Mercurial > repos > ebi-gxa > scanpy_compute_graph
view scanpy-neighbours.xml @ 20:c42c2b540ced draft
"planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/tree/develop/tools/tertiary-analysis/scanpy commit ebe77c8718ec65277f4dc0d71fa5f4c5677df62d-dirty"
author | ebi-gxa |
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date | Wed, 05 May 2021 12:11:28 +0000 |
parents | 1dc0ea7a7e62 |
children | 5ec3b715809c |
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<?xml version="1.0" encoding="utf-8"?> <tool id="scanpy_compute_graph" name="Scanpy ComputeGraph" version="@TOOL_VERSION@+galaxy0" profile="@PROFILE@"> <description>to derive kNN graph</description> <macros> <import>scanpy_macros2.xml</import> </macros> <expand macro="requirements"/> <command detect_errors="exit_code"><![CDATA[ ln -s '${input_obj_file}' input.h5 && PYTHONIOENCODING=utf-8 scanpy-neighbors #if $settings.default == "false" #if $settings.n_neighbors_file #set f = open($settings.n_neighbors_file.__str__) #set n_neighbors = f.read().strip() #silent f.close #elif $settings.n_neighbors #set n_neighbors = $settings.n_neighbors.__str__.strip() #end if #if $n_neighbors --n-neighbors $n_neighbors #end if #if $settings.key_added #set key_added = $settings.key_added #if $n_neighbors #set key_added = $key_added.replace('N_NEIGHBORS', $n_neighbors.__str__) #end if --key-added '${key_added}' #end if --method '${settings.method}' --metric '${settings.metric}' --random-state '${settings.random_seed}' #if $settings.use_rep != "auto" --use-rep '${settings.use_rep}' #end if #if $settings.n_pcs --n-pcs '${settings.n_pcs}' #end if ${settings.knn} #end if @INPUT_OPTS@ @OUTPUT_OPTS@ ]]></command> <inputs> <expand macro="input_object_params"/> <expand macro="output_object_params"/> <conditional name="settings"> <param name="default" type="boolean" checked="true" label="Use programme defaults"/> <when value="true"/> <when value="false"> <param name="key_added" argument="--key-added" type="text" optional="true" label="Key added" help="If not specified, the neighbors data is stored in .uns[‘neighbors’], distances and connectivities are stored in .obsp[‘distances’] and .obsp[‘connectivities’] respectively. If specified, the neighbors data is added to .uns[key_added], distances are stored in .obsp[key_added+’_distances’] and connectivities in .obsp[key_added+’_connectivities’]." value='' /> <param name="n_neighbors" argument="--n-neighbors" type="integer" value="15" label="Maximum number of neighbors used"/> <param name="n_neighbors_file" argument="--n-neighbors" type="data" format="txt,tsv" optional="true" label="File with n_neighbours, use with parameter iterator. Overrides the n_neighbors setting"/> <param name="use_rep" type="select" label="Use the indicated representation"> <option value="X_pca" selected="true">X_pca, use PCs</option> <option value="X">X, use normalised expression values</option> </param> <param name="n_pcs" argument="--n-pcs" type="integer" value="50" optional="true" label="Number of PCs to use"/> <param name="knn" argument="--knn" type="boolean" truevalue="" falsevalue="--no-knn" checked="true" label="Use hard threshold to restrict neighbourhood size (otherwise use a Gaussian kernel to down weight distant neighbors)"/> <param name="method" argument="--method" type="select" label="Method for calculating connectivity"> <option value="umap" selected="true">UMAP</option> <option value="gauss">Gaussian</option> <option value="rapids">RAPIDS</option> </param> <param name="metric" argument="--metric" type="select" label="A known metric’s name"> <option value="euclidean" selected="true">Euclidean</option> <option value="cityblock">cityblock</option> <option value="cosine">cosine</option> <option value="l1">l1</option> <option value="l2">l2</option> <option value="manhattan">manhattan</option> <option value="braycurtis">braycurtis</option> <option value="canberra">canberra</option> <option value="chebyshev">chebyshev</option> <option value="correlation">correlation</option> <option value="dice">dice</option> <option value="hamming">hamming</option> <option value="jaccard">jaccard</option> <option value="kulsinski">kulsinski</option> <option value="mahalanobis">mahalanobis</option> <option value="minkowski">minkowski</option> <option value="rogerstanimoto">rogerstanimoto</option> <option value="russelrao">russelrao</option> <option value="seuclidan">seuclidian</option> <option value="sokalmichener">sokalmichener</option> <option value="sokalsneath">sokalsneath</option> <option value="sqeuclidean">sqeuclidean</option> <option value="yule">yule</option> </param> <param name="random_seed" argument="--random-seed" type="integer" value="0" label="Seed for random number generator"/> </when> </conditional> </inputs> <outputs> <expand macro="output_data_obj" description="Graph object"/> </outputs> <tests> <test> <param name="input_obj_file" value="run_pca.h5"/> <param name="input_format" value="anndata"/> <param name="output_format" value="anndata"/> <param name="default" value="false"/> <param name="n_neighbors_file" value="n_neighbors.txt"/> <param name="n_pcs" value="50"/> <param name="knn" value="true"/> <param name="random_seed" value="0"/> <param name="method" value="umap"/> <output name="output_h5" file="compute_graph.h5" ftype="h5" compare="sim_size"/> </test> <test> <param name="input_obj_file" value="run_pca.h5"/> <param name="input_format" value="anndata"/> <param name="output_format" value="anndata"/> <param name="default" value="false"/> <param name="n_neighbors" value="15"/> <param name="n_pcs" value="50"/> <param name="knn" value="true"/> <param name="random_seed" value="0"/> <param name="method" value="umap"/> <output name="output_h5" file="compute_graph.h5" ftype="h5" compare="sim_size"/> </test> </tests> <help><![CDATA[ ============================================================= Compute a neighborhood graph of observations (`pp.neighbors`) ============================================================= The neighbor search efficiency of this heavily relies on UMAP (McInnes et al, 2018), which also provides a method for estimating connectivities of data points - the connectivity of the manifold (`method=='umap'`). If `method=='diffmap'`, connectivities are computed according to Coifman et al (2005), in the adaption of Haghverdi et al (2016). @HELP@ @VERSION_HISTORY@ ]]></help> <expand macro="citations"/> </tool>