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author | goeckslab |
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date | Mon, 29 Aug 2022 23:55:43 +0000 |
parents | 42e6c251bfd0 |
children | d19c068c2490 |
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<tool id="scimap_spatial" name="Spatial Analysis Tools" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@PROFILE@"> <description>from Scimap</description> <macros> <import>main_macros.xml</import> </macros> <expand macro="scimap_requirements"/> <expand macro="macro_stdio" /> <version_command>echo "@VERSION@"</version_command> <command> <![CDATA[ python '$__tool_directory__/scimap_spatial.py' --inputs '$inputs' --anndata '$anndata' --output '$output' ]]> </command> <configfiles> <inputs name="inputs" /> </configfiles> <inputs> <param name="anndata" type="data" format="h5ad" label="Select the input anndata" /> <conditional name="analyses"> <param name="selected_tool" type="select" label="Select an analysis"> <option value="cluster">Cluster</option> <option value="spatial_aggregate">Spatial Aggregate -- find regions of aggregration of similar cells</option> <option value="spatial_count" selected="true">Spatial Count -- compute a neighbourhood matrix using any categorical variables (e.g. cell-types)</option> <option value="spatial_distance">Spatial Distance -- calculate the average shortest between phenotypes or clusters of interest</option> <option value="spatial_expression">Spatial Expression -- o compute a neighbourhood weighted matrix based on the expression values</option> <option value="spatial_interaction">Spatial Interaction -- computes how likely celltypes are found next to each another compared to random background</option> <option value="spatial_lda">Spatial LDA -- compute a neighbourhood matrix using any categorical variable and then perform Latent Dirichlet Allocation (LDA) modelling</option> <option value="spatial_pscore">Spatial pscore -- a scoring system to evaluate user defined proximity between cell types</option> </param> <when value="cluster"> <param name="method" type="select" label="Select the clustering method"> <option value="kmeans" selected="true">kmeans</option> <option value="phenograph">phenograph</option> <option value="leiden">leiden</option> <option value="parc">parc</option> </param> <section name="options" title="Advanced Options" expanded="false"> <param argument="subset_genes" type="text" value="" optional="true" label="Type in a list of genes that should be included for the purpose of clustering" help="Optional. Comma delimited. By default the algorithm uses all genes in the dataset." /> <param argument="sub_cluster" type="boolean" checked="false" optional="true" label="Whether to do sub-clustering on existing clustering or phenotyping " /> <param argument="sub_cluster_column" type="text" value="phenotype" optional="true" label="Type in the name of a column to be sub-clustered" help="This is only required when sub_cluster is set to True." /> <param argument="sub_cluster_group" type="text" value="" optional="true" label="Type in a list of group names within the sub-cluster column" help="Optional. Comma delimited. By default the program will sub-cluster all groups within column passed through the argument sub_cluster_column." /> <param argument="parc_small_pop" type="integer" value="50" optional="true" label="Smallest cluster population to be considered a community in PARC clustering" /> <param argument="parc_too_big_factor" type="float" value="0.4" optional="true" label="If a cluster exceeds this share of the entire cell population, then the PARC will be run on the large cluster" /> <param argument="k" type="integer" value="10" optional="true" label="Number of clusters to return when using K-Means clustering" /> <param argument="n_pcs" type="integer" value="" optional="true" label="Number of PC's to be used in leiden clustering" help="By default it uses all PC's" /> <param argument="resolution" type="float" value="1" optional="true" label="A parameter value controlling the coarseness of the clustering" help="Higher values lead to more clusters." /> <param argument="phenograph_clustering_metric" type="select" label="Distance metric to define nearest neighbors"> <option value="euclidean" selected="true">euclidean</option> <option value="cityblock">cityblock</option> <option value="cosine">cosine</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="mahalanobis">mahalanobis</option> <option value="minkowski">minkowski</option> <option value="rogerstanimoto">rogerstanimoto</option> <option value="russellrao">russellrao</option> <option value="seuclidean">seuclidean</option> <option value="sokalmichener">sokalmichener</option> <option value="sokalsneath">sokalsneath</option> <option value="sqeuclidean">sqeuclidean</option> <option value="yule">yule</option> </param> <param argument="nearest_neighbors" type="integer" value="30" optional="true" label="Number of nearest neighbors to use in first step of graph construction" help="This parameter is used both in leiden and phenograph clustering." /> <param argument="use_raw" type="boolean" checked="true" optional="true" label="Whether to use raw data for clustering" help=" If False, normalized/scaled data within adata.X will be used." /> <!-- <param argument="log" type="boolean" checked="true" optional="true" label="Whether to log the raw data" help="Set use_raw = True for this to take effect." /> --> <param argument="random_state" type="integer" value="0" optional="true" help="Used to change the initialization of the optimization." /> <param argument="collapse_labels" type="boolean" checked="false" optional="true" help="While sub clustering only a few phenotypes/clusters, this argument helps to group all the other phenotypes/clusters into a single category- Helps in visualisation." /> <param argument="label" type="text" value="" optional="true" label="Column name for the returned data" help="Stored in adata.obs. The default is adata.obs [method used]." /> <!