bengrn
  • Home

example notebook

  • Omnipath
  • Genome-wide perturb-seq
  • Mc Calla et al.

documentation

  • base
  • genie3
bengrn
  • example notebook
  • Omnipath

Omnipath¶

In [1]:
Copied!
from bengrn.base import train_classifier
from bengrn import compute_genie3, BenGRN
from grnndata import utils as grnutils

import pandas as pd
import scanpy as sc
from anndata.utils import make_index_unique

%load_ext autoreload
%autoreload 2 

import torch
torch.set_float32_matmul_precision('medium')
from bengrn.base import train_classifier from bengrn import compute_genie3, BenGRN from grnndata import utils as grnutils import pandas as pd import scanpy as sc from anndata.utils import make_index_unique %load_ext autoreload %autoreload 2 import torch torch.set_float32_matmul_precision('medium')
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/site-packages/torch/cuda/__init__.py:546: UserWarning: Can't initialize NVML
  warnings.warn("Can't initialize NVML")
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/site-packages/bitsandbytes/cextension.py:31: UserWarning: The installed version of bitsandbytes was compiled without GPU support. 8-bit optimizers, 8-bit multiplication, and GPU quantization are unavailable.
  warn("The installed version of bitsandbytes was compiled without GPU support. "
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/site-packages/bitsandbytes/libbitsandbytes_cpu.so: undefined symbol: cadam32bit_grad_fp32
💡 connected lamindb: jkobject/scprint
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/site-packages/umap/__init__.py:9: ImportWarning: Tensorflow not installed; ParametricUMAP will be unavailable
  warn(
In [2]:
Copied!
NUM_GENES = 5000
MAXCELLS = 1024
NUM_GENES = 5000 MAXCELLS = 1024
In [3]:
Copied!
CELLTYPES = [
    'kidney distal convoluted tubule epithelial cell',
    'kidney loop of Henle thick ascending limb epithelial cell',
    'kidney collecting duct principal cell',
    'mesangial cell',
    'blood vessel smooth muscle cell',
    'podocyte',
    'macrophage',
    'leukocyte',
    'kidney interstitial fibroblast',
   # 'endothelial cell'
]
CELLTYPES = [ 'kidney distal convoluted tubule epithelial cell', 'kidney loop of Henle thick ascending limb epithelial cell', 'kidney collecting duct principal cell', 'mesangial cell', 'blood vessel smooth muscle cell', 'podocyte', 'macrophage', 'leukocyte', 'kidney interstitial fibroblast', # 'endothelial cell' ]
In [4]:
Copied!
#adata = sc.read_h5ad('/home/ml4ig1/scprint/.lamindb/yBCKp6HmXuHa0cZptMo7.h5ad')
adata = sc.read_h5ad('../data/yBCKp6HmXuHa0cZptMo7.h5ad')
adata.var["isTF"] = False
adata.var.loc[adata.var.symbol.isin(grnutils.TF), "isTF"] = True
adata
#adata = sc.read_h5ad('/home/ml4ig1/scprint/.lamindb/yBCKp6HmXuHa0cZptMo7.h5ad') adata = sc.read_h5ad('../data/yBCKp6HmXuHa0cZptMo7.h5ad') adata.var["isTF"] = False adata.var.loc[adata.var.symbol.isin(grnutils.TF), "isTF"] = True adata
Out[4]:
View of AnnData object with n_obs × n_vars = 15728 × 23149
    obs: 'donor_id', 'self_reported_ethnicity_ontology_term_id', 'organism_ontology_term_id', 'sample_uuid', 'sample_preservation_method', 'tissue_ontology_term_id', 'development_stage_ontology_term_id', 'tissue_section_uuid', 'tissue_section_thickness', 'library_uuid', 'assay_ontology_term_id', 'mapped_reference_annotation', 'is_primary_data', 'cell_type_ontology_term_id', 'author_cell_type', 'disease_ontology_term_id', 'sex_ontology_term_id', 'suspension_type', 'cell_type', 'assay', 'disease', 'organism', 'sex', 'tissue', 'self_reported_ethnicity', 'development_stage', 'cell_culture', 'nnz', 'n_genes_by_counts', 'log1p_n_genes_by_counts', 'total_counts', 'log1p_total_counts', 'pct_counts_in_top_20_genes', 'total_counts_mt', 'log1p_total_counts_mt', 'pct_counts_mt', 'total_counts_ribo', 'log1p_total_counts_ribo', 'pct_counts_ribo', 'total_counts_hb', 'log1p_total_counts_hb', 'pct_counts_hb', 'outlier', 'mt_outlier', 'leiden_3', 'leiden_2', 'leiden_1', 'dpt_group', 'heat_diff', 'proliferation', 'apoptosis', 'normalized_growth'
    var: 'feature_is_filtered', 'feature_name', 'feature_reference', 'feature_biotype', 'ncbi_gene_id', 'biotype', 'description', 'synonyms', 'mt', 'ribo', 'hb', 'n_cells_by_counts', 'mean_counts', 'log1p_mean_counts', 'pct_dropout_by_counts', 'total_counts', 'log1p_total_counts', 'symbol', 'isTF'
    uns: 'T_fwd_params', 'diffmap_evals', 'iroot', 'leiden', 'neighbors', 'umap', 'unseen_genes'
    obsm: 'X_diffmap', 'X_pca', 'X_umap', 'clean_pca'
    layers: 'clean'
    obsp: 'T_fwd', 'connectivities', 'distances'
In [5]:
Copied!
adata.obs['current'] = "other"
adata.obs.loc[adata.obs['cell_type']=="podocyte", 'current'] = "podocyte"
adata.obs['current'] = "other" adata.obs.loc[adata.obs['cell_type']=="podocyte", 'current'] = "podocyte"
In [6]:
Copied!
sc.pl.umap(adata, color='current', palette=['grey', 'green'])
sc.pl.umap(adata, color='current', palette=['grey', 'green'])
... storing 'current' as categorical
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/site-packages/scanpy/plotting/_tools/scatterplots.py:1234: FutureWarning: The default value of 'ignore' for the `na_action` parameter in pandas.Categorical.map is deprecated and will be changed to 'None' in a future version. Please set na_action to the desired value to avoid seeing this warning
  color_vector = pd.Categorical(values.map(color_map))
No description has been provided for this image
In [7]:
Copied!
sc.pl.umap(adata, color=['cell_type'])
sc.pl.umap(adata, color=['cell_type'])
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/site-packages/scanpy/plotting/_tools/scatterplots.py:1234: FutureWarning: The default value of 'ignore' for the `na_action` parameter in pandas.Categorical.map is deprecated and will be changed to 'None' in a future version. Please set na_action to the desired value to avoid seeing this warning
  color_vector = pd.Categorical(values.map(color_map))
No description has been provided for this image
In [8]:
Copied!
sc.tl.rank_genes_groups(
    adata, groupby="cell_type"
)
adata.var['ensembl_id'] = adata.var.index
adata = adata[adata.X.sum(1) > 500]
shapes = []
metrics = {}
for celltype in CELLTYPES:
    to_use = adata.uns["rank_genes_groups"]["names"][celltype][
        : NUM_GENES
    ].tolist()
    subadata = adata[adata.obs.cell_type == celltype][:MAXCELLS,  adata.var.index.isin(to_use)]
    genie_grn = compute_genie3(
        subadata, nthreads=20, regulators=adata.var[adata.var.isTF].index.tolist())
    genie_grn.var.index = make_index_unique(
        genie_grn.var['symbol'].astype(str))
    print(celltype, genie_grn.shape)
    metrics['genie3_tf_'+celltype] = BenGRN(genie_grn,
                                            do_auc=True, doplot=True).scprint_benchmark()
    genie_grn = compute_genie3(subadata, nthreads=20)
    genie_grn.var.index = make_index_unique(
        genie_grn.var['symbol'].astype(str))
    metrics['genie3_'+celltype] = BenGRN(genie_grn,
                                         do_auc=True, doplot=True).scprint_benchmark()
    shapes.append(genie_grn.shape[1])
sc.tl.rank_genes_groups( adata, groupby="cell_type" ) adata.var['ensembl_id'] = adata.var.index adata = adata[adata.X.sum(1) > 500] shapes = [] metrics = {} for celltype in CELLTYPES: to_use = adata.uns["rank_genes_groups"]["names"][celltype][ : NUM_GENES ].tolist() subadata = adata[adata.obs.cell_type == celltype][:MAXCELLS, adata.var.index.isin(to_use)] genie_grn = compute_genie3( subadata, nthreads=20, regulators=adata.var[adata.var.isTF].index.tolist()) genie_grn.var.index = make_index_unique( genie_grn.var['symbol'].astype(str)) print(celltype, genie_grn.shape) metrics['genie3_tf_'+celltype] = BenGRN(genie_grn, do_auc=True, doplot=True).scprint_benchmark() genie_grn = compute_genie3(subadata, nthreads=20) genie_grn.var.index = make_index_unique( genie_grn.var['symbol'].astype(str)) metrics['genie3_'+celltype] = BenGRN(genie_grn, do_auc=True, doplot=True).scprint_benchmark() shapes.append(genie_grn.shape[1])
WARNING: Default of the method has been changed to 't-test' from 't-test_overestim_var'
WARNING: It seems you use rank_genes_groups on the raw count data. Please logarithmize your data before calling rank_genes_groups.
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 74.96 seconds
base enrichment
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
Top central genes: []
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  14.705882352941176 % TFs

