Benchmark integration #41
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as multi-dimensional observation (obsm) in the anndata itself. This is quite useful for further analysis later when calculating the batch correc. coefficients for example.
the anndata object in obsm.
Heavily based on how scGPT does it with scib.
bputzeys
commented
Jul 4, 2024
| @@ -4,6 +4,7 @@ on: | |||
| pull_request: | |||
| branches: | |||
| - main | |||
| - release | |||
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run GitHub Actions check on release branch
bputzeys
commented
Jul 4, 2024
| @@ -113,7 +114,7 @@ def process_data(self, | |||
| # map gene symbols to ensemble ids if provided | |||
| if gene_column_name != "ensembl_id": | |||
| mappings = pkl.load(open(files_config["mapping_path"], 'rb')) | |||
| data.var['ensembl_id'] = data.var[gene_column_name].apply(lambda x: mappings.get(x,{"id":None})['id']) | |||
| self.adata.var['ensembl_id'] = self.adata.var[gene_column_name].apply(lambda x: mappings.get(x,{"id":None})['id']) | |||
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the next PR will do this outside the models!
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