comparison cluster_reduce_dimension.xml @ 7:b2df381a6004 draft

"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scanpy/ commit 150c96596b94f9658c8b7c44814c420d38fbee0c"

6:77b91b9bdf52

    <description>with scanpy</description>
    <macros>
        <import>macros.xml</import>
        <xml name="pca_inputs">
            <param argument="n_comps" type="integer" min="0" value="50" label="Number of principal components to compute" help=""/>
            <param argument="dtype" type="text" value="float32" label="Numpy data type string to which to convert the result" help=""/>
            <conditional name="pca">
                <param argument="chunked" type="select" label="Type of PCA?">
                    <option value="True">Incremental PCA on segments (incremental PCA automatically zero centers and ignores settings of 'random_seed' and 'svd_solver')</option>
                    <option value="False" selected="true">Full PCA</option>
                </param>

                            help="Higher resolution means finding more and smaller clusters, which defaults to 1.0. See “Time as a resolution parameter” in Lambiotte et al, 2009"/>
                    </when>
                    <when value="igraph"/>
                </conditional>
                <expand macro="param_random_state"/>
                <param argument="key_added" type="text" value="louvain" optional="true" label="Key under which to add the cluster labels" help=""/>
                <param argument="directed" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Interpret the adjacency matrix as directed graph?"/>
                <expand macro="param_use_weights"/>
            </when>
            <when value="tl.leiden">
                <param argument="resolution" type="float" value="1" label="Coarseness of the clusterin" help="Higher values lead to more clusters"/>
                <expand macro="param_random_state"/>
                <param argument="key_added" type="text" value="leiden" label="Key under which to add the cluster labels" help=""/>
                <expand macro="param_use_weights"/>
                <param argument="n_iterations" type="integer" value="-1" label="How many iterations of the Leiden clustering algorithm to perform." help="Positive values above 2 define the total number of iterations to perform, -1 has the algorithm run until it reaches its optimal clustering."/>
            </when>
            <when value="pp.pca">
                <expand macro="pca_inputs"/>

            </when>
            <when value="tl.draw_graph">
                <expand macro="param_layout"/>
                <expand macro="param_root"/>
                <expand macro="param_random_state"/>
                <param argument="init_pos" type="text" optional="true" value="" label="Precomputed coordinates for initialization" help="It should be a valid 2d observation (e.g. paga)"/>
                <param argument="adjacency" type="data" format="mtx" optional="true" label="Sparse adjacency matrix of the graph" help="If not set, it uses the unstructured annotation (uns) / neighbors / connectivities"/>
                <param argument="key_ext" type="text" optional="true" value="" label="External key" help="If not set, it appends 'layout'"/>
            </when>
            <when value="tl.dpt">
                <param argument="n_dcs" type="integer" min="0" value="10" label="Number of diffusion components to use" help=""/>
                <param argument="n_branchings" type="integer" min="0" value="0" label="Number of branchings to detect" help=""/>
                <param argument="min_group_size" type="float" min="0" value="0.01" label="Min group size" help="During recursive splitting of branches ('dpt groups') for 'n_branchings' &gt; 1, do not consider groups that contain less than 'min_group_size' data points. If a float, 'min_group_size' refers to a fraction of the total number of data points."/>
                <param argument="allow_kendall_tau_shift" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Allow Kendal tau shift?" help="If a very small branch is detected upon splitting, shift away from maximum correlation in Kendall tau criterion of Haghverdi et al (2016) to stabilize the splitting."/>
            </when>
            <when value="tl.paga">
                <param argument="groups" type="text" value="louvain" label="Key for categorical in the input" help="You can pass your predefined groups by choosing any categorical annotation of observations ('adata.obs')."/>
                <param argument="use_rna_velocity" type="boolean" truevalue="False" falsevalue="False" checked="false" label="Use RNA velocity to orient edges in the abstracted graph and estimate transitions?" help="Requires that 'adata.uns' contains a directed single-cell graph with key '['velocyto_transitions']'. This feature might be subject to change in the future."/>
                <param argument="model" type="select" label="PAGA connectivity model" help="">
                    <option value="v1.2">v1.2</option>
                    <option value="v1.0">v1.0</option>
                </param>

