digraph workflow {
	graph [_draw_="c 9 -#fffffe00 C 7 -#eeeeee P 4 0 0 0 278 2977 278 2977 0 ",
		bb="0,0,2977,278",
		bgcolor="#eeeeee",
		clusterrank=local,
		color=black,
		dpi=96,
		fontsize=10,
		labeljust=left,
		nodesep=0.05,
		ranksep=0.22,
		xdotversion=1.7
	];
	node [color=black,
		fillcolor=lightgoldenrodyellow,
		fontcolor=black,
		fontname=Helvetica,
		fontsize=10,
		height=0,
		label="\N",
		shape=record,
		style=filled,
		width=0
	];
	edge [arrowsize=0.7,
		color=black,
		fontcolor=black,
		fontname=Helvetica,
		fontsize=8
	];
	subgraph cluster_inputs {
		graph [_draw_="S 6 -dashed c 7 -#000000 C 7 -#eeeeee P 4 696 215 696 270 991 270 991 215 ",
			_ldraw_="F 10 11 -Times-Roman c 7 -#000000 T 746 258 0 84 15 -Workflow Inputs ",
			bb="696,215,991,270",
			label="Workflow Inputs",
			lheight=0.15,
			lp="746,260.5",
			lwidth=1.17,
			rank=same,
			style=dashed
		];
		assay	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 881.5 223.5 881.5 242.5 982.5 242.5 982.5 223.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 932 230.5 0 85 15 -scRNA-seq assay ",
			fillcolor="#94DDF4",
			height=0.27778,
			label="scRNA-seq assay",
			pos="932,233",
			rects="881.5,223.5,982.5,242.5",
			width=1.4028];
		data_dir	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 704.5 223.5 704.5 242.5 877.5 242.5 877.5 223.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 791 230.5 0 157 32 -Directory containing FASTQ files ",
			fillcolor="#94DDF4",
			height=0.27778,
			label="Directory containing FASTQ files",
			pos="791,233",
			rects="704.5,223.5,877.5,242.5",
			width=2.4028];
	}
	subgraph cluster_outputs {
		graph [_draw_="S 6 -dashed c 7 -#000000 C 7 -#eeeeee P 4 8 8 8 63 2969 63 2969 8 ",
			_ldraw_="F 10 11 -Times-Roman c 7 -#000000 T 62 15 0 92 16 -Workflow Outputs ",
			bb="8,8,2969,63",
			label="Workflow Outputs",
			labelloc=b,
			lheight=0.15,
			lp="62,17.5",
			lwidth=1.28,
			rank=same,
			style=dashed
		];
		sdata_zarr	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 16.5 35.5 16.5 54.5 243.5 54.5 243.5 35.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 130 42.5 0 211 44 -SpatialData object serialized in zarr format ",
			fillcolor="#94DDF4",
			height=0.27778,
			label="SpatialData object serialized in zarr format",
			pos="130,45",
			rects="16.5,35.5,243.5,54.5",
			width=3.1528];
		dispersion_plot	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 2111.5 35.5 2111.5 54.5 2284.5 54.5 2284.5 35.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 2198 42.5 0 157 31 -Gene expression dispersion plot ",
			fillcolor="#94DDF4",
			height=0.27778,
			label="Gene expression dispersion plot",
			pos="2198,45",
			rects="2111.5,35.5,2284.5,54.5",
			width=2.4028];
		umap_plot	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 2289 35.5 2289 54.5 2481 54.5 2481 35.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 2385 42.5 0 176 34 -UMAP dimensionality reduction plot ",
			fillcolor="#94DDF4",
			height=0.27778,
			label="UMAP dimensionality reduction plot",
			pos="2385,45",
			rects="2289,35.5,2481,54.5",
			width=2.6667];
		filtered_data_h5ad	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 2485.5 35.5 2485.5 54.5 2648.5 54.5 2648.5 35.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 2567 42.5 0 147 33 -Full data set of filtered results ",
