Repository 'scanpy_inspect'
hg clone https://toolshed.g2.bx.psu.edu/repos/iuc/scanpy_inspect

Changeset 20:d86cb2ce311b (2024-10-18)
Previous changeset 19:4338bf96809e (2024-10-03)
Commit message:
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scanpy/ commit 55ba4cd74d5d8f7baff164b1864c36759d1c7fd9
modified:
inspect.xml
macros.xml
b
diff -r 4338bf96809e -r d86cb2ce311b inspect.xml
--- a/inspect.xml Thu Oct 03 22:44:00 2024 +0000
+++ b/inspect.xml Fri Oct 18 10:39:04 2024 +0000
[
b'@@ -221,6 +221,27 @@\n     #end if\n     copy=False)\n \n+    #if str($method.get_df.get_df_select) == \'True\':\n+cluster_DEG = sc.get.rank_genes_groups_df(adata,\n+                                            group=None, # return all groups\n+                                            #if str($method.get_df.key) != \'\':\n+                                            key=\'$method.get_df.key\',\n+                                            #end if\n+                                            #if str($method.get_df.pval_cutoff) != \'\':\n+                                            pval_cutoff=$method.get_df.pval_cutoff,\n+                                            #end if\n+                                            #if str($method.get_df.log2fc_min) != \'\':\n+                                            log2fc_min=$method.get_df.log2fc_min,\n+                                            #end if\n+                                            #if str($method.get_df.log2fc_max) != \'\':\n+                                            log2fc_max=$method.get_df.log2fc_max,\n+                                            #end if\n+                                            @CMD_PARAM_GENE_SYMBOLS@                                            \n+                                            )\n+\n+cluster_DEG.to_csv(\'DEG.tsv\', sep="\\t", index=False)\n+    #end if\n+    \n #else if str($method.method) == "tl.marker_gene_overlap":\n reference_markers = {}\n #for $i, $s in enumerate($method.reference_markers)\n@@ -292,10 +313,10 @@\n sc.pp.sqrt(\n     adata,\n     copy=False)\n+\n+print("stats after sqrt:", "min=", adata.X.min(), "max=", adata.X.max(), "mean=", adata.X.mean())    \n #end if\n \n-print("stats after sqrt:", "min=", adata.X.min(), "max=", adata.X.max(), "mean=", adata.X.mean())\n-\n @CMD_ANNDATA_WRITE_OUTPUTS@\n         ]]>\n         </configfile>\n@@ -392,6 +413,20 @@\n                 <expand macro="params_score_genes"/>\n             </when>\n             <when value="tl.rank_genes_groups">\n+                <conditional name="get_df">\n+                    <param name="get_df_select" type="select" label="Get ranked genes as a Tabular file?">\n+                        <option value="False" selected="true">False</option>\n+                        <option value="True">True</option>\n+                    </param>\n+                    <when value="False"/>\n+                    <when value="True">\n+                        <param argument="key" type="text" value="" optional="true" label="Key differential expression groups were stored under"/>\n+                        <param argument="pval_cutoff" type="float" min="0.0" value="" optional="true" label="Return only adjusted p-values below the cutoff."/>\n+                        <param argument="log2fc_min" type="float" value="" optional="true" label="Minimum logfc to return."/>\n+                        <param argument="log2fc_max" type="float" value="" optional="true" label="Maximum logfc to return."/>\n+                        <expand macro="param_gene_symbols" label="Column name in [.var] DataFrame that stores gene symbols."/>\n+                    </when>\n+                </conditional>\n                 <param argument="groupby" type="text" value="" label="The key of the observations grouping to consider">\n                     <expand macro="sanitize_query"/>\n                 </param>\n@@ -558,6 +593,9 @@\n     </inputs>\n     <outputs>\n         <expand macro="anndata_outputs"/>\n+        <data name="ranked_gene" format="tabular" from_work_dir="DEG.tsv" label="${tool.name} (${method.method}) on ${on_string}: Ranked genes">\n+            <filter> method[\'method\'] == \'tl.rank_genes_groups\' and method[\'get_df\'][\'get_df_select\'] == \'True\'</filter>\n+        </data>\n     </outputs>\n     <tests>\n <!-- test 1 -->\n@@ -1028,6 +1066,157 @@\n                 </assert_contents>\n             </output>\n         </test>\n+\n+        <!