Mercurial > repos > iuc > spapros_evaluation
diff evaluation.xml @ 0:0c1b0a3b19df draft default tip
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/spapros/ commit aed7fe13fa0ed09d77a31eeecaf3ec3fba7eed3b
| author | iuc |
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| date | Mon, 16 Sep 2024 11:37:34 +0000 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/evaluation.xml Mon Sep 16 11:37:34 2024 +0000 @@ -0,0 +1,598 @@ +<tool id="spapros_evaluation" name="Evaluation" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@profile@"> + <description>of marker genes with spapros</description> + <macros> + <import>macros.xml</import> + </macros> + <expand macro="requirements"> + </expand> + <expand macro="version_command"/> + <command detect_errors="exit_code"><![CDATA[ +@CMD@ + ]]></command> + <configfiles> + <configfile name="script_file"><![CDATA[ +@CMD_imports@ +@CMD_read_inputs@ + +mpl.rcParams['figure.dpi'] = $figure_options.dpi +plt.rcParams["font.size"] = $figure_options.fontsize + +header_probeset='infer' +#if $header_probeset == 'not_included': +header_probeset=None +#end if + +## Probe set generation +probeset = pd.read_csv('$probeset', sep='\t', index_col=0, header=header_probeset) +probeset = [x for x in probeset.values.flatten().tolist() if not pd.isna(x)] + +## Reference set generation +methods_pre="#echo ','.join(["%s" % $s for $i, $s in enumerate($methods_reference)])#" +methods=methods_pre.split(',') + +reference_sets = sp.se.select_reference_probesets( +adata, +n=$nreference, +#if $genes_key != '': +genes_key='$genes_key', +#else: +genes_key=None, +#end if +#if $obs_key != '': +obs_key='$obs_key', +#end if +#if $seeds != '': +seeds=[$seeds], +#end if +methods=methods, +verbosity=0 +) + +## Parameter setting + +custom_params = { +'data': { +'name': '$probeset_name', +'celltype_key': '$celltype_key' +}, +'metrics': { +#if $method.method == 'plot_summary' or $method.method == 'plot_cluster_similarity': +'cluster_similarity': { +'ns': [$method.ns_start, $method.ns_end], +'AUC_borders': [#echo ",".join(["[%s, %s]" % ($s.auc_borders_start, $s.auc_borders_end) for $i, $s in enumerate($method.series_auc_borders)])#] +}, +#end if +#if $method.method == 'plot_summary' or $method.method == 'plot_knn_overlap': +'knn_overlap': { +'ks': [#echo ",".join([ "%s" % $s.k for $i, $s in enumerate($method.knn) ])#] +}, +#end if +#if $method.method == 'plot_confusion_matrix': +'forest_clfs': { +'ct_key': '$celltype_key', +#if $method.method == 'plot_summary': +'threshold': $method.forest_clfs_threshold +#end if +}, +#end if +#if $method.method == 'plot_summary': +#if $method.select_marker_corr.use_marker_corr == 'True': +'marker_corr': { +'per_celltype': $method.select_marker_corr.per_celltype, +'per_marker': $method.select_marker_corr.per_marker, +#if $method.select_marker_corr.select_per_celltype_min_mean.use_per_celltype_min_mean == 'True' +'per_celltype_min_mean': $method.select_marker_corr.select_per_celltype_min_mean.per_celltype_min_mean, +#end if +#if $method.select_marker_corr.select_per_marker_min_mean.use_per_marker_min_mean == 'True' +'per_marker_min_mean': $method.select_marker_corr.select_per_marker_min_mean.per_marker_min_mean +#end if +}, +#end if +#end if +#if $method.method == 'plot_marker_corr': +'marker_corr': { +'per_celltype': $method.per_celltype, +'per_marker': $method.per_marker, +#if $method.select_per_celltype_min_mean.use_per_celltype_min_mean == 'True' +'per_celltype_min_mean': $method.select_per_celltype_min_mean.per_celltype_min_mean, +#else: +'per_celltype_min_mean': None, +#end if +#if $method.select_per_marker_min_mean.use_per_marker_min_mean == 'True' +'per_marker_min_mean': $method.select_per_marker_min_mean.per_marker_min_mean +#else: +'per_marker_min_mean': None +#end if +}, +#end if +#if $method.method == 'plot_summary': +'gene_corr': { +'threshold': $method.gene_corr_threshold +} +#end if +} +} + +## Setup evaluator + +#if $method.method == 'plot_summary' or $method.method == 'plot_marker_corr': + +header_markerset='infer' +feature_marker=dict() + +#if $method.method == 'plot_summary': +#if $method.select_marker_corr.header_markerset == 'not_included' : +header_markerset=None +#end if +feature_marker = {key: [v for v in list(value.values()) if pd.notna(v)] for key, value in pd.read_csv('$method.select_marker_corr.markerset', sep='\t', index_col=0, header=header_markerset).to_dict(orient='index').items()} +#end if +#if $method.method == 'plot_marker_corr': +#if $method.header_markerset == 'not_included': +header_markerset=None +#end if +feature_marker = {key: [v for v in list(value.values()) if pd.notna(v)] for key, value in pd.read_csv('$method.markerset', sep='\t', index_col=0, header=header_markerset).to_dict(orient='index').items()} +#end if + +#end if + +evaluator = sp.ev.ProbesetEvaluator( +adata, +metrics_params=custom_params, +scheme="full", +verbosity=0, +#if $method.method == 'plot_summary' or $method.method == 'plot_marker_corr': +marker_list=feature_marker, +#end if +results_dir=None +) + +## Evaluation reference set +for set_id, df in reference_sets.items(): + gene_set = df[df["selection"]].index.to_list() + evaluator.evaluate_probeset(gene_set, set_id=set_id) + +## Evaluation probe set +evaluator.evaluate_probeset(probeset, set_id='$probeset_name') + +## Execution of method ## + +#if $method.method == 'plot_summary': +evaluator.plot_summary( +@CMD_plot@ +) +#end if + +#if $method.method == 'plot_confusion_matrix': +evaluator.plot_confusion_matrix( +@CMD_plot@ +) +#end if + +#if $method.method == 'plot_coexpression': +evaluator.plot_coexpression( +@CMD_plot@ +) +#end if + +#if $method.method == 'plot_cluster_similarity': +evaluator.plot_cluster_similarity( +@CMD_plot@ +) +#end if + +#if $method.method == 'plot_knn_overlap': +evaluator.plot_knn_overlap( +@CMD_plot@ +) +#end if + +## plot_marker_corr does not allow for the show keyword +#if $method.method == 'plot_marker_corr': +evaluator.plot_marker_corr( +#if $method.set_ids != 'all' and $method.set_ids != '': +set_ids=[$method.set_ids], +#end if +save='plot.$format' +) +#end if + +]]></configfile> + </configfiles> + <inputs> + <expand macro="inputs_anndata"/> + <expand macro="param_plot_format"/> + <param name="probeset" type="data" format="tabular" label="Probeset tabular file with rows=conditions (e.g., celltypes) and column=features (e.g., genes)"/> + <param name="header_probeset" type="select" optional="false" label="Header in the list of probes?"> + <option value="included">Header incldued</option> + <option value="not_included">Header not included</option> + </param> + <param argument="nreference" type="integer" value="10" min="1" optional="false" label="Number of selected genes to generate a reference set"/> + <param name="methods_reference" type="select" multiple="True" optional="false" label="Select the methods to genereate a reference probeset"> + <option value="random" selected="true">Random</option> + <option value="PCA" selected="false">PCA</option> + <option value="DE" selected="false">Differential expressed features based on wilxocon rank genes test (DE)</option> + <option value="HVG" selected="false">Highly variable features (HVG)</option> + </param> + <param name="genes_key" type="text" optional="true" label="adata.var key for subset of preselected genes to run the selections" help="This is typically highly_variable_genes. Leave empty to not subset genes."/> + <param name="obs_key" type="text" optional="true" label="Column name of adata.obs for which marker scores are calculated" help="Only required for method DE."