_________________________________________
loading GT,  omnipath
intersection of 3565 genes
intersection pct: 0.713
precision:  0.004541789382676131 
recall:  0.33513633669235326 
random precision: 0.001062203773751226
  0%|          | 0/128 [00:00<?, ?it/s]
  4%|▍         | 5/128 [00:00<00:02, 46.25it/s]
  8%|▊         | 10/128 [00:00<00:02, 46.20it/s]
 12%|█▏        | 15/128 [00:00<00:02, 46.14it/s]
 16%|█▌        | 20/128 [00:00<00:02, 46.23it/s]
 20%|█▉        | 25/128 [00:00<00:02, 46.28it/s]
 23%|██▎       | 30/128 [00:00<00:02, 46.30it/s]
 27%|██▋       | 35/128 [00:00<00:02, 46.25it/s]
 31%|███▏      | 40/128 [00:00<00:01, 46.24it/s]
 35%|███▌      | 45/128 [00:00<00:01, 46.29it/s]
 39%|███▉      | 50/128 [00:01<00:01, 46.31it/s]
 43%|████▎     | 55/128 [00:01<00:01, 46.30it/s]
 47%|████▋     | 60/128 [00:01<00:01, 46.32it/s]
 51%|█████     | 65/128 [00:01<00:01, 46.25it/s]
 55%|█████▍    | 70/128 [00:01<00:01, 46.23it/s]
 59%|█████▊    | 75/128 [00:01<00:01, 46.26it/s]
 62%|██████▎   | 80/128 [00:01<00:01, 46.23it/s]
 66%|██████▋   | 85/128 [00:01<00:00, 46.17it/s]
 70%|███████   | 90/128 [00:01<00:00, 46.06it/s]
 74%|███████▍  | 95/128 [00:02<00:00, 46.14it/s]
 78%|███████▊  | 100/128 [00:02<00:00, 46.19it/s]
 82%|████████▏ | 105/128 [00:02<00:00, 46.21it/s]
 86%|████████▌ | 110/128 [00:02<00:00, 46.19it/s]
 90%|████████▉ | 115/128 [00:02<00:00, 46.24it/s]
 94%|█████████▍| 120/128 [00:02<00:00, 46.28it/s]
 98%|█████████▊| 125/128 [00:02<00:00, 46.29it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:02<00:00, 46.20it/s]

Average Precision (AP):  0.0028506585986099184
Area Under Precision-Recall Curve (AUPRC):  0.00252355640477646
EPR: 5.849284104972232
No description has been provided for this image
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 262.67 seconds
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
base enrichment
Top central genes: []
No description has been provided for this image
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  2.9411764705882355 % TFs

_________________________________________
loading GT,  omnipath
intersection of 3565 genes
intersection pct: 0.713
precision:  0.0011096698483979172 
recall:  0.6956135151155898 
random precision: 0.001062203773751226
  0%|          | 0/128 [00:00<?, ?it/s]
  4%|▍         | 5/128 [00:00<00:02, 45.40it/s]
  8%|▊         | 10/128 [00:00<00:02, 45.34it/s]
 12%|█▏        | 15/128 [00:00<00:02, 45.27it/s]
 16%|█▌        | 20/128 [00:00<00:02, 45.31it/s]
 20%|█▉        | 25/128 [00:00<00:02, 45.33it/s]
 23%|██▎       | 30/128 [00:00<00:02, 45.31it/s]
 27%|██▋       | 35/128 [00:00<00:02, 45.35it/s]
 31%|███▏      | 40/128 [00:00<00:01, 45.37it/s]
 35%|███▌      | 45/128 [00:00<00:01, 45.38it/s]
 39%|███▉      | 50/128 [00:01<00:01, 45.39it/s]
 43%|████▎     | 55/128 [00:01<00:01, 45.37it/s]
 47%|████▋     | 60/128 [00:01<00:01, 45.37it/s]
 51%|█████     | 65/128 [00:01<00:01, 45.32it/s]
 55%|█████▍    | 70/128 [00:01<00:01, 45.34it/s]
 59%|█████▊    | 75/128 [00:01<00:01, 45.35it/s]
 62%|██████▎   | 80/128 [00:01<00:01, 45.36it/s]
 66%|██████▋   | 85/128 [00:01<00:00, 45.36it/s]
 70%|███████   | 90/128 [00:01<00:00, 45.39it/s]
 74%|███████▍  | 95/128 [00:02<00:00, 45.38it/s]
 78%|███████▊  | 100/128 [00:02<00:00, 45.34it/s]
 82%|████████▏ | 105/128 [00:02<00:00, 45.34it/s]
 86%|████████▌ | 110/128 [00:02<00:00, 45.35it/s]
 90%|████████▉ | 115/128 [00:02<00:00, 45.37it/s]
 94%|█████████▍| 120/128 [00:02<00:00, 45.35it/s]
 98%|█████████▊| 125/128 [00:02<00:00, 45.37it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:02<00:00, 45.34it/s]

Average Precision (AP):  0.001095405878733279
Area Under Precision-Recall Curve (AUPRC):  0.0010760455741965266
EPR: 1.7466859320820376
No description has been provided for this image
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 40.44 seconds
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
base enrichment
Top central genes: []
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  10.0 % TFs

_________________________________________
loading GT,  omnipath
intersection of 3514 genes
intersection pct: 0.7028
precision:  0.006271091258494464 
recall:  0.40673661698857183 
random precision: 0.0012121008868434197
  0%|          | 0/128 [00:00<?, ?it/s]
  4%|▍         | 5/128 [00:00<00:02, 47.73it/s]
  8%|▊         | 10/128 [00:00<00:02, 47.67it/s]
 12%|█▏        | 15/128 [00:00<00:02, 47.71it/s]
 16%|█▌        | 20/128 [00:00<00:02, 47.72it/s]
 20%|█▉        | 25/128 [00:00<00:02, 47.69it/s]
 23%|██▎       | 30/128 [00:00<00:02, 47.68it/s]
 27%|██▋       | 35/128 [00:00<00:01, 47.65it/s]
 31%|███▏      | 40/128 [00:00<00:01, 47.68it/s]
 35%|███▌      | 45/128 [00:00<00:01, 47.65it/s]
 39%|███▉      | 50/128 [00:01<00:01, 47.66it/s]
 43%|████▎     | 55/128 [00:01<00:01, 47.71it/s]
 47%|████▋     | 60/128 [00:01<00:01, 47.75it/s]
 51%|█████     | 65/128 [00:01<00:01, 47.69it/s]
 55%|█████▍    | 70/128 [00:01<00:01, 47.66it/s]
 59%|█████▊    | 75/128 [00:01<00:01, 47.69it/s]
 62%|██████▎   | 80/128 [00:01<00:01, 47.70it/s]
 66%|██████▋   | 85/128 [00:01<00:00, 47.69it/s]
 70%|███████   | 90/128 [00:01<00:00, 47.71it/s]
 74%|███████▍  | 95/128 [00:01<00:00, 47.73it/s]
 78%|███████▊  | 100/128 [00:02<00:00, 47.73it/s]
 82%|████████▏ | 105/128 [00:02<00:00, 47.68it/s]
 86%|████████▌ | 110/128 [00:02<00:00, 47.67it/s]
 90%|████████▉ | 115/128 [00:02<00:00, 47.67it/s]
 94%|█████████▍| 120/128 [00:02<00:00, 47.69it/s]
 98%|█████████▊| 125/128 [00:02<00:00, 47.69it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:02<00:00, 47.68it/s]

Average Precision (AP):  0.0038068710056600934
Area Under Precision-Recall Curve (AUPRC):  0.0033103141109521303
EPR: 4.897761556952193
No description has been provided for this image
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 64.58 seconds
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
base enrichment
Top central genes: []
No description has been provided for this image
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  2.5 % TFs

