annotate Nb_cluster.xml @ 4:cf7aefee9977 draft default tip

planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/Ecoregionalization_workflow commit c41939f1cdc03331ec021d47495576a6b0c5fd14

<tool id="ecoregion_cluster_estimate" name="ClusterEstimate" version="0.1.0+galaxy0" profile="22.05">
    <description>Find an optimal number of cluster with SIH index</description>
    <requirements>
       <requirement type="package" version="4.2.3">r-base</requirement>
       <requirement type="package" version="2.1.4">r-cluster</requirement>
       <requirement type="package" version="1.1.1">r-dplyr</requirement>
       <requirement type="package" version="2.0.0">r-tidyverse</requirement>
    </requirements>
    <command detect_errors="exit_code"><![CDATA[
        Rscript
         '$__tool_directory__/nb_clust_G.R'
         '$envfile'
         '$taxafile'
         '$predictionfile'
         '$max_k'
         '$metric'
         '$sample'
         '$output1'
         '$output2'
         '$output3'
    ]]>
    </command>
    <inputs>
      <param name="envfile" type="data" format="tabular" label="Environment file (tabular format only)" help="See example below"/>
      <param name="taxafile" type="data" format="txt" label="Taxa selected file (File 'List of taxa' from TaxaSeeker tool)"/>
      <param name="predictionfile" type="data" format="tabular" multiple="true" label="Prediction files"/>
      <param name="max_k" type="integer" value="2" min="1" label="Number of Cluster to test"/>
      <param name="metric" type="select" label="What metric to use to calculate dissimilarities between observations ?">
             <option value="manhattan">manhattan</option>
             <option value="euclidean">euclidean</option>
             <option value="jaccard">jaccard</option>
      </param>
      <param name="sample" type="integer" label="The number of samples to be drawn from the dataset" min="5" value="10"/>
    </inputs>
    <outputs>
      <data name="output1" from_work_dir="Indices_SIH.png" format="png" label="SIH index plot"/>
      <data name="output2" from_work_dir="data_to_clus.tsv" format="tabular" label="Data to cluster"/>
      <data name="output3" from_work_dir="data_bio.tsv" format="tabular" label="Data.bio table "/>
    </outputs>
    <tests>
        <test>
            <param name="envfile" value="ceamarc_env.tsv"/>
            <param name="taxafile" value="List_of_taxa.txt"/>
            <param name="predictionfile" value="1_brts_pred_ceamarc.tsv"/>
            <param name='max_k' value="2"/>
            <param name='metric' value="manhattan"/>
            <param name='sample' value="10"/>
            <output name='output1'>
                <assert_contents>
            	    <has_size value="4297" delta="500"/>
            	</assert_contents>
            </output>
            <output name='output2' value="Data_to_cluster.tsv"/>
            <output name='output3' value="Data.bio_table.tsv"/>
        </test>
    </tests>
    <help><![CDATA[
==================    
**What it does ?**
==================

The tool enables the determination of the optimal number of clusters for partition-based clustering, along with generating files used in the subsequent ecoregionalization workflow.

===================         
**How to use it ?**
===================

The tool takes three inputs files: a file containing the environmental parameter values for each environment layer pixel (latitude-longitude), a file containing the list of selected taxa from previous step of the workflow and the file containing the BRT predictions. See example below.

Then there are few parameters : 

- the maximum number of clusters to be tested with a minimum of two clusters
 
- the metric used to calculate the dissimilarities between the observations: Manhattan, Euclidean and Jaccard  

- the sample size that will be used to perform clustering. Indeed, the clara function is used to clustering large data using a representative sample rather than the entire data set. This will speed up the clustering process and make the calculation more efficient. A fairly high value representative of the data is recommended. It is important to note that using too small a sample may result in loss of information compared to using the entire data set.

The tool will produce three outputs. The first two are files that will be used in the rest of the workflow: a file containing four pieces of information, latitude, longitude, presence prediction and corresponding taxon, and a file containing the data to be partitioned. The third output corresponds to the main information of the tool, a graph presenting the value of the SIH index according to the number of clusters. The silhouette index provides a measure of the separation between clusters and the compactness within each cluster. The silhouette index ranges from -1 to 1. Values close to 1 indicate that objects are well grouped and separated from other clusters, while values close to -1 indicate that objects are poorly grouped and may be closer to other clusters. A value close to 0 indicates a situation where objects are located at the border between two neighboring clusters.

**Example of the environemental file :**

+------+------+---------+------+--------------+-----+
| long | lat  |  Carbo  | Grav |  Maxbearing  | ... |
+------+------+---------+------+--------------+-----+
|139.22|-65.57|   0.88  |28.59 |     3.67     | ... |
+------+------+---------+------+--------------+-----+
|139.22|-65.57|   0.88  |28.61 |     3.64     | ... |
+------+------+---------+------+--------------+-----+
| ...  | ...  |   ...   | ...  |     ...      | ... |
+------+------+---------+------+--------------+-----+

**Example of the Brt prediction file :**

+-----------+----------+-----------------------+-------------+
|    lat    |   long   |   Prediction.index    |     spe     |
+-----------+----------+-----------------------+-------------+
|  -65.57   |  139.22  |   0.122438487221909   |  Acarnidae  |
+-----------+----------+-----------------------+-------------+
|  -65.57   |  139.32  |   0.119154535627801   |  Acarnidae  |
+-----------+----------+-----------------------+-------------+
|   ...     |   ...    |         ...           |     ...     |
+-----------+----------+-----------------------+-------------+

    ]]>
    </help>
    <citations>
       <citation type="doi">10.32614/CRAN.package.dplyr</citation>
       <citation type="doi">10.32614/CRAN.package.cluster</citation>
       <citation type="doi">10.32614/CRAN.package.tidyverse</citation>
   </citations>
</tool>