/> + <param name="seeds" type="text" optional="true" label="List of random integer seeds (comma seperated, e.g., 123,999,22)" help="For each seed, one random gene set is selected if random in methods. Leave it empty to for one random set with a random seed."/> + <param name="probeset_name" type="text" value="probeset" optional="false" label="Name for your probeset that should be displayed in plots"/> + <param name="celltype_key" type="text" value="celltype" optional="false" label="Column name of adata.obs that represents groups of your cells (e.g., celltype)"/> + <conditional name="method"> + <param argument="method" type="select" optional="false" label="Method of spapros"> + <option value="plot_summary">Plot statistic summary, using 'evaluator.plot_summary'</option> + <option value="plot_confusion_matrix">Plot confusion matrix, using 'evaluator.plot_confusion_matrix'</option> + <option value="plot_coexpression">Plot coexpression heatmap, using 'evaluator.plot_coexpression'</option> + <option value="plot_cluster_similarity">Plot cluster similariy, using 'evaluator.plot_cluster_similarity'</option> + <option value="plot_knn_overlap">Plot knn overlap, using 'evaluator.plot_knn_overlap'</option> + <option value="plot_marker_corr">Plot featue marker correlation, using 'evaluator.plot_marker_corr'</option> + </param> + <when value="plot_summary"> + <expand macro="set_ids"/> + <param name="forest_clfs_threshold" type="float" value="0.8" min="0.0" max="1.0" label="Assesses how many cell types (%) can be predicted with an accuracy of at least threshold" help="The metric gives an idea about how many cell types can be identified with high confidence with the given gene set."/> + <param name="gene_corr_threshold" type="float" value="0.8" min="0.0" max="1.0" label="Percentage of features (e.g., genes) that have a maximum correlation of less than threshold with all other features" help="This metric gives an idea about how many features show unique expression profiles in the gene set."/> + <param name="ns_start" type="integer" value="5" min="1" label="The minimum number of leiden clusters clusters" help="Clusterings are calculated with different leiden resolutions to genertate clusterings of n = ns_start to ns_end clusters."/> + <param name="ns_end" type="integer" value="21" min="1" label="The maximum number of leiden clusters clusters" help="Clusterings are calculated with different leiden resolutions to genertate clusterings of n = ns_start to ns_end clusters."/> + <repeat name="series_auc_borders" title="Calculates nmi AUCs over given borders"> + <param name="auc_borders_start" type="integer" value="15" min="1" label="Calculates nmi over n ranges auc_borders_start to auc_borders_end" help="Defined border shouldn't exceed values in nmis."/> + <param name="auc_borders_end" type="integer" value="20" min="1" label="Calculates nmi over n ranges auc_borders_start to auc_borders_end" help="Defined border shouldn't exceed values in nmis."/> + </repeat> + <repeat name="knn" title="Calculate knn graphs for each k"> + <param name="k" type="integer" value="10" min="1" label="Includes nearest neighbors for all k"/> + </repeat> + <conditional name="select_marker_corr"> + <param name="use_marker_corr" type="select" label="Do you want to calculate the correlation between your probeset and marker features?"