			fillcolor="#94DDF4",
			height=0.27778,
			label="Full data set of filtered results",
			pos="2567,45",
			rects="2485.5,35.5,2648.5,54.5",
			width=2.2639];
		interaction_matrix_plot	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 1300.5 35.5 1300.5 54.5 1431.5 54.5 1431.5 35.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 1366 42.5 0 115 23 -interaction_matrix_plot ",
			fillcolor="#94DDF4",
			height=0.27778,
			label=interaction_matrix_plot,
			pos="1366,45",
			rects="1300.5,35.5,1431.5,54.5",
			width=1.8194];
		ripley_plot	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 1436 35.5 1436 54.5 1504 54.5 1504 35.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 1470 42.5 0 52 11 -ripley_plot ",
			fillcolor="#94DDF4",
			height=0.27778,
			label=ripley_plot,
			pos="1470,45",
			rects="1436,35.5,1504,54.5",
			width=0.94444];
		centrality_scores_plot	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 621 35.5 621 54.5 745 54.5 745 35.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 683 42.5 0 108 22 -centrality_scores_plot ",
			fillcolor="#94DDF4",
			height=0.27778,
			label=centrality_scores_plot,
			pos="683,45",
			rects="621,35.5,745,54.5",
			width=1.7222];
		neighborhood_enrichment_plot	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 749 35.5 749 54.5 917 54.5 917 35.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 833 42.5 0 152 28 -neighborhood_enrichment_plot ",
			fillcolor="#94DDF4",
			height=0.27778,
			label=neighborhood_enrichment_plot,
			pos="833,45",
			rects="749,35.5,917,54.5",
			width=2.3333];
		umap_density_plot	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 2653 35.5 2653 54.5 2961 54.5 2961 35.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 2807 42.5 0 292 59 -UMAP dimensionality reduction plot, colored by cell density ",
			fillcolor="#94DDF4",
			height=0.27778,
			label="UMAP dimensionality reduction plot, colored by cell density",
			pos="2807,45",
			rects="2653,35.5,2961,54.5",
			width=4.2778];
		squidpy_annotated_h5ad	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 921.5 35.5 921.5 54.5 1060.5 54.5 1060.5 35.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 991 42.5 0 123 22 -squidpy_annotated_h5ad ",
			fillcolor="#94DDF4",
			height=0.27778,
			label=squidpy_annotated_h5ad,
			pos="991,45",
			rects="921.5,35.5,1060.5,54.5",
			width=1.9306];
		spatial_plot	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 1508.5 35.5 1508.5 54.5 1747.5 54.5 1747.5 35.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 1628 42.5 0 223 46 -Slide-seq bead plot, colored by Leiden cluster ",
			fillcolor="#94DDF4",
			height=0.27778,
			label="Slide-seq bead plot, colored by Leiden cluster",
			pos="1628,45",
			rects="1508.5,35.5,1747.5,54.5",
			width=3.3194];
		marker_gene_plot_logreg	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 1752 35.5 1752 54.5 1950 54.5 1950 35.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 1851 42.5 0 182 35 -Cluster marker genes, logreg method ",
			fillcolor="#94DDF4",
			height=0.27778,
			label="Cluster marker genes, logreg method",
			pos="1851,45",
			rects="1752,35.5,1950,54.5",
			width=2.75];
