| Previous changeset 2:dc2de14881ba (2019-12-05) Next changeset 4:766be978777a (2019-12-18) |
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Commit message:
"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scanpy/ commit 3b41d687ff30583540d055f6995de00530cca81d" |
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modified:
cluster_reduce_dimension.xml macros.xml test-data/pp.highly_variable_genes.krumsiek11-cell_ranger.h5ad |
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added:
test-data/pl.rank_genes_groups_dotplot.rank_genes_groups.krumsiek11.png test-data/pl.rank_genes_groups_heatmap.rank_genes_groups.krumsiek11.png test-data/pl.rank_genes_groups_matrixplot.rank_genes_groups.krumsiek11.png test-data/pl.rank_genes_groups_stacked_violin.rank_genes_groups.krumsiek11.png |
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| diff -r dc2de14881ba -r ac8e59e87ce3 cluster_reduce_dimension.xml --- a/cluster_reduce_dimension.xml Thu Dec 05 07:11:19 2019 -0500 +++ b/cluster_reduce_dimension.xml Thu Dec 12 09:25:42 2019 -0500 |
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| b'@@ -7,7 +7,7 @@\n <param argument="dtype" type="text" value="float32" label="Numpy data type string to which to convert the result" help=""/>\n <conditional name="pca">\n <param argument="chunked" type="select" label="Type of PCA?">\n- <option value="True">Incremental PCA on segments (incremental PCA automatically zero centers and ignores settings of `random_seed` and `svd_solver`)</option>\n+ <option value="True">Incremental PCA on segments (incremental PCA automatically zero centers and ignores settings of \'random_seed\' and \'svd_solver\')</option>\n <option value="False" selected="true">Full PCA</option>\n </param>\n <when value="True">\n@@ -74,7 +74,7 @@\n sc.tl.louvain(\n adata=adata,\n flavor = \'$method.flavor.flavor\',\n- #if $method.flavor.flavor == \'vtraag\' and $method.flavor.resolution\n+ #if $method.flavor.flavor == \'vtraag\'\n resolution=$method.flavor.resolution,\n #end if\n random_state=$method.random_state,\n@@ -185,16 +185,16 @@\n <expand macro="inputs_anndata"/>\n <conditional name="method">\n <param argument="method" type="select" label="Method used for plotting">\n- <option value="tl.louvain">Cluster cells into subgroups, using `tl.louvain`</option>\n- <option value="tl.leiden">Cluster cells into subgroups, using `tl.leiden`</option>\n- <option value="pp.pca">Computes PCA (principal component analysis) coordinates, loadings and variance decomposition, using `pp.pca`</option>\n- <option value="tl.pca">Computes PCA (principal component analysis) coordinates, loadings and variance decomposition, using `tl.pca`</option>\n- <option value="tl.diffmap">Diffusion Maps, using `tl.diffmap`</option>\n- <option value="tl.tsne">t-distributed stochastic neighborhood embedding (tSNE), using `tl.tsne`</option>\n- <option value="tl.umap">Embed the neighborhood graph using UMAP, using `tl.umap`</option>\n- <option value="tl.draw_graph">Force-directed graph drawing, using `tl.draw_graph`</option>\n- <option value="tl.dpt">Infer progression of cells through geodesic distance along the graph, using `tl.dpt`</option>\n- <option value="tl.paga">Generate cellular maps of differentiation manifolds with complex topologies, using `tl.paga`</option>\n+ <option value="tl.louvain">Cluster cells into subgroups, using \'tl.louvain\'</option>\n+ <option value="tl.leiden">Cluster cells into subgroups, using \'tl.leiden\'</option>\n+ <option value="pp.pca">Computes PCA (principal component analysis) coordinates, loadings and variance decomposition, using \'pp.pca\'</option>\n+ <option value="tl.pca">Computes PCA (principal component analysis) coordinates, loadings and variance decomposition, using \'tl.pca\'</option>\n+ <option value="tl.diffmap">Diffusion Maps, using \'tl.diffmap\'</option>\n+ <option value="tl.tsne">t-distributed stochastic neighborhood embedding (tSNE), using \'tl.tsne\'</option>\n+ <option value="tl.umap">Embed the neighborhood graph using UMAP, using \'tl.umap\'</option>\n+ <option value="tl.draw_graph">Force-directed graph drawing, using \'tl.draw_graph\'</option>\n+ <option value="tl.dpt">Infer progression of cells through geodesic distance along the graph, using \'tl.dpt\'</option>\n+ <option value="tl.paga">Generate cellular maps of differentiation manifolds with complex topologies, using \'tl.paga\'</option>\n </param>\n <when value="tl.louvain">\n <conditional name="flavor">\n@@ -203,7 +203,7 @@\n <option value="igraph">igraph</option>\n </param>\n <when value="vtraag">\n- <param argume'..b'nt="init_pos" type="select" label="How to initialize the low dimensional