> + <option value="False">No</option> + <option value="True">Yes</option> + </param> + <when value="True"> + <expand macro="param_markerset"/> + <param name="per_celltype" type="boolean" truevalue="True" falsevalue="False" label="Wether to return columns with per cell type max correlations" checked="true"/> + <param name="per_marker" type="boolean" truevalue="True" falsevalue="False" label="Wether to return columns with per marker max correlations" checked="true"/> + <conditional name="select_per_celltype_min_mean"> + <param name="use_per_celltype_min_mean" type="select" label="Add a column for correlation per cell type that only takes into accounts markers with mean expression > per_celltype_min_mean"> + <option value="False">No</option> + <option value="True">Yes</option> + </param> + <when value="True"> + <param name="per_celltype_min_mean" type="float" value="0.0" min="0.0" label="Set per_celltype_min_mean"/> + </when> + <when value="False"/> + </conditional> + <conditional name="select_per_marker_min_mean"> + <param name="use_per_marker_min_mean" type="select" label="Add a column for correlation per cell type that only takes into accounts markers with mean expression > per_celltype_min_mean"> + <option value="False">No</option> + <option value="True">Yes</option> + </param> + <when value="True"> + <param name="per_marker_min_mean" type="float" value="0.0" min="0.0" label="Set per_marker_min_mean"/> + </when> + <when value="False"/> + </conditional> + </when> + <when value="False"/> + </conditional> + </when> + <when value="plot_confusion_matrix"> + <expand macro="set_ids"/> + </when> + <when value="plot_coexpression"> + <expand macro="set_ids"/> + </when> + <when value="plot_cluster_similarity"> + <expand macro="set_ids"/> + <param name="ns_start" type="integer" value="5" min="1" label="The minimum number of leiden clusters clusters" help="Clusterings are calculated with different leiden resolutions to genertate clusterings of n = ns_start to ns_end clusters."/> + <param name="ns_end" type="integer" value="21" min="1" label="The maximum number of leiden clusters clusters" help="Clusterings are calculated with different leiden resolutions to genertate clusterings of n = ns_start to ns_end clusters."/> + <repeat name="series_auc_borders" title="Calculates nmi AUCs over given borders"> + <param name="auc_borders_start" type="integer" value="15" min="1" label="Calculates nmi over n ranges auc_borders_start to auc_borders_end" help="Defined border shouldn't exceed values in nmis."/> + <param name="auc_borders_end" type="integer" value="20" min="1" label="Calculates nmi over n ranges auc_borders_start to auc_borders_end" help="Defined border shouldn't exceed values in nmis."/> + </repeat> + </when> + <when value="plot_knn_overlap"> + <expand macro="set_ids"/> + <repeat name="knn" title="Calculate knn graphs for each k"> + <param name="k" type="integer" value="10" min="1" label="Includes nearest neighbors for all k"/> + </repeat> + </when> + <when value="plot_marker_corr"> + <expand macro="param_markerset"/> + <expand macro="set_ids"/> + <param name="per_celltype" type="boolean" truevalue="True" falsevalue="False" label="Wether to return columns with per cell type max correlations" checked="true"/> + <param name="per_marker" type="boolean" truevalue="True" falsevalue="False" label="Wether to return columns with per marker max correlations" checked="true"/> + <conditional name="select_per_celltype_min_mean"> + <param name="use_per_celltype_min_mean" type="select" label="Add a column for correlation per cell type that only takes into accounts markers with mean expression > per_celltype_min_mean"> + <option value="False">No</option> + <option value="True">Yes</option> + </param> + <when value="True"> + <param name="per_celltype_min_mean" type="float" value="0.0" min="0.0" label="Set per_celltype_min_mean"/> + </when> + <when value="False"/> + </conditional> + <conditional name="select_per_marker_min_mean"> + <param name="use_per_marker_min_mean" type="select" label="Add a column for correlation per cell type that only takes into accounts markers with mean expression > per_celltype_min_mean"> + <option value="False">No</option> + <option value="True">Yes</option> + </param> + <when value="True"> + <param