_________________________________________
loading GT,  omnipath
intersection of 3514 genes
intersection pct: 0.7028
precision:  0.001285625479006546 
recall:  0.32881106729933834 
random precision: 0.0012121008868434197
  0%|          | 0/128 [00:00<?, ?it/s]
  4%|▍         | 5/128 [00:00<00:02, 47.47it/s]
  8%|▊         | 10/128 [00:00<00:02, 47.49it/s]
 12%|█▏        | 15/128 [00:00<00:02, 47.16it/s]
 16%|█▌        | 20/128 [00:00<00:02, 47.21it/s]
 20%|█▉        | 25/128 [00:00<00:02, 47.32it/s]
 23%|██▎       | 30/128 [00:00<00:02, 47.32it/s]
 27%|██▋       | 35/128 [00:00<00:01, 47.37it/s]
 31%|███▏      | 40/128 [00:00<00:01, 47.37it/s]
 35%|███▌      | 45/128 [00:00<00:01, 47.37it/s]
 39%|███▉      | 50/128 [00:01<00:01, 47.35it/s]
 43%|████▎     | 55/128 [00:01<00:01, 47.35it/s]
 47%|████▋     | 60/128 [00:01<00:01, 47.35it/s]
 51%|█████     | 65/128 [00:01<00:01, 47.38it/s]
 55%|█████▍    | 70/128 [00:01<00:01, 47.43it/s]
 59%|█████▊    | 75/128 [00:01<00:01, 47.42it/s]
 62%|██████▎   | 80/128 [00:01<00:01, 47.36it/s]
 66%|██████▋   | 85/128 [00:01<00:00, 47.34it/s]
 70%|███████   | 90/128 [00:01<00:00, 47.39it/s]
 74%|███████▍  | 95/128 [00:02<00:00, 47.41it/s]
 78%|███████▊  | 100/128 [00:02<00:00, 47.38it/s]
 82%|████████▏ | 105/128 [00:02<00:00, 47.41it/s]
 86%|████████▌ | 110/128 [00:02<00:00, 47.39it/s]
 90%|████████▉ | 115/128 [00:02<00:00, 47.45it/s]
 94%|█████████▍| 120/128 [00:02<00:00, 47.44it/s]
 98%|█████████▊| 125/128 [00:02<00:00, 47.39it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:02<00:00, 47.36it/s]

Average Precision (AP):  0.0012326445926554342
Area Under Precision-Recall Curve (AUPRC):  0.0012041101257049699
EPR: 0.7162872764286753
No description has been provided for this image
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 46.47 seconds
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
base enrichment
Top central genes: []
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  1.4285714285714286 % TFs

_________________________________________
loading GT,  omnipath
intersection of 3594 genes
intersection pct: 0.7188
precision:  0.007092883035904675 
recall:  0.4387900153522488 
random precision: 0.0013619352909207464
  0%|          | 0/128 [00:00<?, ?it/s]
  4%|▍         | 5/128 [00:00<00:02, 44.58it/s]
  8%|▊         | 10/128 [00:00<00:02, 44.62it/s]
 12%|█▏        | 15/128 [00:00<00:02, 44.66it/s]
 16%|█▌        | 20/128 [00:00<00:02, 44.64it/s]
 20%|█▉        | 25/128 [00:00<00:02, 44.61it/s]
 23%|██▎       | 30/128 [00:00<00:02, 44.60it/s]
 27%|██▋       | 35/128 [00:00<00:02, 44.63it/s]
 31%|███▏      | 40/128 [00:00<00:01, 44.65it/s]
 35%|███▌      | 45/128 [00:01<00:01, 44.62it/s]
 39%|███▉      | 50/128 [00:01<00:01, 44.60it/s]
 43%|████▎     | 55/128 [00:01<00:01, 44.64it/s]
 47%|████▋     | 60/128 [00:01<00:01, 44.58it/s]
 51%|█████     | 65/128 [00:01<00:01, 44.51it/s]
 55%|█████▍    | 70/128 [00:01<00:01, 44.54it/s]
 59%|█████▊    | 75/128 [00:01<00:01, 44.57it/s]
 62%|██████▎   | 80/128 [00:01<00:01, 44.58it/s]
 66%|██████▋   | 85/128 [00:01<00:00, 44.62it/s]
 70%|███████   | 90/128 [00:02<00:00, 44.63it/s]
 74%|███████▍  | 95/128 [00:02<00:00, 44.65it/s]
 78%|███████▊  | 100/128 [00:02<00:00, 44.67it/s]
 82%|████████▏ | 105/128 [00:02<00:00, 44.63it/s]
 86%|████████▌ | 110/128 [00:02<00:00, 44.62it/s]
 90%|████████▉ | 115/128 [00:02<00:00, 44.62it/s]
 94%|█████████▍| 120/128 [00:02<00:00, 44.29it/s]
 98%|█████████▊| 125/128 [00:02<00:00, 44.39it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:02<00:00, 44.55it/s]

Average Precision (AP):  0.005337285240454103
Area Under Precision-Recall Curve (AUPRC):  0.004757467010786939
EPR: 8.781634597124883
No description has been provided for this image
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 94.85 seconds
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
base enrichment
Top central genes: []
No description has been provided for this image
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  2.857142857142857 % TFs

_________________________________________
loading GT,  omnipath
intersection of 3594 genes
intersection pct: 0.7188
precision:  0.001539952451821791 
recall:  0.4742707681810428 
random precision: 0.0013619352909207464
  0%|          | 0/128 [00:00<?, ?it/s]
  4%|▍         | 5/128 [00:00<00:02, 44.68it/s]
  8%|▊         | 10/128 [00:00<00:02, 44.90it/s]
 12%|█▏        | 15/128 [00:00<00:02, 44.96it/s]
 16%|█▌        | 20/128 [00:00<00:02, 45.01it/s]
 20%|█▉        | 25/128 [00:00<00:02, 45.03it/s]
 23%|██▎       | 30/128 [00:00<00:02, 45.03it/s]
 27%|██▋       | 35/128 [00:00<00:02, 45.02it/s]
 31%|███▏      | 40/128 [00:00<00:01, 44.93it/s]
 35%|███▌      | 45/128 [00:01<00:01, 44.87it/s]
 39%|███▉      | 50/128 [00:01<00:01, 44.85it/s]
 43%|████▎     | 55/128 [00:01<00:01, 44.87it/s]
 47%|████▋     | 60/128 [00:01<00:01, 44.92it/s]
 51%|█████     | 65/128 [00:01<00:01, 44.96it/s]
 55%|█████▍    | 70/128 [00:01<00:01, 44.69it/s]
 59%|█████▊    | 75/128 [00:01<00:01, 44.78it/s]
 62%|██████▎   | 80/128 [00:01<00:01, 44.87it/s]
 66%|██████▋   | 85/128 [00:01<00:00, 44.92it/s]
 70%|███████   | 90/128 [00:02<00:00, 44.95it/s]
 74%|███████▍  | 95/128 [00:02<00:00, 44.98it/s]
 78%|███████▊  | 100/128 [00:02<00:00, 45.00it/s]
 82%|████████▏ | 105/128 [00:02<00:00, 45.00it/s]
 86%|████████▌ | 110/128 [00:02<00:00, 44.91it/s]
 90%|████████▉ | 115/128 [00:02<00:00, 44.94it/s]
 94%|█████████▍| 120/128 [00:02<00:00, 44.97it/s]
 98%|█████████▊| 125/128 [00:02<00:00, 45.02it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:02<00:00, 44.92it/s]

Average Precision (AP):  0.0014811949583253049
Area Under Precision-Recall Curve (AUPRC):  0.0014320894483849911
EPR: 1.5890254176610075
No description has been provided for this image
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 22.75 seconds
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
base enrichment
Top central genes: []
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  2.5641025641025643 % TFs

_________________________________________
loading GT,  omnipath
intersection of 2542 genes
intersection pct: 0.7242165242165243
precision:  0.011580584843104287 
recall:  0.1789703739679456 
random precision: 0.0012750761624232764
  0%|          | 0/128 [00:00<?, ?it/s]
  8%|▊         | 10/128 [00:00<00:01, 90.64it/s]
 16%|█▌        | 20/128 [00:00<00:01, 90.71it/s]
 23%|██▎       | 30/128 [00:00<00:01, 90.85it/s]
 31%|███▏      | 40/128 [00:00<00:00, 90.85it/s]
 39%|███▉      | 50/128 [00:00<00:00, 90.79it/s]
 47%|████▋     | 60/128 [00:00<00:00, 90.83it/s]
 55%|█████▍    | 70/128 [00:00<00:00, 90.89it/s]
 62%|██████▎   | 80/128 [00:00<00:00, 90.93it/s]
 70%|███████   | 90/128 [00:00<00:00, 90.93it/s]
 78%|███████▊  | 100/128 [00:01<00:00, 90.93it/s]
 86%|████████▌ | 110/128 [00:01<00:00, 90.94it/s]
 94%|█████████▍| 120/128 [00:01<00:00, 90.90it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:01<00:00, 90.85it/s]

Average Precision (AP):  0.003349531418887418
Area Under Precision-Recall Curve (AUPRC):  0.0030541973899464257
EPR: 9.434251628175465
No description has been provided for this image
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 23.17 seconds
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
base enrichment
Top central genes: []
No description has been provided for this image
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  2.5641025641025643 % TFs

_________________________________________
loading GT,  omnipath
intersection of 2542 genes
intersection pct: 0.7242165242165243
precision:  0.0016484163428705993 
recall:  0.0305973773676542 
random precision: 0.0012750761624232764
  0%|          | 0/128 [00:00<?, ?it/s]
  8%|▊         | 10/128 [00:00<00:01, 90.83it/s]
 16%|█▌        | 20/128 [00:00<00:01, 90.81it/s]
 23%|██▎       | 30/128 [00:00<00:01, 90.82it/s]
 31%|███▏      | 40/128 [00:00<00:00, 90.20it/s]
 39%|███▉      | 50/128 [00:00<00:00, 90.48it/s]
 47%|████▋     | 60/128 [00:00<00:00, 90.65it/s]
 55%|█████▍    | 70/128 [00:00<00:00, 90.80it/s]
 62%|██████▎   | 80/128 [00:00<00:00, 90.81it/s]
 70%|███████   | 90/128 [00:00<00:00, 90.78it/s]
 78%|███████▊  | 100/128 [00:01<00:00, 90.79it/s]
 86%|████████▌ | 110/128 [00:01<00:00, 90.85it/s]
 94%|█████████▍| 120/128 [00:01<00:00, 90.86it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:01<00:00, 90.72it/s]