7:b2df381a6004

    <description>with scanpy</description>
    <macros>
        <import>macros.xml</import>
        <xml name="pca_inputs">
            <param argument="n_comps" type="integer" min="0" value="50" label="Number of principal components to compute" help=""/>
            <param argument="dtype" type="text" value="float32" label="Numpy data type string to which to convert the result" help="">
                <expand macro="sanitize_query" />
            </param>
            <conditional name="pca">
                <param argument="chunked" type="select" label="Type of PCA?">
                    <option value="True">Incremental PCA on segments (incremental PCA automatically zero centers and ignores settings of 'random_seed' and 'svd_solver')</option>
                    <option value="False" selected="true">Full PCA</option>
                </param>

                            help="Higher resolution means finding more and smaller clusters, which defaults to 1.0. See “Time as a resolution parameter” in Lambiotte et al, 2009"/>
                    </when>
                    <when value="igraph"/>
                </conditional>
                <expand macro="param_random_state"/>
                <param argument="key_added" type="text" value="louvain" optional="true" label="Key under which to add the cluster labels" help="">
                    <expand macro="sanitize_query" />
                </param>
                <param argument="directed" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Interpret the adjacency matrix as directed graph?"/>
                <expand macro="param_use_weights"/>
            </when>
            <when value="tl.leiden">
                <param argument="resolution" type="float" value="1" label="Coarseness of the clusterin" help="Higher values lead to more clusters"/>
                <expand macro="param_random_state"/>
                <param argument="key_added" type="text" value="leiden" label="Key under which to add the cluster labels" help="">
                    <expand macro="sanitize_query" />
                </param>
                <expand macro="param_use_weights"/>
                <param argument="n_iterations" type="integer" value="-1" label="How many iterations of the Leiden clustering algorithm to perform." help="Positive values above 2 define the total number of iterations to perform, -1 has the algorithm run until it reaches its optimal clustering."/>
            </when>
            <when value="pp.pca">
                <expand macro="pca_inputs"/>

            </when>
            <when value="tl.draw_graph">
                <expand macro="param_layout"/>
                <expand macro="param_root"/>
                <expand macro="param_random_state"/>
                <param argument="init_pos" type="text" optional="true" value="" label="Precomputed coordinates for initialization" help="It should be a valid 2d observation (e.g. paga)">
                    <expand macro="sanitize_query" />
                </param>
                <param argument="adjacency" type="data" format="mtx" optional="true" label="Sparse adjacency matrix of the graph" help="If not set, it uses the unstructured annotation (uns) / neighbors / connectivities"/>
                <param argument="key_ext" type="text" optional="true" value="" label="External key" help="If not set, it appends 'layout'">
                    <expand macro="sanitize_query" />
                </param>
            </when>
            <when value="tl.dpt">
                <param argument="n_dcs" type="integer" min="0" value="10" label="Number of diffusion components to use" help=""/>
                <param argument="n_branchings" type="integer" min="0" value="0" label="Number of branchings to detect" help=""/>
                <param argument="min_group_size" type="float" min="0" value="0.01" label="Min group size" help="During recursive splitting of branches ('dpt groups') for 'n_branchings' &gt; 1, do not consider groups that contain less than 'min_group_size' data points. If a float, 'min_group_size' refers to a fraction of the total number of data points."/>
                <param argument="allow_kendall_tau_shift" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Allow Kendal tau shift?" help="If a very small branch is detected upon splitting, shift away from maximum correlation in Kendall tau criterion of Haghverdi et al (2016) to stabilize the splitting."/>
            </when>
            <when value="tl.paga">
                <param argument="groups" type="text" value="louvain" label="Key for categorical in the input" help="You can pass your predefined groups by choosing any categorical annotation of observations ('adata.obs').">
                    <expand macro="sanitize_query" />
                </param>
                <param argument="use_rna_velocity" type="boolean" truevalue="False" falsevalue="False" checked="false" label="Use RNA velocity to orient edges in the abstracted graph and estimate transitions?" help="Requires that 'adata.uns' contains a directed single-cell graph with key '['velocyto_transitions']'. This feature might be subject to change in the future."/>
                <param argument="model" type="select" label="PAGA connectivity model" help="">
                    <option value="v1.2">v1.2</option>
                    <option value="v1.0">v1.0</option>
                </param>