name="per_marker_min_mean" type="float" value="0.0" min="0.0" label="Set per_marker_min_mean"/> + </when> + <when value="False"/> + </conditional> + </when> + </conditional> + <section name="figure_options" title="Figure Output Options" expanded="false"> + <param argument="dpi" type="integer" value="300" min="1" label="Dpi of figures"/> + <param argument="fontsize" type="integer" value="100" min="1" label="Font size of figures"/> + </section> + <expand macro="inputs_common_advanced"/> + </inputs> + <outputs> + <data name="out_png" format="png" from_work_dir="*.png" label="PNG plot from ${tool.name} (${method.method}) on ${on_string}"> + <filter>format == 'png'</filter> + </data> + <data name="out_pdf" format="pdf" from_work_dir="*.pdf" label="PDF plot from ${tool.name} (${method.method}) on ${on_string}"> + <filter>format == 'pdf'</filter> + </data> + <data name="out_svg" format="svg" from_work_dir="*.svg" label="SVG plot from ${tool.name} (${method.method}) on ${on_string}"> + <filter>format == 'svg'</filter> + </data> + <expand macro="hidden_outputs"/> + </outputs> + <tests> + <test expect_num_outputs="2"> + <param name="adata" value="tl.rank_genes_groups.newton-cg.pbmc68k_reduced_240cells.h5ad"/> + <param name="format" value="png"/> + <param name="probeset" value="tl.rank_genes_groups.newton-cg.pbmc68k_highly_reduced_marker_filtered_1.tsv"/> + <param name="header_probeset" value="included"/> + <param name="nreference" value="30"/> + <param name="methods_reference" value="random,PCA,DE,HVG"/> + <param name="genes_key" value="highly_variable"/> + <param name="obs_key" value="celltype"/> + <param name="seeds" value="123,124"/> + <conditional name="method"> + <param name="method" value="plot_summary"/> + <param name="set_ids" value="all"/> + <param name="forest_clfs_threshold" value="0.8"/> + <param name="gene_corr_threshold" value="0.8"/> + <param name="ns_start" value="5"/> + <param name="ns_end" value="21"/> + <repeat name="series_auc_borders"> + <param name="auc_borders_start" value="7"/> + <param name="auc_borders_end" value="14"/> + </repeat> + <repeat name="series_auc_borders"> + <param name="auc_borders_start" value="15"/> + <param name="auc_borders_end" value="20"/> + </repeat> + <repeat name="knn"> + <param name="k" value="5"/> + </repeat> + <repeat name="knn"> + <param name="k" value="10"/> + </repeat> + <conditional name="select_marker_corr"> + <param name="use_marker_corr" value="True"/> + <param name="markerset" value="marker.tsv"/> + <param name="header_markerset" value="not_included"/> + <param name="per_celltype" value="True"/> + <param name="per_marker" value="True"/> + <conditional name="select_per_celltype_min_mean"> + <param name="use_per_celltype_min_mean" value="False"/> + </conditional> + <conditional name="select_per_marker_min_mean"> + <param name="use_per_marker_min_mean" value="True"/> + <param name="per_marker_min_mean" value="0.025"/> + </conditional> + </conditional> + </conditional> + <param name="show_log" value="true" /> + <output name="hidden_output"> + <assert_contents> + <has_text_matching expression="'name': 'probeset',"/> + <has_text_matching expression="'per_celltype': True,"/> + <has_text_matching expression="'per_marker': True,"/> + <has_text_matching expression="'per_marker_min_mean': 0.025"/> + <has_text_matching expression="evaluator.plot_summary"/> + <has_text_matching expression="save='plot.png',"/> + </assert_contents> + </output> + <output name="out_png"> + <assert_contents> + <has_image_width width="3253" delta="2"/> + <has_image_height height="1446" delta="2"/> + </assert_contents> + </output> + </test> + <test expect_num_outputs="2"> + <param name="adata" value="tl.rank_genes_groups.newton-cg.pbmc68k_reduced_240cells.h5ad"/> + <param name="format" value="png"/> + <param