		co_occurrence_plot	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 1065 35.5 1065 54.5 1175 54.5 1175 35.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 1120 42.5 0 94 18 -co_occurrence_plot ",
			fillcolor="#94DDF4",
			height=0.27778,
			label=co_occurrence_plot,
			pos="1120,45",
			rects="1065,35.5,1175,54.5",
			width=1.5278];
		marker_gene_plot_t_test	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 1954.5 35.5 1954.5 54.5 2107.5 54.5 2107.5 35.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 2031 42.5 0 137 28 -Cluster marker genes, t-test ",
			fillcolor="#94DDF4",
			height=0.27778,
			label="Cluster marker genes, t-test",
			pos="2031,45",
			rects="1954.5,35.5,2107.5,54.5",
			width=2.125];
		squidpy_spatial_plot	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 1179.5 35.5 1179.5 54.5 1296.5 54.5 1296.5 35.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 1238 42.5 0 101 20 -squidpy_spatial_plot ",
			fillcolor="#94DDF4",
			height=0.27778,
			label=squidpy_spatial_plot,
			pos="1238,45",
			rects="1179.5,35.5,1296.5,54.5",
			width=1.625];
		count_matrix_h5ad	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 445 35.5 445 54.5 617 54.5 617 35.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 531 42.5 0 156 30 -Count matrix converted to h5ad ",
			fillcolor="#94DDF4",
			height=0.27778,
			label="Count matrix converted to h5ad",
			pos="531,45",
			rects="445,35.5,617,54.5",
			width=2.3889];
		scanpy_qc_results	[_draw_="c 7 -#000000 C 7 -#94ddf4 P 4 247.5 35.5 247.5 54.5 440.5 54.5 440.5 35.5 ",
			_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 344 42.5 0 177 35 -Quality control metrics from Scanpy ",
			fillcolor="#94DDF4",
			height=0.27778,
			label="Quality control metrics from Scanpy",
			pos="344,45",
			rects="247.5,35.5,440.5,54.5",
			width=2.6806];
	}
	scanpy_analysis	[_draw_="c 7 -#000000 C 7 -#fafad2 P 4 1831 125.5 1831 144.5 2043 144.5 2043 125.5 ",
		_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 1937 132.5 0 196 39 -Dimensionality reduction and clustering ",
		height=0.27778,
		label="Dimensionality reduction and clustering",
		pos="1937,135",
		rects="1831,125.5,2043,144.5",
		width=2.9444];
	assay -> scanpy_analysis	[_draw_="c 7 -#000000 B 4 982.18 227.21 1140.28 212.1 1629.96 165.33 1839.86 145.28 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 1839.88 147.74 1846.62 144.63 1839.41 142.86 ",
		_ldraw_="F 8 9 -Helvetica c 7 -#000000 T 1579.5 178.1 0 25 5 -assay ",
		label=assay,
		lp="1579.5,180",
		pos="e,1848.1,144.49 982.18,227.21 1140.3,212.1 1630,165.33 1839.9,145.28"];
	convert_formats	[_draw_="c 7 -#000000 C 7 -#fafad2 P 4 751 170.5 751 189.5 1113 189.5 1113 170.5 ",
		_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 932 177.5 0 346 68 -Convert Alevin sparse output to anndata.AnnData object, save as h5ad ",
		height=0.27778,
		label="Convert Alevin sparse output to anndata.AnnData object, save as h5ad",
		pos="932,180",
		rects="751,170.5,1113,189.5",
		width=5.0278];
	assay -> convert_formats	[_draw_="c 7 -#000000 B 4 932 223.58 932 216.52 932 206.24 932 197.55 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 934.45 197.78 932 190.78 929.55 197.78 ",
		_ldraw_="F 8 9 -Helvetica c 7 -#000000 T 944.5 200.6 0 25 5 -assay ",
		label=assay,
		lp="944.5,202.5",
		pos="e,932,189.26 932,223.58 932,216.52 932,206.24 932,197.55"];