-- test 16 -->\n+        <test expect_num_outputs="3">\n+            <param name="adata" value="krumsiek11.h5ad"/>\n+            <cond'..b'ssion="method=\'logreg\'"/>\n+                    <has_text_matching expression="solver=\'liblinear\'"/>\n+                    <has_text_matching expression="penalty=\'l2\'"/>\n+                    <has_text_matching expression="dual=False"/>\n+                    <has_text_matching expression="fit_intercept=True"/>\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="groups=\\[\'Ery\'\\]"/>\n+                    <has_text_matching expression="reference=\'Mk\'"/>\n+                    <has_text_matching expression="sc.get.rank_genes_groups_df"/>\n+                </assert_contents>\n+            </output>\n+            <output name="anndata_out" ftype="h5ad">\n+                <assert_contents>\n+                    <has_h5_keys keys="uns/rank_genes_groups"/>\n+                </assert_contents>\n+            </output>\n+            <output name="ranked_gene" ftype="tabular">\n+                <assert_contents>\n+                    <has_text_matching expression="names\\tscores"/>\n+                    <has_text_matching expression="Fli1\\t3.5328505"/>\n+                </assert_contents>\n+            </output>\n+        </test>\n+\n+        <!-- test 18 -->\n+        <test expect_num_outputs="3">\n+            <param name="adata" value="krumsiek11.h5ad"/>\n+            <conditional name="method">\n+                <param name="method" value="tl.rank_genes_groups"/>\n+                <conditional name="get_df">\n+                    <param name="get_df_select" value="True"/>\n+                    <param name="pval_cutoff" value="0.05"/>\n+                    <param name="log2fc_min" value="1"/>\n+                    <param name="log2fc_max" value="3"/>\n+                </conditional>\n+                <param name="groupby" value="cell_type"/>\n+                <param name="n_genes" value="100"/>\n+                <conditional name="tl_rank_genes_groups_method">\n+                    <param name="method" value="t-test_overestim_var"/>\n+                </conditional>\n+            </conditional>\n+            <section name="advanced_common">\n+                <param name="show_log" value="true"/>\n+            </section>\n+            <output name="hidden_output">\n+                <assert_contents>\n+                    <has_text_matching expression="sc.tl.rank_genes_groups"/>\n+                    <has_text_matching expression="groupby=\'cell_type\'"/>\n+                    <has_text_matching expression="use_raw=False"/>\n+                    <has_text_matching expression="reference=\'rest\'"/>\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="sc.get.rank_genes_groups_df"/>\n+                    <has_text_matching expression="pval_cutoff=0.05"/>\n+                    <has_text_matching expression="log2fc_min=1"/>\n+                    <has_text_matching expression="log2fc_max=3"/>\n+                </assert_contents>\n+            </output>\n+            <output name="anndata_out" ftype="h5ad">\n+                <assert_contents>\n+                    <has_h5_keys keys="uns/rank_genes_groups"/>\n+                </assert_contents>\n+            </output>\n+            <output name="ranked_gene" ftype="tabular">\n+                <assert_contents>\n+                    <has_line_matching expression="group\\tnames\\tscores\\tlogfoldchanges\\tpvals\\tpvals_adj"/>\n+                    <has_line_matching expression="Ery\\tFog1\\t21.071571\\t2.8023682\\t5.701001345880348e-35\\t3.135550740234191e-34"/>\n+                </assert_contents>\n+            </output>\n+        </test>\n     </tests>\n     <help><![CDATA[\n Calculate quality control metrics., using `pp.calculate_qc_metrics`\n'
b
diff -r 4338bf96809e -r d86cb2ce311b macros.xml
--- a/macros.xml Thu Oct 03 22:44:00 2024 +0000
+++ b/macros.xml Fri Oct 18 10:39:04 2024 +0000
b
@@ -1,6 +1,6 @@
 <macros>
     <token name="@TOOL_VERSION@">1.10.2</token>
-    <token name="@VERSION_SUFFIX@">1</token>
+    <token name="@VERSION_SUFFIX@">2</token>
     <token name="@PROFILE@">21.09</token>
     <xml name="requirements">
         <requirements>
@@ -1289,8 +1289,8 @@
     ]]>
     </token>
 
-    <xml name="param_gene_symbols">
-        <param argument="gene_symbols" type="text" value="" optional="true" label="Key for field in '.var' that stores gene symbols" help="By default 'var_names' refer to the index column of the '.var' DataFrame">
+    <xml name="param_gene_symbols" token_label="Key for field in '.var' that stores gene symbols" token_help="By default 'var_names' refer to the index column of the '.var' DataFrame">
+        <param argument="gene_symbols" type="text" value="" optional="true" label="@LABEL@" help="@HELP@">
             <expand macro="sanitize_query"/>
         </param>
     </xml>