name="probeset" value="tl.rank_genes_groups.newton-cg.pbmc68k_highly_reduced_marker_filtered_1.tsv"/> + <param name="header_probeset" value="included"/> + <param name="nreference" value="30"/> + <param name="methods_reference" value="random,PCA,DE,HVG"/> + <param name="genes_key" value="highly_variable"/> + <param name="obs_key" value="celltype"/> + <param name="seeds" value="123,124"/> + <conditional name="method"> + <param name="method" value="plot_confusion_matrix"/> + <param name="set_ids" value="all"/> + </conditional> + <param name="show_log" value="true" /> + <output name="hidden_output"> + <assert_contents> + <has_text_matching expression="'name': 'probeset',"/> + <has_text_matching expression="'ct_key': 'celltype',"/> + <has_text_matching expression="evaluator.plot_confusion_matrix"/> + <has_text_matching expression="save='plot.png',"/> + </assert_contents> + </output> + <output name="out_png"> + <assert_contents> + <has_image_width width="4560" delta="2"/> + <has_image_height height="1859" delta="2"/> + </assert_contents> + </output> + </test> + <test expect_num_outputs="2"> + <param name="adata" value="tl.rank_genes_groups.newton-cg.pbmc68k_reduced_240cells.h5ad"/> + <param name="format" value="png"/> + <param name="probeset" value="tl.rank_genes_groups.newton-cg.pbmc68k_highly_reduced_marker_filtered_1.tsv"/> + <param name="header_probeset" value="included"/> + <param name="nreference" value="30"/> + <param name="methods_reference" value="random,PCA,DE,HVG"/> + <param name="genes_key" value="highly_variable"/> + <param name="obs_key" value="celltype"/> + <param name="seeds" value="123,124"/> + <conditional name="method"> + <param name="method" value="plot_coexpression"/> + <param name="set_ids" value="all"/> + </conditional> + <param name="show_log" value="true" /> + <output name="hidden_output"> + <assert_contents> + <has_text_matching expression="'name': 'probeset',"/> + <has_text_matching expression="evaluator.plot_coexpression"/> + <has_text_matching expression="save='plot.png',"/> + </assert_contents> + </output> + <output name="out_png"> + <assert_contents> + <has_image_width width="5412" delta="2"/> + <has_image_height height="3463" delta="2"/> + </assert_contents> + </output> + </test> + <test expect_num_outputs="2"> + <param name="adata" value="tl.rank_genes_groups.newton-cg.pbmc68k_reduced_240cells.h5ad"/> + <param name="format" value="png"/> + <param name="probeset" value="tl.rank_genes_groups.newton-cg.pbmc68k_highly_reduced_marker_filtered_1.tsv"/> + <param name="header_probeset" value="included"/> + <param name="nreference" value="30"/> + <param name="methods_reference" value="random,PCA,DE,HVG"/> + <param name="genes_key" value="highly_variable"/> + <param name="obs_key" value="celltype"/> + <param name="seeds" value="123,124"/> + <conditional name="method"> + <param name="method" value="plot_cluster_similarity"/> + <param name="set_ids" value="all"/> + <param name="ns_start" value="3"/> + <param name="ns_end" value="20"/> + <repeat name="series_auc_borders"> + <param name="auc_borders_start" value="7"/> + <param name="auc_borders_end" value="14"/> + </repeat> + <repeat name="series_auc_borders"> + <param name="auc_borders_start" value="15"/> + <param name="auc_borders_end" value="20"/> + </repeat> + </conditional> + <param name="show_log" value="true" /> + <output name="hidden_output"> + <assert_contents> + <has_text_matching expression="'name': 'probeset',"/> + <has_text_matching expression="evaluator.plot_cluster_similarity"/> + <has_text_matching expression="save='plot.png',"/> + </assert_contents> + </output> + <output name="out_png"> + <assert_contents> + <has_image_width width="3223" delta="2"/> + <has_image_height height="1406" delta="2"/> + </assert_contents> + </output> + </test> + <test expect_num_outputs="2"> + <param