	compute_qc_results	[_draw_="c 7 -#000000 C 7 -#fafad2 P 4 740 125.5 740 144.5 858 144.5 858 125.5 ",
		_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 799 132.5 0 102 18 -Compute QC metrics ",
		height=0.27778,
		label="Compute QC metrics",
		pos="799,135",
		rects="740,125.5,858,144.5",
		width=1.6389];
	assay -> compute_qc_results	[_draw_="c 7 -#000000 B 10 907.75 223.55 898.52 220.55 887.85 217.34 878 215 844.27 207 746.47 216.41 724 190 708.74 172.06 735.65 156.94 \
761.38 147.3 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 762.08 149.65 767.85 145 760.44 145.03 ",
		_ldraw_="F 8 9 -Helvetica c 7 -#000000 T 736.5 178.1 0 25 5 -assay ",
		label=assay,
		lp="736.5,180",
		pos="e,769.28,144.49 907.75,223.55 898.52,220.55 887.85,217.34 878,215 844.27,207 746.47,216.41 724,190 708.74,172.06 735.65,156.94 761.38,\
147.3"];
	squidpy_analysis	[_draw_="c 7 -#000000 C 7 -#fafad2 P 4 1014 80.5 1014 99.5 1226 99.5 1226 80.5 ",
		_ldraw_="F 10 9 -Helvetica c 7 -#000000 T 1120 87.5 0 196 39 -Dimensionality reduction and clustering ",
		height=0.27778,
		label="Dimensionality reduction and clustering",
		pos="1120,90",
		rects="1014,80.5,1226,99.5",
		width=2.9444];
	assay -> squidpy_analysis	[_draw_="c 7 -#000000 B 7 982.2 226.99 1029.73 221.13 1096.24 209.63 1113 190 1132.58 167.07 1128.66 129.23 1124.22 107.57 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 1126.63 107.13 1122.69 100.85 1121.86 108.22 ",
		_ldraw_="F 8 9 -Helvetica c 7 -#000000 T 1139.5 155.6 0 25 5 -assay ",
		label=assay,
		lp="1139.5,157.5",
		pos="e,1122.4,99.377 982.2,226.99 1029.7,221.13 1096.2,209.63 1113,190 1132.6,167.07 1128.7,129.23 1124.2,107.57"];
	data_dir -> convert_formats	[_draw_="c 7 -#000000 B 4 814.28 223.58 837.96 215.01 874.78 201.7 900.94 192.24 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 901.51 194.63 907.26 189.95 899.84 190.03 ",
		_ldraw_="F 8 9 -Helvetica c 7 -#000000 T 899 200.6 0 34 8 -data_dir ",
		label=data_dir,
		lp="899,202.5",
		pos="e,908.68,189.43 814.28,223.58 837.96,215.01 874.78,201.7 900.94,192.24"];
	scanpy_analysis -> dispersion_plot	[_draw_="c 7 -#000000 B 4 1962.03 125.56 2009.38 109.6 2112.08 74.97 2165 57.13 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 2165.77 59.45 2171.62 54.9 2164.2 54.81 ",
		pos="e,2173,54.412 1962,125.56 2009.4,109.6 2112.1,74.97 2165,57.126"];
	scanpy_analysis -> umap_plot	[_draw_="c 7 -#000000 B 4 1979.96 125.56 2062.81 109.29 2244.35 73.63 2333.51 56.11 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 2333.96 58.52 2340.36 54.77 2333.02 53.71 ",
		pos="e,2341.8,54.477 1980,125.56 2062.8,109.29 2244.3,73.628 2333.5,56.114"];
	scanpy_analysis -> filtered_data_h5ad	[_draw_="c 7 -#000000 B 7 2014.86 125.54 2120.84 113.64 2316.3 90.33 2482 63 2494.19 60.99 2507.29 58.52 2519.48 56.1 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 2519.88 58.51 2526.26 54.73 2518.92 53.71 ",
		pos="e,2527.7,54.429 2014.9,125.54 2120.8,113.64 2316.3,90.33 2482,63 2494.2,60.99 2507.3,58.522 2519.5,56.096"];
	scanpy_analysis -> umap_density_plot	[_draw_="c 7 -#000000 B 7 2036.21 125.51 2066.63 122.85 2100.2 119.86 2131 117 2344.71 97.14 2595.98 69.66 2723.56 55.41 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 2723.59 57.87 2730.28 54.66 2723.05 53.01 ",
