--notrunc" falsevalue="" checked="False" type="boolean" 
                label="Turn off truncated hit detection" help=""/>

            <!-- accelleration pipeline -->

            <param name="max" truevalue="--max" falsevalue="" checked="False" type="boolean" 
                label="Turn off all filters, and run non-banded Inside on every full-length target sequence" help="This
                increases sensitivity somewhat, at an extremely large cost in speed."/>

            <param name="nohmm" truevalue="--nohmm" falsevalue="" checked="False" type="boolean" 
                label="Turn off all HMM filter stages " help=""/>

            <param name="mid" truevalue="--mid" falsevalue="" checked="False" type="boolean" 
                label="Turn off the HMM SSV and Viterbi filter stages" help=""/>


            <!-- Options for model-specific score thresholding -->
            <!--

                        </sanitizer>
                    </param>
                </when>
            </conditional>

            <param name="A" truevalue="-A" falsevalue="" checked="False" type="boolean" 
                label="Save a multiple alignment of all significant hits" help="... those satisfying inclusion thresholds"/>

        </inputs>
    <outputs>

            <filter>A is True</filter>
        </data>

    </outputs>
    <help>


**What it does**

Infernal is used to search sequence databases for homologs of structural RNA sequences, and to make
sequence- and structure-based RNA sequence alignments. Infernal needs a profile from a structurally
annotated multiple sequence alignment of an RNA family with a position-specific scoring system for substitutions, 
insertions, and deletions. Positions in the profile that are basepaired in the consensus secondary
structure of the alignment are modeled as dependent on one another, allowing Infernal’s scoring system to
consider the secondary structure, in addition to the primary sequence, of the family being modeled. Infernal
profiles are probabilistic models called “covariance models”, a specialized type of stochastic context-free
grammar (SCFG) (Lari and Young, 1990).

Compared to other alignment and database search tools based only on sequence comparison, Infernal
aims to be significantly more accurate and more able to detect remote homologs because it models sequence 
and structure.


Output format
-------------

(5) mdl (model): Which type of model was used to compute the final score. Either ’cm’ or ’hmm’. A CM is used to compute the final hit scores unless the model has zero basepairs or the --hmmonly option is used, in which case a HMM will be used.
(6) mdl from (model coord): The start of the alignment of this hit with respect to the profile (CM or HMM), numbered 1..N for a profile of N consensus positions.
(7) mdl to (model coord): The end of the alignment of this hit with respect to the profile (CM or HMM), numbered 1..N for a profile of N consensus positions.
(8) seq from (ali coord): The start of the alignment of this hit with respect to the sequence, numbered 1..L for a sequence of L residues.
(9) seq to (ali coord): The end of the alignment of this hit with respect to the sequence, numbered 1..L for a sequence of L residues.
(10) strand: The strand on which the hit occurs on the sequence. ’+’ if the hit is on the top (Watson) strand, ’-’ if the hit is on the bottom (Crick) strand. If on the top strand, the “seq from” value will be less than or equal to the “seq to” value, else it will be greater than or equal to it. 
(11) trunc: Indicates if this is predicted to be a truncated CM hit or not. This will be “no” if it is a CM hit that is not predicted to be truncated by the end of the sequence, “5’ ” or “3’ ” if the hit is predicted to have one or more 5’ or 3’ residues missing due to a artificial truncation of the sequence, or “5’&3”’ if the hit is predicted to have one or more 5’ residues missing and one or more 3’ residues missing. If the hit is an HMM hit, this will always be ’-’.
(12) pass: Indicates what “pass” of the pipeline the hit was detected on. This is probably only useful for testing and debugging. Non-truncated hits are found on the first pass, truncated hits are found on successive passes.
(13) gc: Fraction of G and C nucleotides in the hit.
(14) bias: The biased-composition correction: the bit score difference contributed by the null3 model for CM hits, or the null2 model for HMM hits. High bias scores may be a red flag for a false positive. It is difficult to correct for all possible ways in which a nonrandom but nonhomologous biological sequences can appear to be similar, such as short-period tandem repeats, so there are cases where the bias correction is not strong enough (creating false positives).
(15) score: The score (in bits) for this target/query comparison. It includes the biased-composition cor-rection (the “null3” model for CM hits, or the “null2” model for HMM hits).
(16) E-value: The expectation value (statistical significance) of the target. This is a per query E-value; i.e. calculated as the expected number of false positives achieving this comparison’s score for a single query against the search space Z. For cmsearch Z is defined as the total number of nucleotides in the target dataset multiplied by 2 because both strands are searched. For cmscan Z is the total number of nucleotides in the query sequence multiplied by 2 because both strands are searched and multiplied by the number of models in the target database. If you search with multiple queries and if you want to control the overall false positive rate of that search rather than the false positive rate per query, you will want to multiply this per-query E-value by how many queries you’re doing.

