view pca.xml @ 5:1414831b3c86 draft default tip

"planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/tree/master/tools/bio3d commit 3b99f08f22b9e0c16c0a0adc82f8c16c1a25cedf"

<tool id="bio3d_pca" name="PCA" version="@VERSION@">
    <description>- principal component analysis using Bio3D</description>    
    <macros>
        <import>macros.xml</import>
    </macros>   
    <expand macro="requirements" />
    <command detect_errors="exit_code">
<![CDATA[ 
   Rscript '$__tool_directory__/pca.R'
        '$dcdin' 
        '$pdbin'
        '$method'
        #if $pca.sele == 'calpha':
          "string"
           "calpha"
        #end if
        #if $pca.sele == 'cbeta':
          "string"
          '$pca.cbeta'
        #end if
        #if $pca.sele == 'backbone':
          "string"
          "backbone"
        #end if
        #if $pca.sele == 'sidechain':
          "string"
          "sidechain"
        #end if
        #if $pca.sele == 'protein':
          "string"
          "protein"
        #end if
        #if $pca.sele == 'ligand':
          "string"
          "ligand"
        #end if
        #if $pca.sele == 'nucleic':
          "string"
          "nucleic"
        #end if
        #if $pca.sele == 'elety':
          "elety"
          '$pca.elety'
        #end if
        #if $pca.sele == 'resid':
          "resid"
          '$pca.resid'
        #end if
        #if $pca.sele == 'segid':
          "segid"
          '$pca.segid'
        #end if
        '$output' 
        '$pca_plot' 
        '$pca_cluster' 
        '$pc1_rmsf'
    2>&1
]]></command>
    <inputs>
        <expand macro="analysis_inputs"/>
        <param name="method" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="false"
            label="Use singular value decomposition (SVD) instead of default eigenvalue decomposition ?" help="Default: No" />
        <conditional name="pca">
           <param name="sele" type="select" label="Select domains">
             <option value="calpha">C-alpha</option>
             <option value="cbeta">C-beta</option>
             <option value="backbone">Backbone</option>
             <option value="sidechain">Sidechain</option>
             <option value="protein">Protein</option>
             <option value="ligand">Ligand</option>
             <option value="nucleic">Nucleic acids</option>
             <option value="elety">Atom names</option>
             <option value="resid">Residue ID</option>
             <option value="segid">Segment ID</option>
           </param>
           <when value="calpha">
           </when>
           <when value="cbeta">
           </when>
           <when value="backbone">
           </when> 
           <when value="sidechain">
           </when>
           <when value="protein">
           </when>
           <when value="ligand">
           </when>
           <when value="nucleic">
           </when>
          <when value="elety">
            <param name="elety"  type="text" value="CA" label="Atom name"/>
          </when>
          <when value="resid">
            <param name="resid"  type="text" value="BGLC" label="Residue ID"/>
          </when>
          <when value="segid">
            <param name="segid"  type="text" value="SUBS" label="Segment ID"/>
          </when>
        </conditional>
    </inputs>
    <outputs>
        <data format="tabular" name="output" label="PCA raw data"/>
        <data format="png" name="pca_plot" label="PCA plot"/>
        <data format="png" name="pca_cluster" label="PCA Cluster Plot"/>
        <data format="png" name="pc1_rmsf" label="PC1 on RMSF"/>
    </outputs>
    <tests>
        <test>
            <expand macro="tests_inputs"/>
            <param name="method" value="false"/>
            <param name="sele" value="calpha"/> 
            <output name="output">
              <assert_contents>
                <has_n_columns n="4" />
                <has_line_matching expression="1\s+0.047.*\s+0.0374.*\s+0.0436.*" />
              </assert_contents>
            </output>
        </test>
    </tests>
    <help><![CDATA[
.. class:: infomark

**What it does**

Principal component analysis (PCA) can be used to determine the relationship between statistically meaningful conformations (major global motions)
sampled during the trajectory. 

_____


.. class:: infomark

**Input**

       - Input file in PDB format
       - Input file in DCD format

_____


.. class:: infomark

**Output**

       - Image (as PNG) of the PCA plot
       - Image (as PNG) of the PCA clustered plot
       - Image (as PNG) of the first principal component plotted on RMSF
       - Tab-separated file of raw data

    ]]></help>
    <expand macro="citations" />
</tool>