| Previous changeset 2:7d22964a8639 (2019-12-05) Next changeset 4:9d1997b08ed6 (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:
inspect.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 7d22964a8639 -r cc0deb593fc8 inspect.xml --- a/inspect.xml Thu Dec 05 07:13:18 2019 -0500 +++ b/inspect.xml Thu Dec 12 09:27:38 2019 -0500 |
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| b'@@ -135,7 +135,6 @@\n sc.tl.rank_genes_groups(\n adata=adata,\n groupby=\'$method.groupby\',\n- use_raw=$method.use_raw,\n #if str($method.groups) != \'\'\n #set $group=[x.strip() for x in str($method.groups).split(\',\')]\n groups=$group,\n@@ -199,7 +198,7 @@\n tol=$method.tl_rank_genes_groups_method.tol,\n C=$method.tl_rank_genes_groups_method.c,\n #end if\n- only_positive=$method.only_positive)\n+ use_raw=$method.use_raw)\n \n #else if $method.method == "tl.marker_gene_overlap"\n reference_markers = {}\n@@ -256,30 +255,30 @@\n <expand macro="inputs_anndata"/>\n <conditional name="method">\n <param argument="method" type="select" label="Method used for inspecting">\n- <option value="pp.calculate_qc_metrics">Calculate quality control metrics, using `pp.calculate_qc_metrics`</option>\n- <option value="pp.neighbors">Compute a neighborhood graph of observations, using `pp.neighbors`</option>\n- <option value="tl.score_genes">Score a set of genes, using `tl.score_genes`</option>\n- <option value="tl.score_genes_cell_cycle">Score cell cycle genes, using `tl.score_genes_cell_cycle`</option>\n- <option value="tl.rank_genes_groups">Rank genes for characterizing groups, using `tl.rank_genes_groups`</option>\n- <!--<option value="tl.marker_gene_overlap">Calculate an overlap score between data-deriven marker genes and provided markers, using `tl.marker_gene_overlap`</option>-->\n- <option value="pp.log1p">Logarithmize the data matrix, using `pp.log1p`</option>\n- <option value="pp.scale">Scale data to unit variance and zero mean, using `pp.scale`</option>\n- <option value="pp.sqrt">Square root the data matrix, using `pp.sqrt`</option>\n+ <option value="pp.calculate_qc_metrics">Calculate quality control metrics, using \'pp.calculate_qc_metrics\'</option>\n+ <option value="pp.neighbors">Compute a neighborhood graph of observations, using \'pp.neighbors\'</option>\n+ <option value="tl.score_genes">Score a set of genes, using \'tl.score_genes\'</option>\n+ <option value="tl.score_genes_cell_cycle">Score cell cycle genes, using \'tl.score_genes_cell_cycle\'</option>\n+ <option value="tl.rank_genes_groups">Rank genes for characterizing groups, using \'tl.rank_genes_groups\'</option>\n+ <!--<option value="tl.marker_gene_overlap">Calculate an overlap score between data-deriven marker genes and provided markers, using \'tl.marker_gene_overlap\'</option>-->\n+ <option value="pp.log1p">Logarithmize the data matrix, using \'pp.log1p\'</option>\n+ <option value="pp.scale">Scale data to unit variance and zero mean, using \'pp.scale\'</option>\n+ <option value="pp.sqrt">Square root the data matrix, using \'pp.sqrt\'</option>\n </param>\n <when value="pp.calculate_qc_metrics">\n <param argument="expr_type" type="text" value="counts" label="Name of kind of values in X"/>\n <param argument="var_type" type="text" value="genes" label="The kind of thing the variables are"/>\n- <param argument="qc_vars" type="text" value="" label="Keys for boolean columns of `.var` which identify variables you could want to control for" \n+ <param argument="qc_vars" type="text" value="" label="Keys for boolean columns of \'.var\' which identify variables you could want to control for" \n help="Keys separated by a comma"/>\n <param argument="percent_top" type="text" value="" label="Proportions of top genes to cover" \n- help=" Values (integers) are considered 1-indexed, `50` finds cumulative proportion to the 50th most expressed genes. Values separated by a comma. \n+ help=" Values (integers) are considered 1-indexed, \'50\' finds cumulative proportion to the '..b'>\n <assert_stdout>\n <has_text_matching expression="sc.tl.rank_genes_groups"/>\n@@ -608,7 +604,6 @@\n <has_text_matching expression="n_genes=100"/>\n <has_text_matching expression="method=\'t-test_overestim_var\'"/>\n <has_text_matching expression="corr_method=\'benjamini-hochberg\'"/>\n- <has_text_matching expression="only_positive=True"/>\n </assert_stdout>\n <output name="anndata_out" file="tl.rank_genes_groups.krumsiek11.h5ad" ftype="h5ad" compare="sim_size"/>\n </test>\n@@ -634,7 +629,6 @@\n <param name="tol" value="1e-4"/>\n <param name="c" value="1.0"/>\n </conditional>\n- <param name="only_positive" value="true"/>\n </conditional>\n <assert_stdout>\n <has_text_matching expression="sc.tl.rank_genes_groups"/>\n@@ -650,7 +644,6 @@\n <has_text_matching expression="multi_class=\'auto\'"/>\n <has_text_matching expression="tol=0.0001"/>\n <has_text_matching expression="C=1.0"/>\n- <has_text_matching expression="only_positive=True"/>\n </assert_stdout>\n <output name="anndata_out" file="tl.rank_genes_groups.newton-cg.pbmc68k_reduced.h5ad" ftype="h5ad" compare="sim_size">\n <assert_contents>\n@@ -686,7 +679,6 @@\n <param name="tol" value="1e-4"/>\n <param name="c" value="1.0"/>\n </conditional>\n- <param name="only_positive" value="true"/>\n </conditional>\n <assert_stdout>\n <has_text_matching expression="sc.tl.rank_genes_groups"/>\n@@ -702,7 +694,6 @@\n <has_text_matching expression="intercept_scaling=1.0"/>\n <has_text_matching expression="tol=0.0001"/>\n <has_text_matching expression="C=1.0"/>\n- <has_text_matching expression="only_positive=True"/>\n </assert_stdout>\n <output name="anndata_out" file="tl.rank_genes_groups.liblinear.krumsiek11.h5ad" ftype="h5ad" compare="sim_size">\n <assert_contents>\n@@ -797,18 +788,18 @@\n Calculates a number of qc metrics for an AnnData object, largely based on calculateQCMetrics from scater. \n Currently is most efficient on a sparse CSR or dense matrix.\n \n-It updates the observation level metrics:\n+It updates the observation level metrics with\n \n - total_{var_type}_by_{expr_type} (e.g. "total_genes_by_counts", number of genes with positive counts in a cell)\n - total_{expr_type} (e.g. "total_counts", total number of counts for a cell)\n-- pct_{expr_type}_in_top_{n}_{var_type} (e.g. "pct_counts_in_top_50_genes", cumulative percentage of counts for 50 most expressed genes in a cell)\n-- total_{expr_type}_{qc_var} (e.g. "total_counts_mito", total number of counts for variabes in qc_vars )\n-- pct_{expr_type}_{qc_var} (e.g. "pct_counts_mito", proportion of total counts for a cell which are mitochondrial)\n+- pct_{expr_type}_in_top_{n}_{var_type} - for n in percent_top (e.g. "pct_counts_in_top_50_genes", cumulative percentage of counts for 50 most expressed genes in a cell)\n+- total_{expr_type}_{qc_var} - for qc_var in qc_vars (e.g. "total_counts_mito", total number of counts for variabes in qc_vars)\n+- pct_{expr_type}_{qc_var} - for qc_var in qc_vars (e.g. "pct_counts_mito", proportion of total counts for a cell which are mitochondrial)\n \n And also the variable level metrics:\n \n - total_{expr_type} (e.g. "total_counts", sum of counts for a gene)\n-- mean_{expr_type} (e.g. "mean counts", mean expression over all cells.\n+- mean_{expr_type} (e.g. "mean counts", mean expression over all cells)\n - n_cells_by_{expr_type} (e.g. "n_cells_by_counts", number of cells this expression is measured in)\n - pct_dropout_by_{expr_type} (e.g. "pct_dropout_by_counts", percentage of cells this feature does not appear in)\n \n' |
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| diff -r 7d22964a8639 -r cc0deb593fc8 macros.xml --- a/macros.xml Thu Dec 05 07:13:18 2019 -0500 +++ b/macros.xml Thu Dec 12 09:27:38 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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