Mercurial > repos > iuc > ampvis2_ordinate

comparison ordinate.xml @ 3:75e025c9bc10 draft

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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/ampvis2 commit 5b6fb9641a1320e13aba367c4e7bc52ae064acc6
author iuc
date Mon, 26 Feb 2024 07:50:05 +0000
parents 8569e8d8b712
children 811df76f4f26
comparison
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2:8569e8d8b712 3:75e025c9bc10
21 <option value="raup">raup</option> 21 <option value="raup">raup</option>
22 <option value="binomial">binomial</option> 22 <option value="binomial">binomial</option>
23 <option value="chao">chao</option> 23 <option value="chao">chao</option>
24 <option value="cao">cao</option> 24 <option value="cao">cao</option>
25 <option value="mahalanobis">mahalanobis</option> 25 <option value="mahalanobis">mahalanobis</option>
26 <option value="clark">Clark</option>
27 <option value="chisq">Chi-square</option>
28 <option value="chord"> Chord</option>
29 <option value="hellinger">Hellinger</option>
30 <option value="aitchison">Aitchison</option>
31 <option value="robust.aitchison">Robust Aitchison </option>
26 </param> 32 </param>
27 </xml> 33 </xml>
28 <!-- default is most often hellinger, but for N/MMDS none is suggested --> 34 <!-- default is most often hellinger, but for N/MMDS none is suggested -->
29 <xml name="transform_macro"> 35 <xml name="transform_macro">
30 <param argument="transform" type="select" label="Transforms the abundances before ordination" help="See details in decostand. Using the hellinger transformation is a good choice when performing PCA/RDA as it will produce a more ecologically meaningful result (read about the double-zero problem in Numerical Ecology). When the Hellinger transformation is used with CA/CCA it will help reducing the impact of low abundant species. When performing nMDS or PCoA (aka mMDS) it is not recommended to also use data transformation as this will obscure the chosen distance measure."> 36 <param argument="transform" type="select" label="Transforms the abundances before ordination" help="See details in decostand. Using the hellinger transformation is a good choice when performing PCA/RDA as it will produce a more ecologically meaningful result (read about the double-zero problem in Numerical Ecology). When the Hellinger transformation is used with CA/CCA it will help reducing the impact of low abundant species. When performing nMDS or PCoA (aka mMDS) it is not recommended to also use data transformation as this will obscure the chosen distance measure.">