name="adata" value="tl.rank_genes_groups.newton-cg.pbmc68k_reduced_240cells.h5ad"/> + <param name="format" value="png"/> + <param name="probeset" value="tl.rank_genes_groups.newton-cg.pbmc68k_highly_reduced_marker_filtered_1.tsv"/> + <param name="header_probeset" value="included"/> + <param name="nreference" value="30"/> + <param name="methods_reference" value="random,PCA,DE,HVG"/> + <param name="genes_key" value="highly_variable"/> + <param name="obs_key" value="celltype"/> + <param name="seeds" value="123,124"/> + <conditional name="method"> + <param name="method" value="plot_knn_overlap"/> + <param name="set_ids" value="all"/> + <repeat name="knn"> + <param name="k" value="6"/> + </repeat> + <repeat name="knn"> + <param name="k" value="11"/> + </repeat> + </conditional> + <param name="show_log" value="true" /> + <output name="hidden_output"> + <assert_contents> + <has_text_matching expression="'name': 'probeset',"/> + <has_text_matching expression="evaluator.plot_knn_overlap"/> + <has_text_matching expression="save='plot.png',"/> + </assert_contents> + </output> + <output name="out_png"> + <assert_contents> + <has_image_width width="3223" delta="2"/> + <has_image_height height="1406" delta="2"/> + </assert_contents> + </output> + </test> + <test expect_num_outputs="2"> + <param name="adata" value="tl.rank_genes_groups.newton-cg.pbmc68k_reduced_240cells.h5ad"/> + <param name="format" value="png"/> + <param name="probeset" value="tl.rank_genes_groups.newton-cg.pbmc68k_highly_reduced_marker_filtered_1.tsv"/> + <param name="header_probeset" value="included"/> + <param name="nreference" value="50"/> + <param name="methods_reference" value="random,PCA,DE,HVG"/> + <param name="genes_key" value="highly_variable"/> + <param name="obs_key" value="celltype"/> + <conditional name="method"> + <param name="method" value="plot_marker_corr"/> + <param name="set_ids" value="all"/> + <param name="use_marker_corr" value="True"/> + <param name="markerset" value="marker.tsv"/> + <param name="header_markerset" value="not_included"/> + <param name="per_celltype" value="True"/> + <param name="per_marker" value="True"/> + <conditional name="select_per_celltype_min_mean"> + <param name="use_per_celltype_min_mean" value="False"/> + </conditional> + <conditional name="select_per_marker_min_mean"> + <param name="use_per_marker_min_mean" value="True"/> + <param name="per_marker_min_mean" value="0.025"/> + </conditional> + </conditional> + <param name="show_log" value="true" /> + <output name="hidden_output"> + <assert_contents> + <has_text_matching expression="'name': 'probeset',"/> + <has_text_matching expression="'per_celltype': True,"/> + <has_text_matching expression="'per_marker': True,"/> + <has_text_matching expression="'per_marker_min_mean': 0.025"/> + <has_text_matching expression="evaluator.plot_marker_corr"/> + <has_text_matching expression="save='plot.png'"/> + </assert_contents> + </output> + <output name="out_png"> + <assert_contents> + <has_image_width width="5064" delta="2"/> + <has_image_height height="4554" delta="2"/> + </assert_contents> + </output> + </test> + </tests> + <help><![CDATA[ +Probe set evaluation for single-cell sequencing data using spapros. +============================================================================================================ + +Spapros is a python package that provides a pipeline for probe set selection and evaluation for targeted spatial transcriptomics data. + +Key Features: +* Select probe sets for spatial transcriptomics which identify cell types of interest, capture general transcriptomic variation, and incorporate prior knowledge +* Evaluate probe sets with an extensive pipeline + +Further documentation can be found here: https://spapros.readthedocs.io/en/latest/index.html. + + ]]></help> + <expand macro="citations"/> +</tool>