Open bazoogis opened 2 weeks ago
YazdanZ
commented
2 weeks ago Hi,
can you provide us with the .cfg file that you used? Did you use the provided one without any modifications?
The problem seems to be the number of genes in the GEX matrix (1 instead of 1000).
lryup
commented
1 week ago I have the same mistake.
you need change code:
real_cells_df = pd.DataFrame.sparse.from_spmatrix(real_cells.X, index=real_cells.obs_names, columns=real_cells.var_names)
bazoogis
commented
1 week ago Hi,
can you provide us with the .cfg file that you used? Did you use the provided one without any modifications?
The problem seems to be the number of genes in the GEX matrix (1 instead of 1000).
It's the same .cfg file as was provided, I only made slight folder modifications. Nevertheless, I attach it here.
I have the same mistake.
you need change code:
real_cells_df = pd.DataFrame.sparse.from_spmatrix(real_cells.X, index=real_cells.obs_names, columns=real_cells.var_names)
Thanks, this seems to have gotten over this issue, although I'm getting a different error now:
parsing input
creating dask graph
shutting down client and local cluster
finished
Traceback (most recent call last):
File "/home/vzogop/GRouNdGAN/src/main.py", line 41, in
Best Regards, Bill
lryup
commented
1 week ago I am not modifying any folders, and .cfg files. After the correction,
TFs = list(set(TFs).intersection(gene_names))
# 李荣远修正错误
# preparing GRNBoost2's input
real_cells_df = pd.DataFrame.sparse.from_spmatrix(real_cells.X, index=real_cells.obs_names, columns=real_cells.var_names)
# real_cells_df = pd.DataFrame(real_cells.X, index=real_cells.obs_names,columns=real_cells.var_names)
# we can optionally pass a list of TFs to GRNBoost2
print(f"Using {len(TFs)} TFs for GRN inference.")
real_grn = grnboost2(real_cells_df, tf_names=TFs, verbose=True, seed=1)
real_grn.to_csv(cfg.get("GRN Preparation", "Inferred GRN"))run the following command. $ python src/main.py --config configs/causal_gan.cfg --create_grn
The results are the same as the authors.
TFs 63 Targets 937 Genes 1000 Possible Edges 59031 Imposed Edges 14055 GRN density Edges 0.238095
bazoogis
commented
1 week ago I have already modified grn_creation.py as per your suggestion:
def create_GRN(cfg: ConfigParser) -> None: """ Infers a GRN using GRNBoost2 and uses it to construct a causal graph to impose onto GRouNdGAN.
Parameters
----------
cfg : ConfigParser
Parser for config file containing GRN creation params.
"""
real_cells = sc.read_h5ad(cfg.get("Data", "train"))
real_cells_val = sc.read_h5ad(cfg.get("Data", "validation"))
real_cells_test = sc.read_h5ad(cfg.get("Data", "test"))
# find TFs that are in highly variable genes
gene_names = real_cells.var_names.tolist()
TFs = pd.read_csv(cfg.get("GRN Preparation", "TFs"), sep="\t")["Symbol"]
TFs = list(set(TFs).intersection(gene_names))
# preparing GRNBoost2's input
#real_cells_df = pd.DataFrame(real_cells.X, columns=real_cells.var_names)
real_cells_df = pd.DataFrame.sparse.from_spmatrix(real_cells.X, index=real_cells.obs_names, columns=real_cells.var_names)
# we can optionally pass a list of TFs to GRNBoost2
print(f"Using {len(TFs)} TFs for GRN inference.")
real_grn = grnboost2(real_cells_df, tf_names=TFs, verbose=True, seed=1)
real_grn.to_csv(cfg.get("GRN Preparation", "Inferred GRN"))However, the same error persists:
finished Traceback (most recent call last): File "/home/vzogop/GRouNdGAN/src/main.py", line 41, in grn_creation.create_GRN(cfg_parser) File "/home/vzogop/GRouNdGAN/src/preprocessing/grn_creation.py", line 35, in create_GRN real_grn = grnboost2(real_cells_df, tf_names=TFs, verbose=True, seed=1) File "/home/vzogop/miniconda3/envs/myenv/lib/python3.9/site-packages/arboreto/algo.py", line 39, in grnboost2 return diy(expression_data=expression_data, regressor_type='GBM', regressor_kwargs=SGBM_KWARGS, File "/home/vzogop/miniconda3/envs/myenv/lib/python3.9/site-packages/arboreto/algo.py", line 120, in diy graph = create_graph(expression_matrix, File "/home/vzogop/miniconda3/envs/myenv/lib/python3.9/site-packages/arboreto/core.py", line 450, in create_graph all_meta_df = from_delayed(delayed_meta_dfs, meta=_META_SCHEMA) File "/home/vzogop/miniconda3/envs/myenv/lib/python3.9/site-packages/dask_expr/io/_delayed.py", line 101, in from_delayed raise TypeError("Must supply at least one delayed object") TypeError: Must supply at least one delayed object
Could the error be attributed to a mismatch n the installed packages versions?
Hello,
I am trying to run the tutorial for GRouNdGAN, using the PBMC example, having kept the folder structure as is.
I have successfully run the preprocess command and the train, test and validation files are created.
However, during the next step - create_grn, I get the following error:
File "/home/vzogop/GRouNdGAN/src/main.py", line 41, in
grn_creation.create_GRN(cfg_parser)
File "/home/vzogop/GRouNdGAN/src/preprocessing/grn_creation.py", line 30, in create_GRN
real_cells_df = pd.DataFrame(real_cells.X, columns=real_cells.var_names)
File "/home/vzogop/miniconda3/envs/myenv/lib/python3.9/site-packages/pandas/core/frame.py", line 867, in init
mgr = ndarray_to_mgr(
File "/home/vzogop/miniconda3/envs/myenv/lib/python3.9/site-packages/pandas/core/internals/construction.py", line 336, in ndarray_to_mgr
_check_values_indices_shape_match(values, index, columns)
File "/home/vzogop/miniconda3/envs/myenv/lib/python3.9/site-packages/pandas/core/internals/construction.py", line 420, in _check_values_indices_shape_match
raise ValueError(f"Shape of passed values is {passed}, indices imply {implied}")
ValueError: Shape of passed values is (66579, 1), indices imply (66579, 1000)
As shown, I am using a python 3.9 environment created using miniconda to run GRouNdGAN.
Best Regards, Bill