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Describe the bug
"Hi, I am trying to use region_to_gene in the Snakemake pipeline, but I encountered an error: 'ValueError: Input y contains NaN.'"
To Reproduce
scenicplus grn_inference region_to_gene
--multiome_mudata_fname /home/may/vscode/scv/pscturoial/outs_scenic/ACC_GEX.h5mu
--search_space_fname /home/may/vscode/scv/pscturoial/outs_scenic/search_space.tsv
--temp_dir /home/may/vscode/scv/pscturoial/tmp
--out_region_to_gene_adjacencies /home/may/vscode/scv/pscturoial/outs_scenic/region_to_gene_adj.tsv
--importance_scoring_method GBM
--correlation_scoring_method SR
--n_cpu 8
Error output
2024-10-15 15:36:47,975 SCENIC+ INFO Reading multiome MuData.
/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/anndata/_core/anndata.py:522: FutureWarning: The dtype argument is deprecated and will be removed in late 2024.
warnings.warn(
/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/anndata/_core/anndata.py:522: FutureWarning: The dtype argument is deprecated and will be removed in late 2024.
warnings.warn(
2024-10-15 15:36:49,617 SCENIC+ INFO Reading search space
2024-10-15 15:36:49,701 R2G INFO Calculating region to gene importances, using GBM method
Running using 1 cores: 0%| | 0/3806 [00:00<?, ?it/s]Traceback (most recent call last):
File "/home/may/miniconda3/envs/scep3118/bin/scenicplus", line 8, in
sys.exit(main())
^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/scenicplus/cli/scenicplus.py", line 1137, in main
args.func(args)
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/scenicplus/cli/scenicplus.py", line 330, in TF_to_gene
infer_region_to_gene(
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/scenicplus/cli/commands.py", line 739, in infer_region_to_gene
adj = calculate_regions_to_genes_relationships(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/scenicplus/enhancer_to_gene.py", line 261, in calculate_regions_to_genes_relationships
region_to_gene_importances = _score_regions_to_genes(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/scenicplus/enhancer_to_gene.py", line 219, in _score_regions_to_genes
joblib.Parallel(
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/joblib/parallel.py", line 1863, in call
return output if self.return_generator else list(output)
^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/joblib/parallel.py", line 1792, in _get_sequential_output
res = func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/scenicplus/enhancer_to_gene.py", line 143, in _score_regions_to_single_gene
fitted_model = arboreto_core.fit_model(regressor_type=regressor_type,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/arboreto/core.py", line 143, in fit_model
return do_sklearn_regression()
^^^^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/arboreto/core.py", line 138, in do_sklearn_regression
regressor.fit(tf_matrix, target_gene_expression)
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/sklearn/base.py", line 1152, in wrapper
return fit_method(estimator, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/sklearn/ensemble/_gb.py", line 416, in fit
X, y = self._validate_data(
^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/sklearn/base.py", line 622, in _validate_data
X, y = check_X_y(X, y, **check_params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/sklearn/utils/validation.py", line 1162, in check_X_y
y = _check_y(y, multi_output=multi_output, y_numeric=y_numeric, estimator=estimator)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/sklearn/utils/validation.py", line 1172, in _check_y
y = check_array(
^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/sklearn/utils/validation.py", line 957, in check_array
_assert_all_finite(
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/sklearn/utils/validation.py", line 122, in _assert_all_finite
_assert_all_finite_element_wise(
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/sklearn/utils/validation.py", line 171, in _assert_all_finite_element_wise
raise ValueError(msg_err)
ValueError: Input y contains NaN.
Version (please complete the following information):
Python: 3.11.8
SCENIC+: 1.0a1
Additional context
The data is example data from tutorial 10x: Flash-Frozen Human Healthy Brain Tissue (3k)
The text was updated successfully, but these errors were encountered:
Describe the bug
"Hi, I am trying to use region_to_gene in the Snakemake pipeline, but I encountered an error: 'ValueError: Input y contains NaN.'"
To Reproduce
scenicplus grn_inference region_to_gene
--multiome_mudata_fname /home/may/vscode/scv/pscturoial/outs_scenic/ACC_GEX.h5mu
--search_space_fname /home/may/vscode/scv/pscturoial/outs_scenic/search_space.tsv
--temp_dir /home/may/vscode/scv/pscturoial/tmp
--out_region_to_gene_adjacencies /home/may/vscode/scv/pscturoial/outs_scenic/region_to_gene_adj.tsv
--importance_scoring_method GBM
--correlation_scoring_method SR
--n_cpu 8
Error output
2024-10-15 15:36:47,975 SCENIC+ INFO Reading multiome MuData.
/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/anndata/_core/anndata.py:522: FutureWarning: The dtype argument is deprecated and will be removed in late 2024.
warnings.warn(
/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/anndata/_core/anndata.py:522: FutureWarning: The dtype argument is deprecated and will be removed in late 2024.
warnings.warn(
2024-10-15 15:36:49,617 SCENIC+ INFO Reading search space
2024-10-15 15:36:49,701 R2G INFO Calculating region to gene importances, using GBM method
Running using 1 cores: 0%| | 0/3806 [00:00<?, ?it/s]Traceback (most recent call last):
File "/home/may/miniconda3/envs/scep3118/bin/scenicplus", line 8, in
sys.exit(main())
^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/scenicplus/cli/scenicplus.py", line 1137, in main
args.func(args)
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/scenicplus/cli/scenicplus.py", line 330, in TF_to_gene
infer_region_to_gene(
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/scenicplus/cli/commands.py", line 739, in infer_region_to_gene
adj = calculate_regions_to_genes_relationships(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/scenicplus/enhancer_to_gene.py", line 261, in calculate_regions_to_genes_relationships
region_to_gene_importances = _score_regions_to_genes(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/scenicplus/enhancer_to_gene.py", line 219, in _score_regions_to_genes
joblib.Parallel(
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/joblib/parallel.py", line 1863, in call
return output if self.return_generator else list(output)
^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/joblib/parallel.py", line 1792, in _get_sequential_output
res = func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/scenicplus/enhancer_to_gene.py", line 143, in _score_regions_to_single_gene
fitted_model = arboreto_core.fit_model(regressor_type=regressor_type,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/arboreto/core.py", line 143, in fit_model
return do_sklearn_regression()
^^^^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/arboreto/core.py", line 138, in do_sklearn_regression
regressor.fit(tf_matrix, target_gene_expression)
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/sklearn/base.py", line 1152, in wrapper
return fit_method(estimator, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/sklearn/ensemble/_gb.py", line 416, in fit
X, y = self._validate_data(
^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/sklearn/base.py", line 622, in _validate_data
X, y = check_X_y(X, y, **check_params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/sklearn/utils/validation.py", line 1162, in check_X_y
y = _check_y(y, multi_output=multi_output, y_numeric=y_numeric, estimator=estimator)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/sklearn/utils/validation.py", line 1172, in _check_y
y = check_array(
^^^^^^^^^^^^
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/sklearn/utils/validation.py", line 957, in check_array
_assert_all_finite(
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/sklearn/utils/validation.py", line 122, in _assert_all_finite
_assert_all_finite_element_wise(
File "/home/may/miniconda3/envs/scep3118/lib/python3.11/site-packages/sklearn/utils/validation.py", line 171, in _assert_all_finite_element_wise
raise ValueError(msg_err)
ValueError: Input y contains NaN.
Version (please complete the following information):
Additional context
The data is example data from tutorial 10x: Flash-Frozen Human Healthy Brain Tissue (3k)
The text was updated successfully, but these errors were encountered: