Mercurial > repos > goeckslab > squidpy

annotate squidpy_spatial.py @ 0:be0e7952e229 draft

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planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
author goeckslab
date Mon, 29 Aug 2022 23:20:54 +0000
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children d30ef0613122
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be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
goeckslab
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diff changeset
1 import argparse
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
goeckslab
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2 import ast
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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3 import json
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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4 import warnings
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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6 import pandas as pd
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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7 import squidpy as sq
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8 from anndata import read_h5ad
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11 def main(inputs, anndata, output, output_plot):
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12 """
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13 Parameter
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14 ---------
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15 inputs : str
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16 File path to galaxy tool parameter.
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17 anndata : str
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18 File path to anndata containing phenotyping info.
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19 output : str
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20 File path to output.
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21 output_plot: str or None
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22 File path to save the plotting image.
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23 """
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24 warnings.simplefilter('ignore')
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26 with open(inputs, 'r') as param_handler:
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27 params = json.load(param_handler)
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29 adata = read_h5ad(anndata)
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31 if 'spatial' not in adata.obsm:
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32 try:
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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33 adata.obsm['spatial'] = adata.obs[['X_centroid', 'Y_centroid']].values
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34 except Exception as e:
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35 print(e)
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37 tool = params['analyses']['selected_tool']
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38 tool_func = getattr(sq.gr, tool)
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39
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40 options = params['analyses']['options']
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41
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42 for k, v in options.items():
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43 if not isinstance(v, str):
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44 continue
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45
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46 if v in ('', 'none'):
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47 options[k] = None
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48 continue
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49
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50 if k == 'genes': # for spatial_autocorr and sepal
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51 options[k] = [e.strip() for e in v.split(',')]
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52 elif k == 'radius': # for spatial_neighbors
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53 options[k] = ast.literal_eval(v)
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54 elif k == 'numba_parallel': # for nhood_enrichment and ligrec
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55 if v == 'false':
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56 options[k] = False
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57 elif v == 'true':
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58 options[k] = True
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59 elif k == 'interactions': # for ligrec
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60 options[k] = pd.read_csv(v, sep="\t")
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61 elif k == 'max_neighs':
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62 options[k] = int(v) # for sepal
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63
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64 cluster_key = params['analyses'].get('cluster_key')
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65 if cluster_key:
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66 tool_func(adata, cluster_key, **options)
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67 else:
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68 tool_func(adata, **options)
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69
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70 if output_plot:
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71 plotting_options = params['analyses']['plotting_options']
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72 for k, v in plotting_options.items():
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73 if not isinstance(v, str):
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74 continue
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75
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76 if v in ('', 'none'):
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77 plotting_options[k] = None
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78 continue
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79
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80 if k == 'figsize':
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81 options[k] = ast.literal_eval(v)
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82 elif k in ('palette', 'score', 'source_groups', 'target_groups'):
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83 options[k] = [e.strip() for e in v.split(',')]
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84 elif k == 'means_range': # ligrec
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85 v = v.strip()
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86 if v[0] == '(':
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87 v = v[1:]
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88 if v[-1] == ')':
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89 v = v[:-1]
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90 options[k] = tuple([float(e.strip()) for e in v.split(',', 1)])
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91
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92 plotting_func = getattr(sq.pl, tool)
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93 if cluster_key:
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94 plotting_func(adata, cluster_key, save=output_plot, **plotting_options)
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95 else: # TODO Remove this, since all plottings need cluster key
be0e7952e229 planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit ee16860018eba110ff845d62b18396db22abd91e
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96 plotting_func(adata, save=output_plot, **plotting_options)
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97
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98 adata.write(output)
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99
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100
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101 if __name__ == '__main__':
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102 aparser = argparse.ArgumentParser()
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103 aparser.add_argument("-i", "--inputs", dest="inputs", required=True)
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104 aparser.add_argument("-e", "--output", dest="output", required=True)
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105 aparser.add_argument("-a", "--anndata", dest="anndata", required=True)
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106 aparser.add_argument("-p", "--output_plot", dest="output_plot", required=False)
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107
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108 args = aparser.parse_args()
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109
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110 main(args.inputs, args.anndata, args.output, args.output_plot)