Average Precision (AP):  0.001177156569385212
Area Under Precision-Recall Curve (AUPRC):  0.0012825989724762198
EPR: 1.3342748933585344
No description has been provided for this image
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 36.26 seconds
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
base enrichment
Top central genes: []
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  0.0 % TFs

_________________________________________
loading GT,  omnipath
intersection of 3595 genes
intersection pct: 0.7264093756314407
precision:  0.00896463904832305 
recall:  0.37216471129514606 
random precision: 0.0016822195546123465
  0%|          | 0/128 [00:00<?, ?it/s]
  4%|▍         | 5/128 [00:00<00:02, 44.26it/s]
  8%|▊         | 10/128 [00:00<00:02, 44.27it/s]
 12%|█▏        | 15/128 [00:00<00:02, 43.46it/s]
 16%|█▌        | 20/128 [00:00<00:02, 43.76it/s]
 20%|█▉        | 25/128 [00:00<00:02, 43.95it/s]
 23%|██▎       | 30/128 [00:00<00:02, 44.06it/s]
 27%|██▋       | 35/128 [00:00<00:02, 44.13it/s]
 31%|███▏      | 40/128 [00:00<00:01, 44.16it/s]
 35%|███▌      | 45/128 [00:01<00:01, 44.19it/s]
 39%|███▉      | 50/128 [00:01<00:01, 44.20it/s]
 43%|████▎     | 55/128 [00:01<00:01, 44.24it/s]
 47%|████▋     | 60/128 [00:01<00:01, 44.25it/s]
 51%|█████     | 65/128 [00:01<00:01, 44.23it/s]
 55%|█████▍    | 70/128 [00:01<00:01, 44.23it/s]
 59%|█████▊    | 75/128 [00:01<00:01, 44.26it/s]
 62%|██████▎   | 80/128 [00:01<00:01, 44.30it/s]
 66%|██████▋   | 85/128 [00:01<00:00, 44.29it/s]
 70%|███████   | 90/128 [00:02<00:00, 44.28it/s]
 74%|███████▍  | 95/128 [00:02<00:00, 44.29it/s]
 78%|███████▊  | 100/128 [00:02<00:00, 44.29it/s]
 82%|████████▏ | 105/128 [00:02<00:00, 44.32it/s]
 86%|████████▌ | 110/128 [00:02<00:00, 44.30it/s]
 90%|████████▉ | 115/128 [00:02<00:00, 44.29it/s]
 94%|█████████▍| 120/128 [00:02<00:00, 44.24it/s]
 98%|█████████▊| 125/128 [00:02<00:00, 44.25it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:02<00:00, 44.18it/s]

Average Precision (AP):  0.0054905113019332215
Area Under Precision-Recall Curve (AUPRC):  0.004916303339642281
EPR: 5.978256210614143
No description has been provided for this image
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 47.64 seconds
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
base enrichment
Top central genes: []
No description has been provided for this image
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  3.5714285714285716 % TFs

_________________________________________
loading GT,  omnipath
intersection of 3595 genes
intersection pct: 0.7264093756314407
precision:  0.002206980823429709 
recall:  0.2576029445594663 
random precision: 0.0016822195546123465
  0%|          | 0/128 [00:00<?, ?it/s]
  4%|▍         | 5/128 [00:00<00:02, 45.24it/s]
  8%|▊         | 10/128 [00:00<00:02, 45.20it/s]
 12%|█▏        | 15/128 [00:00<00:02, 45.17it/s]
 16%|█▌        | 20/128 [00:00<00:02, 44.98it/s]
 20%|█▉        | 25/128 [00:00<00:02, 45.09it/s]
 23%|██▎       | 30/128 [00:00<00:02, 45.07it/s]
 27%|██▋       | 35/128 [00:00<00:02, 45.15it/s]
 31%|███▏      | 40/128 [00:00<00:01, 45.16it/s]
 35%|███▌      | 45/128 [00:00<00:01, 45.03it/s]
 39%|███▉      | 50/128 [00:01<00:01, 44.93it/s]
 43%|████▎     | 55/128 [00:01<00:01, 44.87it/s]
 47%|████▋     | 60/128 [00:01<00:01, 44.83it/s]
 51%|█████     | 65/128 [00:01<00:01, 44.78it/s]
 55%|█████▍    | 70/128 [00:01<00:01, 44.77it/s]
 59%|█████▊    | 75/128 [00:01<00:01, 44.75it/s]
 62%|██████▎   | 80/128 [00:01<00:01, 44.73it/s]
 66%|██████▋   | 85/128 [00:01<00:00, 44.72it/s]
 70%|███████   | 90/128 [00:02<00:00, 44.72it/s]
 74%|███████▍  | 95/128 [00:02<00:00, 44.72it/s]
 78%|███████▊  | 100/128 [00:02<00:00, 44.68it/s]
 82%|████████▏ | 105/128 [00:02<00:00, 44.61it/s]
 86%|████████▌ | 110/128 [00:02<00:00, 44.61it/s]
 90%|████████▉ | 115/128 [00:02<00:00, 44.57it/s]
 94%|█████████▍| 120/128 [00:02<00:00, 44.58it/s]
 98%|█████████▊| 125/128 [00:02<00:00, 44.46it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:02<00:00, 44.75it/s]

Average Precision (AP):  0.0018285890904070012
Area Under Precision-Recall Curve (AUPRC):  0.0017771005963575573
EPR: 1.1218100192058453
No description has been provided for this image
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 41.59 seconds
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
base enrichment
Top central genes: []
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  0.0 % TFs

_________________________________________
loading GT,  omnipath
intersection of 3603 genes
intersection pct: 0.7206
precision:  0.008509893153340102 
recall:  0.4291732223519261 
random precision: 0.001518183918238287
  0%|          | 0/128 [00:00<?, ?it/s]
  4%|▍         | 5/128 [00:00<00:02, 44.30it/s]
  8%|▊         | 10/128 [00:00<00:02, 44.38it/s]
 12%|█▏        | 15/128 [00:00<00:02, 44.42it/s]
 16%|█▌        | 20/128 [00:00<00:02, 44.51it/s]
 20%|█▉        | 25/128 [00:00<00:02, 44.49it/s]
 23%|██▎       | 30/128 [00:00<00:02, 44.45it/s]
 27%|██▋       | 35/128 [00:00<00:02, 44.42it/s]
 31%|███▏      | 40/128 [00:00<00:01, 44.41it/s]
 35%|███▌      | 45/128 [00:01<00:01, 44.38it/s]
 39%|███▉      | 50/128 [00:01<00:01, 44.40it/s]
 43%|████▎     | 55/128 [00:01<00:01, 44.37it/s]
 47%|████▋     | 60/128 [00:01<00:01, 44.40it/s]
 51%|█████     | 65/128 [00:01<00:01, 44.46it/s]
 55%|█████▍    | 70/128 [00:01<00:01, 44.40it/s]
 59%|█████▊    | 75/128 [00:01<00:01, 44.44it/s]
 62%|██████▎   | 80/128 [00:01<00:01, 44.43it/s]
 66%|██████▋   | 85/128 [00:01<00:00, 44.49it/s]
 70%|███████   | 90/128 [00:02<00:00, 44.50it/s]
 74%|███████▍  | 95/128 [00:02<00:00, 44.53it/s]
 78%|███████▊  | 100/128 [00:02<00:00, 44.53it/s]
 82%|████████▏ | 105/128 [00:02<00:00, 44.56it/s]
 86%|████████▌ | 110/128 [00:02<00:00, 44.53it/s]
 90%|████████▉ | 115/128 [00:02<00:00, 44.45it/s]
 94%|█████████▍| 120/128 [00:02<00:00, 44.46it/s]
 98%|█████████▊| 125/128 [00:02<00:00, 44.45it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:02<00:00, 44.44it/s]

Average Precision (AP):  0.0052484975615239675
Area Under Precision-Recall Curve (AUPRC):  0.0046805414565712425
EPR: 6.145020274594569
No description has been provided for this image
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 85.88 seconds
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
base enrichment
Top central genes: []
No description has been provided for this image
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  4.25531914893617 % TFs

