| Previous changeset 1:dcfcad35e847 (2022-08-29) Next changeset 3:3a441d347a46 (2024-06-26) |
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Commit message:
planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/scimap commit 9fb5578191db8a559191e45156cfb95350f01aea |
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modified:
main_macros.xml mcmicro_to_anndata.py scimap_phenotyping.py scimap_phenotyping.xml test-data/mcmicro_output.csv test-data/tutorial_data.h5ad test-data/tutorial_data_pheno.h5ad |
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added:
anndata_to_csv.py scimap_plotting.py |
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removed:
test-data/imc.h5ad |
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| diff -r dcfcad35e847 -r ce22e846c5e4 anndata_to_csv.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/anndata_to_csv.py Mon Jun 10 18:44:25 2024 +0000 |
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| @@ -0,0 +1,45 @@ +import argparse +import json +import warnings + +import scimap as sm +from anndata import read_h5ad + + +def main(inputs, outfile): + """ + Parameters + --------- + inputs : str + File path to galaxy tool parameter. + anndata : str + File path to anndata. + output : str + File path to output. + """ + warnings.simplefilter('ignore') + + with open(inputs, 'r') as param_handler: + params = json.load(param_handler) + + adata = read_h5ad(params['anndata']) + + if params['layer'] == 'x': + params['layer'] = None + + df = sm.hl.scimap_to_csv( + adata=adata, + layer=params['layer'], + CellID=params['cellid'], + ) + + df.to_csv(outfile, index=False) + + +if __name__ == '__main__': + aparser = argparse.ArgumentParser() + aparser.add_argument("-i", "--inputs", dest="inputs", required=True) + aparser.add_argument("-e", "--outfile", dest="outfile", required=True) + args = aparser.parse_args() + + main(args.inputs, args.outfile) |
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| diff -r dcfcad35e847 -r ce22e846c5e4 main_macros.xml --- a/main_macros.xml Mon Aug 29 23:55:18 2022 +0000 +++ b/main_macros.xml Mon Jun 10 18:44:25 2024 +0000 |
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| @@ -1,5 +1,5 @@ <macros> - <token name="@TOOL_VERSION@">0.17.7</token> + <token name="@TOOL_VERSION@">2.1.0</token> <token name="@VERSION_SUFFIX@">0</token> <token name="@PROFILE@">20.01</token> |
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| diff -r dcfcad35e847 -r ce22e846c5e4 mcmicro_to_anndata.py --- a/mcmicro_to_anndata.py Mon Aug 29 23:55:18 2022 +0000 +++ b/mcmicro_to_anndata.py Mon Jun 10 18:44:25 2024 +0000 |
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| @@ -31,7 +31,11 @@ if v == '': options[k] = None - adata = sm.pp.mcmicro_to_scimap(image_path, drop_markers=drop_markers, **options) + adata = sm.pp.mcmicro_to_scimap( + image_path, + drop_markers=drop_markers, + **options + ) adata.write(outfile) |
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| diff -r dcfcad35e847 -r ce22e846c5e4 scimap_phenotyping.py --- a/scimap_phenotyping.py Mon Aug 29 23:55:18 2022 +0000 +++ b/scimap_phenotyping.py Mon Jun 10 18:44:25 2024 +0000 |
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| @@ -9,11 +9,12 @@ def main( adata, output, + log, gating_workflow, gating_workflow_ext, manual_gates=None, manual_gates_ext=None, - rescale_plots=False + random_state=0 ): """ Parameter @@ -22,6 +23,8 @@ File path to the input AnnData. output : str File path to the output AnnData. + log: bool + Boolean whether to log the input data prior to rescaling gating_workflow : str File path to the gating workflow. gating_workflow_ext : str @@ -30,8 +33,8 @@ File path to the munual gating. manual_gates_ext : str Datatype for munual gate, either 'csv' or 'tabular'. - rescale_plots : boolean - Save plots from rescaling. + random_state: int + The seed used by the random number generator for GMM in sm.pp.rescale """ warnings.simplefilter('ignore') @@ -41,13 +44,22 @@ sep = ',' if manual_gates_ext == 'csv' else '\t' manual_gates = pd.read_csv(manual_gates, sep=sep) - adata = sm.pp.rescale(adata, gate=manual_gates, save_fig=rescale_plots) + adata = sm.pp.rescale( + adata, + gate=manual_gates, + log=log, + random_state=random_state + ) # Phenotype cells # Load the gating workflow sep = ',' if gating_workflow_ext == 'csv' else '\t' phenotype = pd.read_csv(gating_workflow, sep=sep) - adata = sm.tl.phenotype_cells(adata, phenotype=phenotype, label="phenotype") + adata = sm.tl.phenotype_cells( + adata, + phenotype=phenotype, + label="phenotype" + ) # Summary of the phenotyping print(adata.obs['phenotype'].value_counts()) @@ -59,15 +71,50 @@ aparser = argparse.ArgumentParser() aparser.add_argument("-a", "--adata", dest="adata", required=True) aparser.add_argument("-o", "--output", dest="output", required=True) - aparser.add_argument("-g", "--gating_workflow", dest="gating_workflow", required=True) - aparser.add_argument("-s", "--gating_workflow_ext", dest="gating_workflow_ext", required=True) - aparser.add_argument("-m", "--manual_gates", dest="manual_gates", required=False) - aparser.add_argument("-S", "--manual_gates_ext", dest="manual_gates_ext", required=False) - aparser.add_argument("-p", "--rescale_plots", dest="rescale_plots", action="store_true", - default=False, required=False) + aparser.add_argument("-l", "--log", dest="log", action="store_true") + aparser.add_argument( + "-g", + "--gating_workflow", + dest="gating_workflow", + required=True + ) + aparser.add_argument( + "-s", + "--gating_workflow_ext", + dest="gating_workflow_ext", + required=True + ) + aparser.add_argument( + "-m", + "--manual_gates", + dest="manual_gates", + required=False + ) + aparser.add_argument( + "-S", + "--manual_gates_ext", + dest="manual_gates_ext", + required=False + ) + aparser.add_argument( + "--random_state", + dest="random_state", + type=int, + required=False + ) args = aparser.parse_args() - main(args.adata, args.output, args.gating_workflow, - args.gating_workflow_ext, args.manual_gates, - args.manual_gates_ext, args.rescale_plots) + if args.log: + print("\n adata.raw.X will be log1p transformed \n") + + main( + adata=args.adata, + output=args.output, + log=args.log, + gating_workflow=args.gating_workflow, + gating_workflow_ext=args.gating_workflow_ext, + manual_gates=args.manual_gates, + manual_gates_ext=args.manual_gates_ext, + random_state=args.random_state + ) |
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| diff -r dcfcad35e847 -r ce22e846c5e4 scimap_phenotyping.xml --- a/scimap_phenotyping.xml Mon Aug 29 23:55:18 2022 +0000 +++ b/scimap_phenotyping.xml Mon Jun 10 18:44:25 2024 +0000 |
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| @@ -7,19 +7,20 @@ <expand macro="scimap_requirements"/> <expand macro="macro_stdio" /> <version_command>echo "@VERSION@"</version_command> - <command> + <command detect_errors="aggressive"> <![CDATA[ python '$__tool_directory__/scimap_phenotyping.py' --adata '$anndata' + #if $log + --log + #end if #if $manual_gates --manual_gates '$manual_gates' --manual_gates_ext '${manual_gates.ext}' #end if --gating_workflow '$gating_workflow' --gating_workflow_ext '${gating_workflow.ext}' - #if $rescale_plots - --rescale_plots - #end if + --random_state '$random_state' --output '$output' ]]> @@ -29,17 +30,14 @@ </configfiles> <inputs> <param name="anndata" type="data" format="h5ad" label="Select the input anndata" /> + <param name="log" type="boolean" checked="true" label="Whether to log the data prior to rescaling" /> <param name="manual_gates" type="data" format="tabular,csv" optional="true" label="Select the dataset containing manual gate information" help="First column as markers and second column as the gate values in log1p scale. If a marker is not included, auto gating based on gaussian mixture modeling will be executed. Optional."/> <param name="gating_workflow" type="data" format="tabular,csv" label="Select the dataset containing gating workflow" /> - <param name="rescale_plots" type="boolean" checked="false" label="Save the GMM gates plots If True"/> + <param name="random_state" type="integer" value="0" optional="true" label="Set seed used by the random number generator for GMM" /> </inputs> <outputs> <data format="h5ad" name="output" /> - <collection name="gmm_plots" type="list" label="${tool.name}: GMM-plots"> - <filter>rescale_plots</filter> - <discover_datasets pattern="__designation_and_ext__" directory="auto_gating" ext="png"/> - </collection> </outputs> <tests> <test> @@ -63,6 +61,10 @@ AnnData. +**Important Note** + +If adata.raw.X exists, it will be used. If adata.raw.X does not exist, adata.X is used + **Output** Anndata with "obs/phenotype" added. @@ -70,6 +72,5 @@ ]]> </help> - <citations> - </citations> + <expand macro="citations" /> </tool> |
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| diff -r dcfcad35e847 -r ce22e846c5e4 scimap_plotting.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/scimap_plotting.py Mon Jun 10 18:44:25 2024 +0000 |