How do I cite Infernal?
-----------------------

The recommended citation for using Infernal 1.1 is E. P. Nawrocki and S. R. Eddy, Infernal 1.1: 100-fold faster RNA homology searches , Bioinformatics 29:2933-2935 (2013). 

**Galaxy Wrapper Author**::

    *  Bjoern Gruening, University of Freiburg

    </help>
</tool>

2:fac157e22e1b

<tool id="infernal_cmsearch" name="Search covariance model(s)" version="1.1.0.2">
    <description>against a sequence database (cmsearch)</description>
    <parallelism method="multi" split_inputs="seqdb" split_mode="to_size" split_size="500" shared_inputs="" merge_outputs="outfile,multiple_alignment_output"></parallelism>
    <requirements>
        <requirement type="package">infernal</requirement>
        <requirement type="package" version="1.1">infernal</requirement>
        <requirement type="package" version="8.22">gnu_coreutils</requirement>
    </requirements>
    <command>
<![CDATA[
        ## a temp file is needed, because the standard tabular output from infernal is not usefull in Galaxy
        ## it will be converted to a tab delimited file and piped to Galaxy
        temp_tabular_output=\$(mktemp);

        cmsearch
            ## Infernal Options
            --cpu "\${GALAXY_SLOTS:-12}"
            -o /dev/null
            --tformat $seqdb.ext ##target format: fasta, embl, genbank, ddbj, stockholm, pfam, a2m, afa, clustal, and phylip
            $bottomonly
            $toponly
            $cyk
            $notrunc
            $max

                $cm_opts.cmfile
            #end if

            ## sequence file
            $seqdb
            2>&1
            ;

            ## 1. replace all lines starting # (comment lines)
            ## 2. replace the first 18 spaces with tabs, 18th field is a free text field (can contain spaces)
            sed -e 's/#.*$//' -e '/^$/d' -e 's/\s\+/\t/g' -e 's/\t/ /18g' \$temp_tabular_output > $outfile

]]>
    </command>
        <inputs>

            <param name="seqdb" type="data" format="fasta" label="Sequence database"/>

                <when value="histdb">
                    <param name="cmfile" type="data" format="cm" label="Covariance models file from the history."/>
                </when>
            </conditional>

            <param name="g" truevalue="-g" falsevalue="" checked="False" type="boolean"
                label="Turn on the glocal alignment algorithm" help="... global with respect to the query model and local with respect to the target database."/>

            <param name="bottomonly" truevalue="--bottomonly" falsevalue="" checked="False" type="boolean"
                label="Only search the bottom (Crick) strand of target sequences" help="in the sequence database"/>
            <param name="toponly" truevalue="--toponly" falsevalue="" checked="False" type="boolean"
                label="Only search the top (Watson) strand of target sequences" help="in the sequence database"/>

            <param name="cyk" truevalue="--cyk" falsevalue="" checked="False" type="boolean"
                label="Use the CYK algorithm, not Inside, to determine the final score of all hits" help=""/>
            <param name="--acyk" truevalue="--cyk" falsevalue="" checked="False" type="boolean"
                label="Use the CYK algorithm to align hits" help="By default, the Durbin/Holmes optimal accuracy algorithm is used, which finds the alignment that maximizes the expected accuracy of all aligned residues."/>

            <param name="notrunc" truevalue="--notrunc" falsevalue="" checked="False" type="boolean"
                label="Turn off truncated hit detection" help=""/>

            <!-- accelleration pipeline -->

            <param name="max" truevalue="--max" falsevalue="" checked="False" type="boolean"
                label="Turn off all filters, and run non-banded Inside on every full-length target sequence" help="This
                increases sensitivity somewhat, at an extremely large cost in speed."/>

            <param name="nohmm" truevalue="--nohmm" falsevalue="" checked="False" type="boolean"
                label="Turn off all HMM filter stages " help=""/>

            <param name="mid" truevalue="--mid" falsevalue="" checked="False" type="boolean"
                label="Turn off the HMM SSV and Viterbi filter stages" help=""/>


