Mercurial > repos > ecology > ecoregion_cluster_estimate
view Nb_cluster.xml @ 0:0f6542d0986e draft
planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/Ecoregionalization_workflow commit 2a2ae892fa2dbc1eff9c6a59c3ad8f3c27c1c78d
author | ecology |
---|---|
date | Wed, 18 Oct 2023 09:59:06 +0000 |
parents | |
children | e94a25eed489 |
line wrap: on
line source
<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="txt,csv,tabular" label="Environment file"/> <param name="taxafile" type="data" format="txt" label="Taxa selected file (List of taxa from TaxaSeeker tool)"/> <param name="predictionfile" type="data" format="txt" 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="tsv" label="Data to cluster"/> <data name="output3" from_work_dir="data_bio.tsv" format="tsv" label="Data.bio table "/> </outputs> <tests> <test> <param name="envfile" value="ceamarc_env.csv"/> <param name="taxafile" value="List_of_taxa.txt"/> <param name="predictionfile" value="1_brts_pred_ceamarc.txt"/> <param name='max_k' value="2"/> <param name='metric' value="manhattan"/> <param name='sample' value="10"/> <output name='output1' value="SIH_index_plot.png"/> <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 HIS 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> </tool>