		pos="e,2731.8,54.494 2036.2,125.51 2066.6,122.85 2100.2,119.86 2131,117 2344.7,97.137 2596,69.659 2723.6,55.413"];
	scanpy_analysis -> spatial_plot	[_draw_="c 7 -#000000 B 4 1907.37 125.56 1850.85 109.46 1727.72 74.4 1665.53 56.69 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 1666.4 54.39 1658.99 54.83 1665.06 59.1 ",
		pos="e,1657.5,54.412 1907.4,125.56 1850.8,109.46 1727.7,74.399 1665.5,56.689"];
	scanpy_analysis -> marker_gene_plot_logreg	[_draw_="c 7 -#000000 B 4 1928.75 125.56 1913.95 110.41 1882.72 78.46 1864.67 59.99 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 1866.8 58.66 1860.15 55.37 1863.29 62.08 ",
		pos="e,1859.1,54.284 1928.8,125.56 1913.9,110.41 1882.7,78.458 1864.7,59.987"];
	scanpy_analysis -> marker_gene_plot_t_test	[_draw_="c 7 -#000000 B 4 1946.01 125.56 1962.2 110.41 1996.33 78.46 2016.06 59.99 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 2017.61 61.89 2021.05 55.32 2014.26 58.31 ",
		pos="e,2022.2,54.284 1946,125.56 1962.2,110.41 1996.3,78.458 2016.1,59.987"];
	scanpy_analysis -> squidpy_analysis	[_draw_="c 7 -#000000 B 4 1831.03 128.42 1677.06 120.32 1392.62 105.35 1234.17 97.01 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 1234.41 94.57 1227.29 96.65 1234.16 99.46 ",
		_ldraw_="F 8 9 -Helvetica c 7 -#000000 T 1620 110.6 0 38 9 -h5ad_file ",
		label=h5ad_file,
		lp="1620,112.5",
		pos="e,1225.8,96.568 1831,128.42 1677.1,120.32 1392.6,105.35 1234.2,97.009"];
	convert_formats -> sdata_zarr	[_draw_="c 7 -#000000 B 7 869.67 170.5 851.1 167.88 830.71 164.92 812 162 578.48 125.61 301 76.62 185.12 55.91 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 185.87 53.55 178.55 54.73 185.01 58.38 ",
		pos="e,177.06,54.467 869.67,170.5 851.1,167.88 830.71,164.92 812,162 578.48,125.61 301,76.624 185.12,55.909"];
	convert_formats -> count_matrix_h5ad	[_draw_="c 7 -#000000 B 16 924.72 170.75 919.74 165.37 912.83 158.36 906 153 887.18 138.21 881.02 136.45 860 125 808.99 97.22 797.92 82.53 \
741 71 688.61 60.39 674.02 69.75 621 63 607.15 61.24 592.22 58.68 578.57 56.09 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 579.09 53.7 571.75 54.77 578.16 58.51 ",
		pos="e,570.27,54.477 924.72,170.75 919.74,165.37 912.83,158.36 906,153 887.18,138.21 881.02,136.45 860,125 808.99,97.22 797.92,82.533 \
741,71 688.61,60.386 674.02,69.75 621,63 607.15,61.237 592.22,58.684 578.57,56.091"];
	convert_formats -> scanpy_analysis	[_draw_="c 7 -#000000 B 7 969.93 170.51 999.05 164.4 1040.35 156.63 1077 153 1218.1 139.04 1623.08 136.44 1822.82 136.02 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 1822.79 138.47 1829.78 136.01 1822.78 133.57 ",
		_ldraw_="F 8 9 -Helvetica c 7 -#000000 T 1096 155.6 0 38 9 -h5ad_file ",
		label=h5ad_file,
		lp="1096,157.5",
		pos="e,1831.3,136.01 969.93,170.51 999.05,164.4 1040.4,156.63 1077,153 1218.1,139.04 1623.1,136.44 1822.8,136.02"];
	convert_formats -> compute_qc_results	[_draw_="c 7 -#000000 B 7 848.31 170.55 840.56 168.3 833 165.49 826 162 820.44 159.23 815.28 154.91 810.99 150.59 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 812.92 149.07 806.39 145.54 809.29 152.37 ",
		_ldraw_="F 8 9 -Helvetica c 7 -#000000 T 867.5 155.6 0 83 19 -primary_matrix_path ",
		label=primary_matrix_path,
		lp="867.5,157.5",
		pos="e,805.37,144.42 848.31,170.55 840.56,168.3 833,165.49 826,162 820.44,159.23 815.28,154.91 810.99,150.59"];