embedding" help="Called \'init\' in the original UMAP">\n <option value="paga">Position from paga</option>\n <option value="spectral" selected="true">Spectral embedding of the graph</option>\n <option value="random">Initial embedding positions at random</option>\n@@ -259,17 +259,17 @@\n <expand macro="param_random_state"/>\n <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)"/>\n <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"/>\n- <param argument="key_ext" type="text" optional="true" value="" label="External key" help="If not set, it appends `layout`"/>\n+ <param argument="key_ext" type="text" optional="true" value="" label="External key" help="If not set, it appends \'layout\'"/>\n </when>\n <when value="tl.dpt">\n <param argument="n_dcs" type="integer" min="0" value="10" label="Number of diffusion components to use" help=""/>\n <param argument="n_branchings" type="integer" min="0" value="0" label="Number of branchings to detect" help=""/>\n- <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` > 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."/>\n+ <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\' > 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."/>\n <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."/>\n </when>\n <when value="tl.paga">\n- <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`)."/>\n- <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."/>\n+ <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\')."/>\n+ <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."/>\n <param argument="model" type="select" label="PAGA connectivity model" help="">\n <option value="v1.2">v1.2</option>\n <option value="v1.0">v1.0</option>\n' |
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| diff -r dc2de14881ba -r ac8e59e87ce3 macros.xml --- a/macros.xml Thu Dec 05 07:11:19 2019 -0500 +++ b/macros.xml Thu Dec 12 09:25:42 2019 -0500 |
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| b'@@ -1,7 +1,7 @@\n <macros>\n <token name="@version@">1.4.4.post1</token>\n <token name="@profile@">19.01</token>\n- <token name="@galaxy_version@"><![CDATA[@version@+galaxy0]]></token>\n+ <token name="@galaxy_version@"><![CDATA[@version@+galaxy1]]></token>\n <xml name="requirements">\n <requirements>\n <requirement type="package" version="@version@">scanpy</requirement>\n@@ -351,10 +351,10 @@\n <option value="gist_ncar">gist_ncar (Miscellaneous)</option>\n </xml>\n <xml name="param_groupby">\n- <param argument="groupby" type="text" value="" optional="true" label="The key of the observation grouping to consider" help="If it is given, the heatmap is ordered by the respective group. It is expected that to be a categorical. If it is not a categorical observation, it would be subdivided into `num_categories`."/>\n+ <param argument="groupby" type="text" value="" optional="true" label="The key of the observation grouping to consider" help="If it is given, the plot is ordered by the respective group. It is expected that to be a categorical. If it is not a categorical observation, it would be subdivided into \'num_categories\'."/>\n </xml>\n <xml name="param_use_raw">\n- <param argument="use_raw" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Use `raw` attribute of input if present" help=""/>\n+ <param argument="use_raw" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Use \'raw\' attribute of input if present" help=""/>\n </xml>\n <xml name="param_log">\n <param argument="log" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Use the log of the values?"/>\n@@ -378,12 +378,12 @@\n <xml name="pl_var_names">\n <conditional name="var_names">\n <param name="type" type="select" label="Variables to plot (columns of the heatmaps)" >\n- <option value="all">All variables in `adata.var_names`</option>\n- <option value="custom">Subset of variables in `adata.var_names`</option>\n+ <option value="all">All variables in \'adata.var_names\'</option>\n+ <option value="custom">Subset of variables in \'adata.var_names\'</option>\n </param>\n <when value="all"/>\n <when value="custom">\n- <param argument="var_names" type="text" value="" label="List of variables to plot" help="They should be a valid subset of `adata.var_names`, and separated by comma"/>\n+ <param argument="var_names" type="text" value="" label="List of variables to plot" help="They should be a valid subset of \'adata.var_names\', and separated by comma"/>\n </when>\n </conditional>\n </xml>\n@@ -404,27 +404,20 @@\n <param argument="var_group_rotation" type="float" value="" optional="true" label="Label rotation degrees" help="By default, labels larger than 4 characters are rotated 90 degrees"/>\n </xml>\n <xml name="param_layer">\n- <param argument="layer" type="text" value="" label="Name of the AnnData object layer that wants to be plotted" help="By default `adata.raw.X` is plotted. If `use_raw=False` is set, then `adata.X` is plotted. If layer is set to a valid layer name, then the layer is plotted. layer takes precedence over `use_raw`."