_________________________________________
loading GT,  omnipath
intersection of 3603 genes
intersection pct: 0.7206
precision:  0.001674633348973699 
recall:  0.4119169669593463 
random precision: 0.001518183918238287
  0%|          | 0/128 [00:00<?, ?it/s]
  4%|▍         | 5/128 [00:00<00:02, 43.73it/s]
  8%|▊         | 10/128 [00:00<00:02, 43.74it/s]
 12%|█▏        | 15/128 [00:00<00:02, 43.77it/s]
 16%|█▌        | 20/128 [00:00<00:02, 43.75it/s]
 20%|█▉        | 25/128 [00:00<00:02, 43.78it/s]
 23%|██▎       | 30/128 [00:00<00:02, 43.78it/s]
 27%|██▋       | 35/128 [00:00<00:02, 43.79it/s]
 31%|███▏      | 40/128 [00:00<00:02, 43.77it/s]
 35%|███▌      | 45/128 [00:01<00:01, 43.76it/s]
 39%|███▉      | 50/128 [00:01<00:01, 43.70it/s]
 43%|████▎     | 55/128 [00:01<00:01, 43.50it/s]
 47%|████▋     | 60/128 [00:01<00:01, 43.56it/s]
 51%|█████     | 65/128 [00:01<00:01, 43.60it/s]
 55%|█████▍    | 70/128 [00:01<00:01, 43.66it/s]
 59%|█████▊    | 75/128 [00:01<00:01, 43.70it/s]
 62%|██████▎   | 80/128 [00:01<00:01, 43.72it/s]
 66%|██████▋   | 85/128 [00:01<00:00, 43.76it/s]
 70%|███████   | 90/128 [00:02<00:00, 43.76it/s]
 74%|███████▍  | 95/128 [00:02<00:00, 43.78it/s]
 78%|███████▊  | 100/128 [00:02<00:00, 43.73it/s]
 82%|████████▏ | 105/128 [00:02<00:00, 43.76it/s]
 86%|████████▌ | 110/128 [00:02<00:00, 43.79it/s]
 90%|████████▉ | 115/128 [00:02<00:00, 43.76it/s]
 94%|█████████▍| 120/128 [00:02<00:00, 43.79it/s]
 98%|█████████▊| 125/128 [00:02<00:00, 43.81it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:02<00:00, 43.72it/s]

Average Precision (AP):  0.0015823538224594797
Area Under Precision-Recall Curve (AUPRC):  0.001539994484667556
EPR: 0.7348799242950723
No description has been provided for this image
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 31.20 seconds
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
base enrichment
Top central genes: []
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  2.4390243902439024 % TFs

_________________________________________
loading GT,  omnipath
intersection of 3411 genes
intersection pct: 0.7128526645768025
precision:  0.009331147617220653 
recall:  0.25440598453150753 
random precision: 0.0013561437852866911
  0%|          | 0/128 [00:00<?, ?it/s]
  4%|▍         | 5/128 [00:00<00:02, 49.35it/s]
  8%|▊         | 10/128 [00:00<00:02, 49.49it/s]
 12%|█▏        | 15/128 [00:00<00:02, 49.45it/s]
 16%|█▌        | 20/128 [00:00<00:02, 49.48it/s]
 20%|█▉        | 25/128 [00:00<00:02, 49.57it/s]
 23%|██▎       | 30/128 [00:00<00:01, 49.50it/s]
 27%|██▋       | 35/128 [00:00<00:01, 49.51it/s]
 31%|███▏      | 40/128 [00:00<00:01, 49.51it/s]
 35%|███▌      | 45/128 [00:00<00:01, 49.50it/s]
 39%|███▉      | 50/128 [00:01<00:01, 49.55it/s]
 43%|████▎     | 55/128 [00:01<00:01, 49.53it/s]
 47%|████▋     | 60/128 [00:01<00:01, 49.60it/s]
 51%|█████     | 65/128 [00:01<00:01, 49.58it/s]
 55%|█████▍    | 70/128 [00:01<00:01, 49.40it/s]
 59%|█████▊    | 75/128 [00:01<00:01, 49.39it/s]
 62%|██████▎   | 80/128 [00:01<00:00, 49.40it/s]
 66%|██████▋   | 85/128 [00:01<00:00, 49.53it/s]
 70%|███████   | 90/128 [00:01<00:00, 49.55it/s]
 74%|███████▍  | 95/128 [00:01<00:00, 49.53it/s]
 78%|███████▊  | 100/128 [00:02<00:00, 49.57it/s]
 82%|████████▏ | 105/128 [00:02<00:00, 49.59it/s]
 86%|████████▌ | 110/128 [00:02<00:00, 49.58it/s]
 90%|████████▉ | 115/128 [00:02<00:00, 49.60it/s]
 94%|█████████▍| 120/128 [00:02<00:00, 49.61it/s]
 98%|█████████▊| 125/128 [00:02<00:00, 49.59it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:02<00:00, 49.52it/s]

Average Precision (AP):  0.003925004962797144
Area Under Precision-Recall Curve (AUPRC):  0.0033775019219795498
EPR: 6.5477109026987135
No description has been provided for this image
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 31.60 seconds
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
base enrichment
Top central genes: []
No description has been provided for this image
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  0.0 % TFs

_________________________________________
loading GT,  omnipath
intersection of 3411 genes
intersection pct: 0.7128526645768025
precision:  0.001856214279002524 
recall:  0.07138328895651071 
random precision: 0.0013561437852866911
  0%|          | 0/128 [00:00<?, ?it/s]
  5%|▍         | 6/128 [00:00<00:02, 50.28it/s]
  9%|▉         | 12/128 [00:00<00:02, 50.48it/s]
 14%|█▍        | 18/128 [00:00<00:02, 50.55it/s]
 19%|█▉        | 24/128 [00:00<00:02, 50.59it/s]
 23%|██▎       | 30/128 [00:00<00:01, 50.66it/s]
 28%|██▊       | 36/128 [00:00<00:01, 50.70it/s]
 33%|███▎      | 42/128 [00:00<00:01, 50.11it/s]
 38%|███▊      | 48/128 [00:00<00:01, 50.29it/s]
 42%|████▏     | 54/128 [00:01<00:01, 50.42it/s]
 47%|████▋     | 60/128 [00:01<00:01, 50.50it/s]
 52%|█████▏    | 66/128 [00:01<00:01, 50.57it/s]
 56%|█████▋    | 72/128 [00:01<00:01, 50.52it/s]
 61%|██████    | 78/128 [00:01<00:00, 50.58it/s]
 66%|██████▌   | 84/128 [00:01<00:00, 50.60it/s]
 70%|███████   | 90/128 [00:01<00:00, 50.61it/s]
 75%|███████▌  | 96/128 [00:01<00:00, 50.60it/s]
 80%|███████▉  | 102/128 [00:02<00:00, 50.60it/s]
 84%|████████▍ | 108/128 [00:02<00:00, 50.61it/s]
 89%|████████▉ | 114/128 [00:02<00:00, 50.58it/s]
 94%|█████████▍| 120/128 [00:02<00:00, 50.65it/s]
 98%|█████████▊| 126/128 [00:02<00:00, 50.67it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:02<00:00, 50.54it/s]

Average Precision (AP):  0.001384961126647782
Area Under Precision-Recall Curve (AUPRC):  0.0013751209299609028
EPR: 1.2630649585124507
No description has been provided for this image
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 15.86 seconds
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
base enrichment
Top central genes: []
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  0.0 % TFs

_________________________________________
loading GT,  omnipath
intersection of 1545 genes
intersection pct: 0.6845369960124058
precision:  0.009188551561432917 
recall:  0.37841984147276914 
random precision: 0.001639502322383755
  0%|          | 0/128 [00:00<?, ?it/s]
 20%|█▉        | 25/128 [00:00<00:00, 249.39it/s]
 39%|███▉      | 50/128 [00:00<00:00, 248.45it/s]
 59%|█████▉    | 76/128 [00:00<00:00, 249.57it/s]
 79%|███████▉  | 101/128 [00:00<00:00, 249.54it/s]
 99%|█████████▉| 127/128 [00:00<00:00, 249.77it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:00<00:00, 248.94it/s]

Average Precision (AP):  0.006097495201627464
Area Under Precision-Recall Curve (AUPRC):  0.005781176553272736
EPR: 9.454522889486277
No description has been provided for this image
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 16.70 seconds
base enrichment
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
Top central genes: []
No description has been provided for this image
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  10.526315789473685 % TFs

_________________________________________
loading GT,  omnipath
intersection of 1545 genes
intersection pct: 0.6845369960124058
precision:  0.0022959552969107387 
recall:  0.2027614420864229 
random precision: 0.001639502322383755
  0%|          | 0/128 [00:00<?, ?it/s]
 21%|██        | 27/128 [00:00<00:00, 260.42it/s]
 42%|████▏     | 54/128 [00:00<00:00, 259.79it/s]
 62%|██████▎   | 80/128 [00:00<00:00, 259.31it/s]
 84%|████████▎ | 107/128 [00:00<00:00, 260.12it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:00<00:00, 259.84it/s]

Average Precision (AP):  0.0016960689439870014
Area Under Precision-Recall Curve (AUPRC):  0.0017903071540811078
EPR: 1.248658655459195
No description has been provided for this image
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 31.63 seconds
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
base enrichment
Top central genes: []
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  6.382978723404255 % TFs

