diff vitessce_spatial.py @ 0:9f60ef2d586e draft

planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/vitessce commit 9b2dc921e692af8045773013d9f87d4d790e2ea1

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/vitessce_spatial.py	Thu Sep 08 17:23:33 2022 +0000
@@ -0,0 +1,121 @@
+import argparse
+import json
+import warnings
+from pathlib import Path
+
+import scanpy as sc
+from anndata import read_h5ad
+from vitessce import (
+    AnnDataWrapper,
+    Component as cm,
+    MultiImageWrapper,
+    OmeTiffWrapper,
+    VitessceConfig,
+)
+
+
+def main(inputs, output, image, anndata=None, masks=None):
+    """
+    Parameter
+    ---------
+    inputs : str
+        File path to galaxy tool parameter.
+    output : str
+        Output folder for saving web content.
+    image : str
+        File path to the OME Tiff image.
+    anndata : str
+        File path to anndata containing phenotyping info.
+    masks : str
+        File path to the image masks.
+    """
+    warnings.simplefilter('ignore')
+
+    with open(inputs, 'r') as param_handler:
+        params = json.load(param_handler)
+
+    vc = VitessceConfig(name=None, description=None)
+    dataset = vc.add_dataset()
+    image_wrappers = [OmeTiffWrapper(img_path=image, name='OMETIFF')]
+    if masks:
+        image_wrappers.append(
+            OmeTiffWrapper(img_path=masks, name='MASKS', is_bitmask=True)
+        )
+    dataset.add_object(MultiImageWrapper(image_wrappers))
+
+    status = vc.add_view(dataset, cm.STATUS)
+    spatial = vc.add_view(dataset, cm.SPATIAL)
+    lc = vc.add_view(dataset, cm.LAYER_CONTROLLER)
+
+    if not anndata:
+        vc.layout(status / lc | spatial)
+        config_dict = vc.export(to='files', base_url='http://localhost', out_dir=output)
+        with open(Path(output).joinpath('config.json'), 'w') as f:
+            json.dump(config_dict, f, indent=4)
+        return
+
+    adata = read_h5ad(anndata)
+
+    params = params['do_phenotyping']
+    embedding = params['scatterplot_embeddings']['embedding']
+    embedding_options = params['scatterplot_embeddings']['options']
+    if embedding == 'umap':
+        sc.pp.neighbors(adata, **embedding_options)
+        sc.tl.umap(adata)
+        mappings_obsm = 'X_umap'
+        mappings_obsm_name = "UMAP"
+    elif embedding == 'tsne':
+        sc.tl.tsne(adata, **embedding_options)
+        mappings_obsm = 'X_tsne'
+        mappings_obsm_name = "tSNE"
+    else:         # pca
+        sc.tl.pca(adata, **embedding_options)
+        mappings_obsm = 'X_pca'
+        mappings_obsm_name = "PCA"
+
+    adata.obsm['XY_centroid'] = adata.obs[['X_centroid', 'Y_centroid']].values
+
+    cell_set_obs = params['phenotype_factory']['phenotypes']
+    if not isinstance(cell_set_obs, list):
+        cell_set_obs = [x.strip() for x in cell_set_obs.split(',')]
+    cell_set_obs_names = [obj[0].upper() + obj[1:] for obj in cell_set_obs]
+    dataset.add_object(
+        AnnDataWrapper(
+            adata,
+            mappings_obsm=[mappings_obsm],
+            mappings_obsm_names=[mappings_obsm_name],
+            spatial_centroid_obsm='XY_centroid',
+            cell_set_obs=cell_set_obs,
+            cell_set_obs_names=cell_set_obs_names,
+            expression_matrix="X"
+        )
+    )
+
+    cellsets = vc.add_view(dataset, cm.CELL_SETS)
+    scattorplot = vc.add_view(dataset, cm.SCATTERPLOT, mapping=mappings_obsm_name)
+    heatmap = vc.add_view(dataset, cm.HEATMAP)
+    genes = vc.add_view(dataset, cm.GENES)
+    cell_set_sizes = vc.add_view(dataset, cm.CELL_SET_SIZES)
+    cell_set_expression = vc.add_view(dataset, cm.CELL_SET_EXPRESSION)
+    vc.layout(
+        (status / genes / cell_set_expression)
+        | (cellsets / lc / scattorplot)
+        | (cell_set_sizes / heatmap / spatial)
+    )
+    config_dict = vc.export(to='files', base_url='http://localhost', out_dir=output)
+
+    with open(Path(output).joinpath('config.json'), 'w') as f:
+        json.dump(config_dict, f, indent=4)
+
+
+if __name__ == '__main__':
+    aparser = argparse.ArgumentParser()
+    aparser.add_argument("-i", "--inputs", dest="inputs", required=True)
+    aparser.add_argument("-e", "--output", dest="output", required=True)
+    aparser.add_argument("-g", "--image", dest="image", required=True)
+    aparser.add_argument("-a", "--anndata", dest="anndata", required=False)
+    aparser.add_argument("-m", "--masks", dest="masks", required=False)
+
+    args = aparser.parse_args()
+
+    main(args.inputs, args.output, args.image, args.anndata, args.masks)