/>\n+ <param argument="layer" type="text" value="" label="Name of the AnnData object layer that wants to be plotted" help="By default \'adata.raw.X\' is plotted. If \'use_raw=False\' is set, then \'adata.X\' is plotted. If layer is set to a valid layer name, then the layer is plotted. layer takes precedence over \'use_raw\'."/>\n </xml>\n <token name="@CMD_param_plot_inputs@"><![CDATA[\n adata,\n save=\'.$format\',\n show=False,\n ]]></token>\n- <xml name="params_plots">\n+ <xml name="params_inputs">\n <expand macro="pl_var_names"/>\n <expand macro="param_groupby"/>\n- <expand macro="param_log"/>'..b'_pl_heatmap@"><![CDATA[\n+ swap_axes=$method.swap_axes,\n+ show_gene_labels=$method.show_gene_labels,\n+ cmap=\'$method.matplotlib_pyplot_imshow.cmap\',\n+ #if str($method.matplotlib_pyplot_imshow.interpolation) != \'None\'\n+ interpolation=\'$method.matplotlib_pyplot_imshow.interpolation\',\n+ #end if\n+ #if $method.matplotlib_pyplot_imshow.alpha\n+ alpha=$method.matplotlib_pyplot_imshow.alpha,\n+ #end if\n+ #if $method.matplotlib_pyplot_imshow.vmin\n+ vmin=$method.matplotlib_pyplot_imshow.vmin,\n+ #end if\n+ #if $method.matplotlib_pyplot_imshow.vmax\n+ vmax=$method.matplotlib_pyplot_imshow.vmax,\n+ #end if\n+ origin=\'$method.matplotlib_pyplot_imshow.origin\'\n+ ]]>\n+ </token>\n+ <xml name="pl_rank_genes_groups_ext">\n+ <expand macro="param_groups"/>\n+ <expand macro="param_n_genes"/>\n+ <expand macro="param_key"/>\n+ </xml>\n+ <token name="@CMD_pl_rank_genes_groups_ext@"><![CDATA[\n+ @CMD_params_groups@\n+ #if str($method.n_genes) != \'\'\n+ n_genes=$method.n_genes,\n+ #end if\n+ #if str($method.key) != \'\'\n+ key=\'$method.key\',\n+ #end if\n+ ]]>\n+ </token>\n+ <xml name="pl_matrixplot">\n+ <expand macro="param_swap_axes"/>\n+ <section name="matplotlib_pyplot_pcolor" title="Parameters for matplotlib.pyplot.pcolor">\n+ <param argument="cmap" type="select" label="Color palette">\n+ <expand macro="seaborn_color_palette_options"/>\n+ </param>\n+ <param argument="vmin" type="float" value="" optional="true" label="Minimum value to anchor the colormap" help=""/>\n+ <param argument="vmax" type="float" value="" optional="true" label="Maximum value to anchor the colormap" help=""/>\n+ <expand macro="param_matplotlib_pyplot_edgecolors"/>\n+ <expand macro="param_alpha"/>\n+ <param argument="snap" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Snap the mesh to pixel boundaries?" help=""/>\n+ </section>\n+ </xml>\n+ <token name="@CMD_pl_matrixplot@"><![CDATA[\n+ swap_axes=$method.swap_axes,\n+ cmap=\'$method.matplotlib_pyplot_pcolor.cmap\',\n+ #if $method.matplotlib_pyplot_pcolor.vmin\n+ vmin=$method.matplotlib_pyplot_pcolor.vmin,\n+ #end if\n+ #if $method.matplotlib_pyplot_pcolor.vmax\n+ vmax=$method.matplotlib_pyplot_pcolor.vmax,\n+ #end if\n+ edgecolors=\'$method.matplotlib_pyplot_pcolor.edgecolors\',\n+ #if $method.matplotlib_pyplot_pcolor.alpha\n+ alpha=$method.matplotlib_pyplot_pcolor.alpha,\n+ #end if\n+ snap=$method.matplotlib_pyplot_pcolor.snap\n+ ]]>\n+ </token>\n+ <xml name="pl_stacked_violin">\n+ <expand macro="param_swap_axes"/>\n+ <section name="violin_plot" title="Violin plot attributes">\n+ <expand macro="conditional_stripplot"/>\n+ <expand macro="param_scale"/>\n+ </section>\n+ <param argument="row_palette" type="select" label="Colors to use in each of the stacked violin plots">\n+ <option value="muted">muted</option>\n+ <expand macro="seaborn_color_palette_options"/>\n+ </param>\n+ <param argument="standard_scale" type="select" label="Standardize a dimension between 0 and 1" help="Each variable or observation is subtracted by the minimum and divided each by its maximum.">\n+ <option value="None">No standardization</option>\n+ <option value="var">Standardization on variable</option>\n+ <option value="obs">Standardization on observation</option>\n+ </param>\n+ <expand macro="seaborn_violinplot"/>\n+ </xml>\n+ <token name="@CMD_pl_stacked_violin@"><![CDATA[\n+ swap_axes=$method.swap_axes,\n+ @CMD_conditional_stripplot@\n+ scale=\'$method.violin_plot.scale\',\n+ row_palette=\'$method.row_palette\',\n+ #if str($method.standard_scale) != \'None\'\n+ standard_scale=\'$method.standard_scale\',\n+ #end if\n+ @CMD_params_seaborn_violinplot@\n+ ]]>\n+ </token>\n </macros>\n' |
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