_________________________________________
loading GT,  omnipath
intersection of 3406 genes
intersection pct: 0.7138964577656676
precision:  0.009544498926019955 
recall:  0.32796150187454537 
random precision: 0.0015409448472635749
  0%|          | 0/128 [00:00<?, ?it/s]
  5%|▍         | 6/128 [00:00<00:02, 50.33it/s]
  9%|▉         | 12/128 [00:00<00:02, 50.46it/s]
 14%|█▍        | 18/128 [00:00<00:02, 50.46it/s]
 19%|█▉        | 24/128 [00:00<00:02, 50.46it/s]
 23%|██▎       | 30/128 [00:00<00:01, 50.45it/s]
 28%|██▊       | 36/128 [00:00<00:01, 50.44it/s]
 33%|███▎      | 42/128 [00:00<00:01, 50.48it/s]
 38%|███▊      | 48/128 [00:00<00:01, 50.44it/s]
 42%|████▏     | 54/128 [00:01<00:01, 50.47it/s]
 47%|████▋     | 60/128 [00:01<00:01, 50.40it/s]
 52%|█████▏    | 66/128 [00:01<00:01, 50.38it/s]
 56%|█████▋    | 72/128 [00:01<00:01, 50.35it/s]
 61%|██████    | 78/128 [00:01<00:00, 50.33it/s]
 66%|██████▌   | 84/128 [00:01<00:00, 50.26it/s]
 70%|███████   | 90/128 [00:01<00:00, 50.26it/s]
 75%|███████▌  | 96/128 [00:01<00:00, 50.32it/s]
 80%|███████▉  | 102/128 [00:02<00:00, 50.32it/s]
 84%|████████▍ | 108/128 [00:02<00:00, 50.18it/s]
 89%|████████▉ | 114/128 [00:02<00:00, 50.11it/s]
 94%|█████████▍| 120/128 [00:02<00:00, 50.05it/s]
 98%|█████████▊| 126/128 [00:02<00:00, 49.98it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:02<00:00, 50.25it/s]

Average Precision (AP):  0.005047515883367648
Area Under Precision-Recall Curve (AUPRC):  0.004712568423019291
EPR: 5.934936091576408
No description has been provided for this image
Tree method: RF
K: sqrt
Number of trees: 100


running jobs on 20 threads
Elapsed time: 36.69 seconds
/pasteur/appa/homes/jkalfon/miniconda3/envs/scprint17/lib/python3.10/multiprocessing/pool.py:265: ResourceWarning: unclosed running multiprocessing pool <multiprocessing.pool.Pool state=RUN pool_size=20>
  _warn(f"unclosed running multiprocessing pool {self!r}",
base enrichment
Top central genes: []
No description has been provided for this image
No description has been provided for this image
No description has been provided for this image
_________________________________________
TF specific enrichment
found some significant results for  6.382978723404255 % TFs

_________________________________________
loading GT,  omnipath
intersection of 3406 genes
intersection pct: 0.7138964577656676
precision:  0.002308445385969307 
recall:  0.19646354428963125 
random precision: 0.0015409448472635749
  0%|          | 0/128 [00:00<?, ?it/s]
  5%|▍         | 6/128 [00:00<00:02, 50.12it/s]
  9%|▉         | 12/128 [00:00<00:02, 50.25it/s]
 14%|█▍        | 18/128 [00:00<00:02, 50.26it/s]
 19%|█▉        | 24/128 [00:00<00:02, 50.28it/s]
 23%|██▎       | 30/128 [00:00<00:01, 50.33it/s]
 28%|██▊       | 36/128 [00:00<00:01, 50.38it/s]
 33%|███▎      | 42/128 [00:00<00:01, 50.36it/s]
 38%|███▊      | 48/128 [00:00<00:01, 50.33it/s]
 42%|████▏     | 54/128 [00:01<00:01, 50.28it/s]
 47%|████▋     | 60/128 [00:01<00:01, 50.35it/s]
 52%|█████▏    | 66/128 [00:01<00:01, 50.36it/s]
 56%|█████▋    | 72/128 [00:01<00:01, 50.35it/s]
 61%|██████    | 78/128 [00:01<00:00, 50.25it/s]
 66%|██████▌   | 84/128 [00:01<00:00, 50.26it/s]
 70%|███████   | 90/128 [00:01<00:00, 50.26it/s]
 75%|███████▌  | 96/128 [00:01<00:00, 50.31it/s]
 80%|███████▉  | 102/128 [00:02<00:00, 50.30it/s]
 84%|████████▍ | 108/128 [00:02<00:00, 50.22it/s]
 89%|████████▉ | 114/128 [00:02<00:00, 50.31it/s]
 94%|█████████▍| 120/128 [00:02<00:00, 50.38it/s]
 98%|█████████▊| 126/128 [00:02<00:00, 50.38it/s]
/pasteur/appa/homes/jkalfon/benGRN/bengrn/base.py:750: RuntimeWarning: invalid value encountered in scalar divide
  precision = (grn[true] > threshold).sum() / (grn > threshold).sum()

100%|██████████| 128/128 [00:02<00:00, 50.30it/s]