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| @@ -0,0 +1,125 @@ +import argparse +import json +import os +import warnings + +import matplotlib.pylab as plt +import numpy as np +import scimap as sm +import seaborn as sns +from anndata import read_h5ad + +sns.set(color_codes=True) + + +def main(inputs, anndata, output): + """ + Parameter + --------- + inputs : str + File path to galaxy tool parameter. + anndata : str + File path to anndata containing phenotyping info. + output : str + File path to output. + """ + warnings.simplefilter('ignore') + + with open(inputs, 'r') as param_handler: + params = json.load(param_handler) + + adata = read_h5ad(anndata) + + tool = params['analyses']['selected_tool'] + options = params['analyses']['options'] + + if tool == 'stacked_barplot': + + # parse list text arguments + for o in options.copy(): + opt_list = options.pop(o) + if opt_list: + options[o] = [x.strip() for x in opt_list.split(',')] + + # add base args into options dict to pass to tool + options['x_axis'] = params['analyses']['x_axis'] + options['y_axis'] = params['analyses']['y_axis'] + options['method'] = params['analyses']['method'] + + options['return_data'] = True + + df = sm.pl.stacked_barplot(adata, **options) + + # Pick cmap to use + num_phenotypes = len(df.columns) - 1 + if num_phenotypes <= 9: + matplotlib_cmap = "Set1" + elif num_phenotypes > 9 and num_phenotypes <= 20: + matplotlib_cmap = plt.cm.tab20 + else: + matplotlib_cmap = plt.cm.gist_ncar + + # Plotting + sns.set_theme(style="white") + ax = df.plot.bar(stacked=True, cmap=matplotlib_cmap) + fig = ax.get_figure() + handles, labels = ax.get_legend_handles_labels() + ax.legend( + reversed(handles), + reversed(labels), + bbox_to_anchor=(1, 1), + loc='upper left' + ) + plt.tight_layout() + + # # save and close + fig.savefig('out.png', dpi=300) + plt.close(fig) + + if tool == 'voronoi': + + plt.style.use('fast') + + tool_func = getattr(sm.pl, tool) + + # x_lim/y_lim need to be parsed from comma-sep str to integer tuples + for lim in ['x_lim', 'y_lim']: + opt_list = options.pop(lim) + if opt_list: + options[lim] = [int(x.strip()) for x in opt_list.split(',')] + + # parse list text arguments + for cat in ['overlay_points_categories', 'overlay_drop_categories']: + opt_list = options.pop(cat) + if opt_list: + options[cat] = [x.strip() for x in opt_list.split(',')] + + # add base args into options dict to pass to tool + options['color_by'] = params['analyses']['color_by'] + options['x_coordinate'] = params['analyses']['x_coordinate'] + options['y_coordinate'] = params['analyses']['y_coordinate'] + + # fill any missing params with None as tool expects + for k, v in options.items(): + if v == '': + options[k] = None + + options['saveDir'] = os.getcwd() + options['fileName'] = 'out.png' + + if options['size_max'] is None: + options['size_max'] = np.inf + + # call the tool and unpack all options + tool_func(adata, **options) + + +if __name__ == '__main__': + aparser = argparse.ArgumentParser() + aparser.add_argument("-i", "--inputs", dest="inputs", required=True) + aparser.add_argument("-a", "--anndata", dest="anndata", required=True) + aparser.add_argument("-e", "--output", dest="output", required=True) + + args = aparser.parse_args() + + main(args.inputs, args.anndata, args.output) |
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| diff -r dcfcad35e847 -r ce22e846c5e4 test-data/imc.h5ad |
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| Binary file test-data/imc.h5ad has changed |
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| diff -r dcfcad35e847 -r ce22e846c5e4 test-data/mcmicro_output.csv --- a/test-data/mcmicro_output.csv Mon Aug 29 23:55:18 2022 +0000 +++ b/test-data/mcmicro_output.csv Mon Jun 10 18:44:25 2024 +0000 |
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| b'@@ -498,4329 +498,3 @@\n 497,42428.94915,967.1186441,702.5762712,1137.59322,37041.13559,769.5254237,699.7966102,1651.576271,20054.16949,632.5762712,473.220339,1735.813559,27445.84746,1412.050847,3662.644068,5047.627119,9486.847458,1401.084746,451.4237288,2420.813559,18292.86441,419.3389831,891.2711864,474.4915254,21906.47458,428.0338983,134.9830508,5820.372881,18267.83051,1575.728814,1378.322034,2861.389831,14785.0678,610.6271186,304.4237288,4221.474576,11649.98305,947.8135593,470.7288136,1340.881356,8565.525424,922.2372881,190.3050847,4911.305085,7047.830508,1394.59322,241.440678,3259.491525,429.8644068,178.6440678,59,11.70055465,6.412084822,0.836468205,1,0.702380952,-0.357722233\r\n 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