	convert_formats -> squidpy_analysis	[_draw_="c 7 -#000000 B 4 950.03 170.56 983.57 154.86 1055.69 121.1 1094.32 103.02 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 1095.36 105.24 1100.66 100.05 1093.28 100.8 ",
		_ldraw_="F 8 9 -Helvetica c 7 -#000000 T 1065.5 133.1 0 43 10 -sdata_zarr ",
		label=sdata_zarr,
		lp="1065.5,135",
		pos="e,1102,99.412 950.03,170.56 983.57,154.86 1055.7,121.1 1094.3,103.02"];
	compute_qc_results -> scanpy_qc_results	[_draw_="c 7 -#000000 B 10 794.09 125.92 784.94 111.7 763.74 82.63 737 71 707.24 58.05 477.3 66.15 445 63 428.42 61.39 410.45 58.68 394.33 \
55.89 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 394.9 53.5 387.58 54.7 394.04 58.33 ",
		pos="e,386.09,54.431 794.09,125.92 784.94,111.7 763.74,82.633 737,71 707.24,58.051 477.3,66.146 445,63 428.42,61.386 410.45,58.677 394.33,\
55.89"];
	squidpy_analysis -> interaction_matrix_plot	[_draw_="c 7 -#000000 B 7 1188.34 80.52 1221.3 76.03 1261.34 70 1297 63 1306.55 61.13 1316.77 58.79 1326.33 56.46 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 1326.87 58.85 1333.07 54.79 1325.69 54.1 ",
		pos="e,1334.5,54.424 1188.3,80.515 1221.3,76.027 1261.3,69.995 1297,63 1306.6,61.126 1316.8,58.793 1326.3,56.461"];
	squidpy_analysis -> ripley_plot	[_draw_="c 7 -#000000 B 7 1225.83 88.99 1286.93 86.82 1364.75 80.31 1432 63 1436.93 61.73 1442.03 59.87 1446.82 57.84 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 1447.79 60.1 1453.15 54.97 1445.77 55.63 ",
		pos="e,1454.5,54.348 1225.8,88.993 1286.9,86.816 1364.8,80.307 1432,63 1436.9,61.731 1442,59.872 1446.8,57.845"];
	squidpy_analysis -> centrality_scores_plot	[_draw_="c 7 -#000000 B 10 1033.13 80.51 997.21 77.21 955.12 73.6 917 71 842.42 65.92 822.91 74.16 749 63 739.04 61.5 728.4 59.11 718.64 \
56.6 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 719.54 54.3 712.14 54.86 718.27 59.04 ",
		pos="e,710.68,54.474 1033.1,80.512 997.21,77.206 955.12,73.597 917,71 842.42,65.92 822.91,74.159 749,63 739.04,61.496 728.4,59.111 718.64,\
56.599"];
	squidpy_analysis -> neighborhood_enrichment_plot	[_draw_="c 7 -#000000 B 7 1047.07 80.55 1009.35 75.91 962.62 69.73 921 63 908.4 60.96 894.84 58.48 882.23 56.06 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 882.92 53.7 875.58 54.77 881.98 58.51 ",
		pos="e,874.1,54.476 1047.1,80.551 1009.4,75.909 962.62,69.732 921,63 908.4,60.962 894.84,58.484 882.23,56.058"];
	squidpy_analysis -> squidpy_annotated_h5ad	[_draw_="c 7 -#000000 B 4 1094.51 80.5 1074.46 73.82 1046.35 64.45 1024.48 57.16 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 1025.28 54.85 1017.87 54.96 1023.74 59.49 ",
		pos="e,1016.4,54.478 1094.5,80.505 1074.5,73.82 1046.3,64.449 1024.5,57.16"];
	squidpy_analysis -> co_occurrence_plot	[_draw_="c 7 -#000000 B 4 1120 80.71 1120 75.59 1120 68.85 1120 62.67 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 1122.45 62.78 1120 55.78 1117.55 62.78 ",
		pos="e,1120,54.265 1120,80.709 1120,75.593 1120,68.848 1120,62.666"];
	squidpy_analysis -> squidpy_spatial_plot	[_draw_="c 7 -#000000 B 4 1143.31 80.5 1161.49 73.88 1186.92 64.61 1206.85 57.35 ",
		_hdraw_="S 5 -solid c 7 -#000000 C 7 -#000000 P 3 1207.58 59.69 1213.31 55 1205.9 55.09 ",
		pos="e,1214.7,54.478 1143.3,80.505 1161.5,73.879 1186.9,64.614 1206.8,57.353"];
}