            <!-- Options for model-specific score thresholding -->
            <!--

                        </sanitizer>
                    </param>
                </when>
            </conditional>

            <param name="A" truevalue="-A" falsevalue="" checked="False" type="boolean"
                label="Save a multiple alignment of all significant hits" help="... those satisfying inclusion thresholds"/>

        </inputs>
    <outputs>

            <filter>A is True</filter>
        </data>

    </outputs>
    <help>
<![CDATA[


**What it does**

Infernal is used to search sequence databases for homologs of structural RNA sequences, and to make
sequence- and structure-based RNA sequence alignments. Infernal needs a profile from a structurally
annotated multiple sequence alignment of an RNA family with a position-specific scoring system for substitutions,
insertions, and deletions. Positions in the profile that are basepaired in the consensus secondary
structure of the alignment are modeled as dependent on one another, allowing Infernal’s scoring system to
consider the secondary structure, in addition to the primary sequence, of the family being modeled. Infernal
profiles are probabilistic models called “covariance models”, a specialized type of stochastic context-free
grammar (SCFG) (Lari and Young, 1990).

Compared to other alignment and database search tools based only on sequence comparison, Infernal
aims to be significantly more accurate and more able to detect remote homologs because it models sequence
and structure.


Output format
-------------

(5) mdl (model): Which type of model was used to compute the final score. Either ’cm’ or ’hmm’. A CM is used to compute the final hit scores unless the model has zero basepairs or the --hmmonly option is used, in which case a HMM will be used.
(6) mdl from (model coord): The start of the alignment of this hit with respect to the profile (CM or HMM), numbered 1..N for a profile of N consensus positions.
(7) mdl to (model coord): The end of the alignment of this hit with respect to the profile (CM or HMM), numbered 1..N for a profile of N consensus positions.
(8) seq from (ali coord): The start of the alignment of this hit with respect to the sequence, numbered 1..L for a sequence of L residues.
(9) seq to (ali coord): The end of the alignment of this hit with respect to the sequence, numbered 1..L for a sequence of L residues.
(10) strand: The strand on which the hit occurs on the sequence. ’+’ if the hit is on the top (Watson) strand, ’-’ if the hit is on the bottom (Crick) strand. If on the top strand, the “seq from” value will be less than or equal to the “seq to” value, else it will be greater than or equal to it.
(11) trunc: Indicates if this is predicted to be a truncated CM hit or not. This will be “no” if it is a CM hit that is not predicted to be truncated by the end of the sequence, “5’ ” or “3’ ” if the hit is predicted to have one or more 5’ or 3’ residues missing due to a artificial truncation of the sequence, or “5’&3”’ if the hit is predicted to have one or more 5’ residues missing and one or more 3’ residues missing. If the hit is an HMM hit, this will always be ’-’.
(12) pass: Indicates what “pass” of the pipeline the hit was detected on. This is probably only useful for testing and debugging. Non-truncated hits are found on the first pass, truncated hits are found on successive passes.
(13) gc: Fraction of G and C nucleotides in the hit.
(14) bias: The biased-composition correction: the bit score difference contributed by the null3 model for CM hits, or the null2 model for HMM hits. High bias scores may be a red flag for a false positive. It is difficult to correct for all possible ways in which a nonrandom but nonhomologous biological sequences can appear to be similar, such as short-period tandem repeats, so there are cases where the bias correction is not strong enough (creating false positives).
(15) score: The score (in bits) for this target/query comparison. It includes the biased-composition cor-rection (the “null3” model for CM hits, or the “null2” model for HMM hits).
(16) E-value: The expectation value (statistical significance) of the target. This is a per query E-value; i.e. calculated as the expected number of false positives achieving this comparison’s score for a single query against the search space Z. For cmsearch Z is defined as the total number of nucleotides in the target dataset multiplied by 2 because both strands are searched. For cmscan Z is the total number of nucleotides in the query sequence multiplied by 2 because both strands are searched and multiplied by the number of models in the target database. If you search with multiple queries and if you want to control the overall false positive rate of that search rather than the false positive rate per query, you will want to multiply this per-query E-value by how many queries you’re doing.

How do I cite Infernal?
-----------------------

The recommended citation for using Infernal 1.1 is E. P. Nawrocki and S. R. Eddy, Infernal 1.1: 100-fold faster RNA homology searches , Bioinformatics 29:2933-2935 (2013).

**Galaxy Wrapper Author**::

    *  Bjoern Gruening, University of Freiburg

]]>
    </help>
</tool>