Average Precision (AP):  0.0015709317218276543
Area Under Precision-Recall Curve (AUPRC):  0.0016294208207601668
EPR: 1.2720250886940248
No description has been provided for this image
In [9]:
Copied!
shapes
shapes
Out[9]:
[5000, 5000, 5000, 3510, 4949, 5000, 4785, 2257, 4771]
In [10]:
Copied!
metrics
metrics
Out[10]:
{'genie3_tf_kidney distal convoluted tubule epithelial cell': {'enriched_terms_Central': ['0__TFs',
   'celltype.gmt__Embryonic stem cells',
   'celltype.gmt__Enteric neurons',
   'celltype.gmt__Melanocytes'],
  'TF_enr': True,
  'enriched_terms_Targets': ['celltype.gmt__Melanocytes'],
  'significant_enriched_TFtargets': 14.705882352941176,
  'precision': 0.004541789382676131,
  'recall': 0.33513633669235326,
  'rand_precision': 0.001062203773751226,
  'auprc': 0.00252355640477646,
  'ap': 0.0028506585986099184,
  'epr': 5.849284104972232},
 'genie3_kidney distal convoluted tubule epithelial cell': {'enriched_terms_Central': ['celltype.gmt__Distal tubule cells',
   'celltype.gmt__-intercalated cells (Collecting duct system)',
   'celltype.gmt__Loop of Henle cells',
   'celltype.gmt__Connecting tubule cells',
   'celltype.gmt__Proximal tubule cells',
   'celltype.gmt__Podocytes',
   'celltype.gmt__Hepatic stellate cells',
   'celltype.gmt__Melanocytes',
   'celltype.gmt__Ductal cells',
   'celltype.gmt__Ionocytes',
   'celltype.gmt__Embryonic stem cells',
   'celltype.gmt__Cholangiocytes',
   'celltype.gmt__Enterocytes'],
  'TF_enr': False,
  'enriched_terms_Targets': ['celltype.gmt__Distal tubule cells',
   'celltype.gmt__Cholangiocytes',
   'celltype.gmt__-intercalated cells (Collecting duct system)',
   'celltype.gmt__Loop of Henle cells',
   'celltype.gmt__Ductal cells',
   'celltype.gmt__Connecting tubule cells',
   'celltype.gmt__Proximal tubule cells',
   'celltype.gmt__Melanocytes',
   'celltype.gmt__Hepatic stellate cells',
   'celltype.gmt__Hepatocytes',
   'celltype.gmt__Enterocytes',
   'celltype.gmt__Podocytes',
   'celltype.gmt__Ionocytes',
   'celltype.gmt__Embryonic stem cells',
   'celltype.gmt__Beta cells',
   'celltype.gmt__Delta cells',
   'celltype.gmt__Principal cells (Collecting duct system)'],
  'significant_enriched_TFtargets': 2.9411764705882355,
  'precision': 0.0011096698483979172,
  'recall': 0.6956135151155898,
  'rand_precision': 0.001062203773751226,
  'auprc': 0.0010760455741965266,
  'ap': 0.001095405878733279,
  'epr': 1.7466859320820376},
 'genie3_tf_kidney loop of Henle thick ascending limb epithelial cell': {'enriched_terms_Central': ['0__TFs',
   'celltype.gmt__Loop of Henle cells',
   'celltype.gmt__Embryonic stem cells',
   'celltype.gmt__Delta cells',
   'celltype.gmt__Distal tubule cells',
   'celltype.gmt__Proximal tubule cells',
   'celltype.gmt__Microfold cells',
   'celltype.gmt__Gamma (PP) cells',
   'celltype.gmt__Alpha cells',
   'celltype.gmt__Renal Vesicle cells',
   'celltype.gmt__Enterocytes'],
  'TF_enr': True,
  'significant_enriched_TFtargets': 10.0,
  'precision': 0.006271091258494464,
  'recall': 0.40673661698857183,
  'rand_precision': 0.0012121008868434197,
  'auprc': 0.0033103141109521303,
  'ap': 0.0038068710056600934,
  'epr': 4.897761556952193},
 'genie3_kidney loop of Henle thick ascending limb epithelial cell': {'enriched_terms_Central': ['celltype.gmt__Distal tubule cells',
   'celltype.gmt__Loop of Henle cells',
   'celltype.gmt__Proximal tubule cells',
   'celltype.gmt__Ductal cells',
   'celltype.gmt__-intercalated cells (Collecting duct system)',
   'celltype.gmt__Hepatocytes'],
  'TF_enr': False,
  'enriched_terms_Targets': ['celltype.gmt__Distal tubule cells',
   'celltype.gmt__Loop of Henle cells',
   'celltype.gmt__Ductal cells',
   'celltype.gmt__Proximal tubule cells',
   'celltype.gmt__-intercalated cells (Collecting duct system)',
   'celltype.gmt__Podocytes'],
  'significant_enriched_TFtargets': 2.5,
  'precision': 0.001285625479006546,
  'recall': 0.32881106729933834,
  'rand_precision': 0.0012121008868434197,
  'auprc': 0.0012041101257049699,
  'ap': 0.0012326445926554342,
  'epr': 0.7162872764286753},
 'genie3_tf_kidney collecting duct principal cell': {'enriched_terms_Central': ['0__TFs',
   'celltype.gmt__Microfold cells',
   'celltype.gmt__Melanocytes',
   'celltype.gmt__Embryonic stem cells',
   'celltype.gmt__Distal tubule cells',
   'celltype.gmt__Satellite cells',
   'celltype.gmt__Principal cells (Collecting duct system)',
   'celltype.gmt__Hepatic stellate cells',
   'celltype.gmt__Keratinocytes',
   'celltype.gmt__Mesangial cells',
   'celltype.gmt__-intercalated cells (Collecting duct system)',
   'celltype.gmt__Renal Vesicle cells',
   'celltype.gmt__Ionocytes',
   'celltype.gmt__Tuft cells'],
  'TF_enr': True,
  'significant_enriched_TFtargets': 1.4285714285714286,
  'precision': 0.007092883035904675,
  'recall': 0.4387900153522488,
  'rand_precision': 0.0013619352909207464,
  'auprc': 0.004757467010786939,
  'ap': 0.005337285240454103,
  'epr': 8.781634597124883},
 'genie3_kidney collecting duct principal cell': {'enriched_terms_Central': ['celltype.gmt__Distal tubule cells',
   'celltype.gmt__Principal cells (Collecting duct system)',
   'celltype.gmt__-intercalated cells (Collecting duct system)',
   'celltype.gmt__Connecting tubule cells',
   'celltype.gmt__Ductal cells',
   'celltype.gmt__Proximal tubule cells',
   'celltype.gmt__Loop of Henle cells',
   'celltype.gmt__Foveolar cells',
   'celltype.gmt__Podocytes',
   'celltype.gmt__Gamma (PP) cells',
   'celltype.gmt__Hepatic stellate cells',
   'celltype.gmt__Alpha cells',
   'celltype.gmt__Cholangiocytes'],
  'TF_enr': False,
  'enriched_terms_Targets': ['celltype.gmt__Principal cells (Collecting duct system)',
   'celltype.gmt__-intercalated cells (Collecting duct system)',
   'celltype.gmt__Distal tubule cells',
   'celltype.gmt__Ductal cells',
   'celltype.gmt__Connecting tubule cells',
   'celltype.gmt__Cholangiocytes',
   'celltype.gmt__Hepatic stellate cells',
   'celltype.gmt__Gamma (PP) cells',
   'celltype.gmt__Loop of Henle cells',
   'celltype.gmt__Foveolar cells',
   'celltype.gmt__Podocytes',
   'celltype.gmt__Proximal tubule cells',
   'celltype.gmt__Acinar cells',
   'celltype.gmt__Alpha cells',
   'celltype.gmt__Pulmonary alveolar type I cells',
   'celltype.gmt__Ionocytes'],
  'significant_enriched_TFtargets': 2.857142857142857,
  'precision': 0.001539952451821791,
  'recall': 0.4742707681810428,
  'rand_precision': 0.0013619352909207464,
  'auprc': 0.0014320894483849911,
  'ap': 0.0014811949583253049,
  'epr': 1.5890254176610075},
 'genie3_tf_mesangial cell': {'enriched_terms_Central': ['0__TFs',
   'celltype.gmt__Mesangial cells'],
  'TF_enr': True,
  'significant_enriched_TFtargets': 2.5641025641025643,
  'precision': 0.011580584843104287,
  'recall': 0.1789703739679456,
  'rand_precision': 0.0012750761624232764,
  'auprc': 0.0030541973899464257,
  'ap': 0.003349531418887418,
  'epr': 9.434251628175465},
 'genie3_mesangial cell': {'enriched_terms_Central': ['celltype.gmt__Hepatic stellate cells',
   'celltype.gmt__Myoepithelial cells',
   'celltype.gmt__Perivascular cells',
   'celltype.gmt__Myofibroblasts',
   'celltype.gmt__Podocytes',
   'celltype.gmt__Loop of Henle cells'],
  'TF_enr': False,
  'enriched_terms_Targets': ['celltype.gmt__Hepatic stellate cells',
   'celltype.gmt__Podocytes',
   'celltype.gmt__Myofibroblasts',
   'celltype.gmt__Principal cells (Collecting duct system)',
   'celltype.gmt__Pulmonary alveolar type I cells',
   'celltype.gmt__Perivascular cells',
   'celltype.gmt__Myoepithelial cells',
   'celltype.gmt__Renal interstitium (Mesenchymal cells)',
   'celltype.gmt__Smooth Muscle cells'],
  'significant_enriched_TFtargets': 2.5641025641025643,
  'precision': 0.0016484163428705993,
  'recall': 0.0305973773676542,
  'rand_precision': 0.0012750761624232764,
  'auprc': 0.0012825989724762198,
  'ap': 0.001177156569385212,
  'epr': 1.3342748933585344},
 'genie3_tf_blood vessel smooth muscle cell': {'enriched_terms_Central': ['0__TFs',
   'celltype.gmt__Embryonic stem cells',
   'celltype.gmt__Perivascular cells',
   'celltype.gmt__Microfold cells',
   'celltype.gmt__Myofibroblasts',
   'celltype.gmt__Satellite cells',
   'celltype.gmt__Smooth Muscle cells',
   'celltype.gmt__Gamma (PP) cells',
   'celltype.gmt__Cap mesenchyme cells (Mesenchymal cells)',
   'celltype.gmt__Mesenchymal stem cells',
   'celltype.gmt__Mesangial cells'],
  'TF_enr': True,
  'significant_enriched_TFtargets': 0.0,
  'precision': 0.00896463904832305,
  'recall': 0.37216471129514606,
  'rand_precision': 0.0016822195546123465,
  'auprc': 0.004916303339642281,
  'ap': 0.0054905113019332215,
  'epr': 5.978256210614143},
 'genie3_blood vessel smooth muscle cell': {'enriched_terms_Central': ['celltype.gmt__Hepatic stellate cells',
   'celltype.gmt__Myofibroblasts',
   'celltype.gmt__Perivascular cells',
   'celltype.gmt__Smooth Muscle cells',
   'celltype.gmt__Smooth muscle cells',
   'celltype.gmt__Mesangial cells',
   'celltype.gmt__Mesenchymal stem cells',
   'celltype.gmt__Myoepithelial cells',
   'celltype.gmt__Vascular smooth muscle cells',
   'celltype.gmt__Fibroblasts',
   'celltype.gmt__Cap mesenchyme cells (Mesenchymal cells)',
   'celltype.gmt__Pericytes',
   'celltype.gmt__Leydig cells',
   'celltype.gmt__Radial glial cells',
   'celltype.gmt__Glycinergic amacrine cells',
   'celltype.gmt__Adipocytes',
   'celltype.gmt__Renal interstitium (Mesenchymal cells)',
   'celltype.gmt__Microfold cells',
   'celltype.gmt__Pro-B cells',
   'celltype.gmt__Endometrium'],
  'TF_enr': False,
  'enriched_terms_Targets': ['celltype.gmt__Hepatic stellate cells',
   'celltype.gmt__Myofibroblasts',
   'celltype.gmt__Smooth Muscle cells',
   'celltype.gmt__Perivascular cells',
   'celltype.gmt__Smooth muscle cells',
   'celltype.gmt__Myoepithelial cells',
   'celltype.gmt__Renal interstitium (Mesenchymal cells)',
   'celltype.gmt__Mesangial cells',
   'celltype.gmt__Vascular smooth muscle cells',
   'celltype.gmt__Pericytes',
   'celltype.gmt__Leydig cells',
   'celltype.gmt__Fibroblasts',
   'celltype.gmt__Mesenchymal stem cells',
   'celltype.gmt__Cap mesenchyme cells (Mesenchymal cells)',
   'celltype.gmt__Radial glial cells',
   'celltype.gmt__Melanocytes'],
  'significant_enriched_TFtargets': 3.5714285714285716,
  'precision': 0.002206980823429709,
  'recall': 0.2576029445594663,
  'rand_precision': 0.0016822195546123465,
  'auprc': 0.0017771005963575573,
  'ap': 0.0018285890904070012,
  'epr': 1.1218100192058453},
 'genie3_tf_podocyte': {'enriched_terms_Central': ['0__TFs',
   'celltype.gmt__Embryonic stem cells',
   'celltype.gmt__Podocytes',
   'celltype.gmt__Hepatic stellate cells',
   'celltype.gmt__Microfold cells',
   'celltype.gmt__Enteric neurons',
   'celltype.gmt__Mesangial cells',
   'celltype.gmt__Gamma (PP) cells',
   'celltype.gmt__Glycinergic amacrine cells',
   'celltype.gmt__Cap mesenchyme cells (Mesenchymal cells)',
   'celltype.gmt__Myocytes'],
  'TF_enr': True,
  'significant_enriched_TFtargets': 0.0,
  'precision': 0.008509893153340102,
  'recall': 0.4291732223519261,
  'rand_precision': 0.001518183918238287,
  'auprc': 0.0046805414565712425,
  'ap': 0.0052484975615239675,
  'epr': 6.145020274594569},
 'genie3_podocyte': {'enriched_terms_Central': ['celltype.gmt__Podocytes',
   'celltype.gmt__Hepatic stellate cells',
   'celltype.gmt__Myofibroblasts',
   'celltype.gmt__Pulmonary alveolar type I cells',
   'celltype.gmt__Mesangial cells'],
  'TF_enr': False,
  'enriched_terms_Targets': ['celltype.gmt__Podocytes',
   'celltype.gmt__Hepatic stellate cells',
   'celltype.gmt__Pulmonary alveolar type I cells',
   'celltype.gmt__Myoepithelial cells',
   'celltype.gmt__Myofibroblasts',
   'celltype.gmt__Endometrium',
   'celltype.gmt__Stromal cells',
   'celltype.gmt__Myocytes',
   'celltype.gmt__Embryonic stem cells',
   'celltype.gmt__Immune cells',
   'celltype.gmt__Smooth muscle cells'],
  'significant_enriched_TFtargets': 4.25531914893617,
  'precision': 0.001674633348973699,
  'recall': 0.4119169669593463,
  'rand_precision': 0.001518183918238287,
  'auprc': 0.001539994484667556,
  'ap': 0.0015823538224594797,
  'epr': 0.7348799242950723},
 'genie3_tf_macrophage': {'enriched_terms_Central': ['0__TFs',
   'celltype.gmt__Tuft cells'],
  'TF_enr': True,
  'significant_enriched_TFtargets': 2.4390243902439024,
  'precision': 0.009331147617220653,
  'recall': 0.25440598453150753,
  'rand_precision': 0.0013561437852866911,
  'auprc': 0.0033775019219795498,
  'ap': 0.003925004962797144,
  'epr': 6.5477109026987135},
 'genie3_macrophage': {'enriched_terms_Central': ['celltype.gmt__Myofibroblasts',
   'celltype.gmt__Hepatic stellate cells'],
  'TF_enr': False,
  'enriched_terms_Targets': ['celltype.gmt__Myofibroblasts'],
  'significant_enriched_TFtargets': 0.0,
  'precision': 0.001856214279002524,
  'recall': 0.07138328895651071,
  'rand_precision': 0.0013561437852866911,
  'auprc': 0.0013751209299609028,
  'ap': 0.001384961126647782,
  'epr': 1.2630649585124507},
 'genie3_tf_leukocyte': {'enriched_terms_Central': ['0__TFs'],
  'TF_enr': True,
  'significant_enriched_TFtargets': 0.0,
  'precision': 0.009188551561432917,
  'recall': 0.37841984147276914,
  'rand_precision': 0.001639502322383755,
  'auprc': 0.005781176553272736,
  'ap': 0.006097495201627464,
  'epr': 9.454522889486277},
 'genie3_leukocyte': {'TF_enr': False,
  'significant_enriched_TFtargets': 10.526315789473685,
  'precision': 0.0022959552969107387,
  'recall': 0.2027614420864229,
  'rand_precision': 0.001639502322383755,
  'auprc': 0.0017903071540811078,
  'ap': 0.0016960689439870014,
  'epr': 1.248658655459195},
 'genie3_tf_kidney interstitial fibroblast': {'enriched_terms_Central': ['0__TFs',
   'celltype.gmt__Perivascular cells',
   'celltype.gmt__Embryonic stem cells',
   'celltype.gmt__Smooth Muscle cells',
   'celltype.gmt__Myofibroblasts',
   'celltype.gmt__Mesangial cells'],
  'TF_enr': True,
  'enriched_terms_Targets': ['celltype.gmt__Mesangial cells'],
  'significant_enriched_TFtargets': 6.382978723404255,
  'precision': 0.009544498926019955,
  'recall': 0.32796150187454537,
  'rand_precision': 0.0015409448472635749,
  'auprc': 0.004712568423019291,
  'ap': 0.005047515883367648,
  'epr': 5.934936091576408},
 'genie3_kidney interstitial fibroblast': {'enriched_terms_Central': ['celltype.gmt__Myofibroblasts',
   'celltype.gmt__Mesangial cells',
   'celltype.gmt__Perivascular cells',
   'celltype.gmt__Smooth Muscle cells',
   'celltype.gmt__Hepatic stellate cells',
   'celltype.gmt__Myoepithelial cells',
   'celltype.gmt__Cap mesenchyme cells (Mesenchymal cells)',
   'celltype.gmt__Vascular smooth muscle cells',
   'celltype.gmt__Embryonic stem cells',
   'celltype.gmt__Plasmacytoid Dendritic cells',
   'celltype.gmt__Mesenchymal stem cells',
   'celltype.gmt__Smooth muscle cells',
   'celltype.gmt__Myeloid Dendritic cells',
   'celltype.gmt__Endothelial cells'],
  'TF_enr': False,
  'enriched_terms_Targets': ['celltype.gmt__Hepatic stellate cells',
   'celltype.gmt__Myofibroblasts',
   'celltype.gmt__Smooth Muscle cells',
   'celltype.gmt__Perivascular cells',
   'celltype.gmt__Myoepithelial cells',
   'celltype.gmt__Mesangial cells',
   'celltype.gmt__Renal interstitium (Mesenchymal cells)',
   'celltype.gmt__Vascular smooth muscle cells',
   'celltype.gmt__Smooth muscle cells',
   'celltype.gmt__Mesenchymal stem cells',
   'celltype.gmt__Myocytes',
   'celltype.gmt__Endothelial'],
  'significant_enriched_TFtargets': 6.382978723404255,
  'precision': 0.002308445385969307,
  'recall': 0.19646354428963125,
  'rand_precision': 0.0015409448472635749,
  'auprc': 0.0016294208207601668,
  'ap': 0.0015709317218276543,
  'epr': 1.2720250886940248}}
In [11]:
Copied!
False
True
True
True
True
True
True
False
True
True
True
True
False
False
False
False
True
True
False True True True True True True False True True True True False False False False True True
Out[11]:
True
In [12]:
Copied!
res = []
for k, v in metrics.items():
    res.append([k.split('_')[-1], v['epr'], v['auprc'], v['rand_precision'], v['significant_enriched_TFtargets'], v.get('TF_enr', False), 'tf_' in k])