-- <param argument="output_dir"> --> </section> </when> <when value="spatial_aggregate"> <expand macro="scimap_spatial_options" label="spatial_aggregate"> <param argument="phenotype" type="text" value="phenotype" optional="flase" label="Column name of the column containing the phenotype information" /> <param argument="purity" type="integer" value="60" min="1" max="100" label="Percent purity of neighbouring cells" help="e.g. if 60 is chosen, every neighbourhood is tested such that if a particular phenotype makes up greater than 60% of the total population it is annotated to be an aggregate of that particular phenotype." /> <param argument="method" type="select" label="Select the method"> <option value="radius" selected="true">radius</option> <option value="knn">knn</option> </param> <param argument="radius" type="integer" value="30" optional="true" label="The radius used to define a local neighbhourhood" /> <param argument="knn" type="integer" value="10" optional="true" label="Number of cells considered for defining the local neighbhourhood" /> </expand> </when> <when value="spatial_count"> <expand macro="scimap_spatial_options" label="spatial_count"> <param argument="phenotype" type="text" value="phenotype" optional="flase" label="Column name of the column containing the phenotype information" /> <param argument="method" type="select" label="Select the method"> <option value="radius" selected="true">radius</option> <option value="knn">knn</option> </param> <param argument="radius" type="integer" value="30" optional="true" label="The radius used to define a local neighbhourhood" /> <param argument="knn" type="integer" value="10" optional="true" label="Number of cells considered for defining the local neighbhourhood" /> </expand> </when> <when value="spatial_distance"> <expand macro="scimap_spatial_options"> <param argument="phenotype" type="text" value="phenotype" optional="flase" label="Column name of the column containing the phenotype information" /> </expand> </when> <when value="spatial_expression"> <expand macro="scimap_spatial_options" label="spatial_expression"> <param argument="method" type="select" label="Select the method"> <option value="radius" selected="true">radius</option> <option value="knn">knn</option> </param> <param argument="radius" type="integer" value="30" optional="true" label="The radius used to define a local neighbhourhood" /> <param argument="knn" type="integer" value="10" optional="true" label="Number of cells considered for defining the local neighbhourhood" /> <param argument="use_raw" type="boolean" checked="true" optional="true" label="Whether to use raw data for clustering" help=" If False, normalized/scaled data within adata.X will be used." /> <!-- <param argument="log" type="boolean" checked="true" optional="true" label="Whether to log the raw data" help="Set use_raw = True for this to take effect." /> --> </expand> </when> <when value="spatial_interaction"> <expand macro="scimap_spatial_options" label="spatial_interaction"> <param argument="phenotype" type="text" value="phenotype" optional="flase" label="Column name of the column containing the phenotype information" /> <param argument="method" type="select" label="Select the method"> <option value="radius" selected="true">radius</option> <option value="knn">knn</option> </param> <param argument="radius" type="integer" value="30" optional="true" label="The radius used to define a local neighbhourhood" /> <param argument="knn" type="integer" value="10" optional="true" label="Number of cells considered for defining the local neighbhourhood" /> <param argument="permutation" type="integer" value="1000" optional="true" label="The number of permutations to be performed for calculating the P-Value" /> <param argument="pval_method" type="select" label="Select a method to calculate the P-values"> <option value="zscore" selected="true">zscore</option> <option value="histocat">histocat</option> </param> </expand> </when> <when value="spatial_lda"> <expand macro="scimap_spatial_options" label="spatial_lda"> <param argument="phenotype" type="text" value="phenotype" optional="flase" label="Column name of the column containing the phenotype information" /> <param argument="method" type="select" label="Select the method"> <option value="radius" selected="true">radius</option> <option value="knn">knn</option> </param> <param argument="radius" type="integer" value="30" optional="true" label="The radius used to define a local neighbhourhood" /> <param argument="knn" type="integer" value="10" optional="true" label="Number of cells considered for defining the local neighbhourhood" /> <param argument="num_motifs" type="integer" value="10" optional="true" label="The number of requested latent motifs to be extracted from the training corpus" /> <param argument="random_state" type="integer" value="0" optional="true" label="The seed number for random state" /> </expand> </when> <when value="spatial_pscore"> <expand macro="scimap_spatial_options" label="spatial_pscore"> <param argument="proximity" type="text" value="" optional="false" label="Type in the list of cell-types for which the proximity score needs to calculated" help="Comma delimited. e.g.: CellType-A,CellType-B." /> <param argument="score_by" type="text" value="imageid" optional="true" label="Column name containing region's of interest for score comparison" help="Optional. By default the score is calculated across the entire image." /> <param argument="phenotype" type="text" value="phenotype" optional="flase" label="Column name of the column containing the phenotype information" /> <param argument="method" type="select" label="Select the method"> <option value="radius" selected="true">radius</option> <option value="knn">knn</option> </param> <param argument="radius" type="integer" value="20" optional="true" label="The radius used to define a local neighbhourhood" /> <param argument="knn" type="integer" value="3" optional="true" label="Number of cells considered for defining the local neighbhourhood" /> </expand> </when> </conditional> </inputs> <outputs> <data format="h5ad" name="output" label="Scimap.tools.${analyses.selected_tool} on ${on_string}" /> </outputs> <tests> <test> <param name="anndata" value="imc.h5ad" /> <conditional name="analyses"> <param name="selected_tool" value="cluster" /> <param name="method" value="kmeans" /> </conditional> <output name="output"> <assert_contents> <has_h5_keys keys="obs/kmeans" /> </assert_contents> </output> </test> <test> <param name="anndata" value="tutorial_data_pheno.h5ad" /> <conditional name="analyses"> <param name="selected_tool" value="spatial_aggregate" /> </conditional> <output name="output"> <assert_contents> <has_h5_keys keys="obs/spatial_aggregate" /> </assert_contents> </output> </test> </tests> <help> <![CDATA[ **What it does** This tool does various single cell spatial analyses with Scimap. **Input** AnnData. **Output** Anndata with a corresponding key added. ]]> </help> <citations> </citations> </tool>