df = pd.DataFrame(res, columns=['name','EPR', 'AUPRC', 'RAND', 'TF_targ', 'TF_enr', 'TF_only'])
df
res = [] for k, v in metrics.items(): res.append([k.split('_')[-1], v['epr'], v['auprc'], v['rand_precision'], v['significant_enriched_TFtargets'], v.get('TF_enr', False), 'tf_' in k]) df = pd.DataFrame(res, columns=['name','EPR', 'AUPRC', 'RAND', 'TF_targ', 'TF_enr', 'TF_only']) df
Out[12]:
name EPR AUPRC RAND TF_targ TF_enr TF_only
0 kidney distal convoluted tubule epithelial cell 5.849284 0.002524 0.001062 14.705882 True True
1 kidney distal convoluted tubule epithelial cell 1.746686 0.001076 0.001062 2.941176 False False
2 kidney loop of Henle thick ascending limb epit... 4.897762 0.003310 0.001212 10.000000 True True
3 kidney loop of Henle thick ascending limb epit... 0.716287 0.001204 0.001212 2.500000 False False
4 kidney collecting duct principal cell 8.781635 0.004757 0.001362 1.428571 True True
5 kidney collecting duct principal cell 1.589025 0.001432 0.001362 2.857143 False False
6 mesangial cell 9.434252 0.003054 0.001275 2.564103 True True
7 mesangial cell 1.334275 0.001283 0.001275 2.564103 False False
8 blood vessel smooth muscle cell 5.978256 0.004916 0.001682 0.000000 True True
9 blood vessel smooth muscle cell 1.121810 0.001777 0.001682 3.571429 False False
10 podocyte 6.145020 0.004681 0.001518 0.000000 True True
11 podocyte 0.734880 0.001540 0.001518 4.255319 False False
12 macrophage 6.547711 0.003378 0.001356 2.439024 True True
13 macrophage 1.263065 0.001375 0.001356 0.000000 False False
14 leukocyte 9.454523 0.005781 0.001640 0.000000 True True
15 leukocyte 1.248659 0.001790 0.001640 10.526316 False False
16 kidney interstitial fibroblast 5.934936 0.004713 0.001541 6.382979 True True
17 kidney interstitial fibroblast 1.272025 0.001629 0.001541 6.382979 False False
Previous Next

Built with MkDocs using a theme provided by Read the Docs.
« Previous Next »