diff --git a/.github/workflows/build_docs.yml b/.github/workflows/build_docs.yml
index f4489de..8c68ee6 100644
--- a/.github/workflows/build_docs.yml
+++ b/.github/workflows/build_docs.yml
@@ -24,7 +24,7 @@ jobs:
       - uses: actions/setup-python@v5
       - name: Install dependencies
         run: |
-          pip install -r doc_conf/doc-requirements.txt
+          python -m pip install .[doc, plotting]
           pip install -e .
       - name: Sphinx build
         id: build-docs
diff --git a/.github/workflows/build_package.yml b/.github/workflows/build_package.yml
index c869baf..4fe384c 100644
--- a/.github/workflows/build_package.yml
+++ b/.github/workflows/build_package.yml
@@ -27,13 +27,10 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
-        python -m pip install flake8 pytest
-        if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
-    # - name: Lint with flake8
-    #  uses: py-actions/flake8@v2.3.0
+        python -m pip install .[dependencies]
     - name: Generate coverage report
       run: |
-        pip install pytest pytest-cov
+        python -m pip install .[test]
         pytest --cov=./ --cov-report=xml
     - name: Upload coverage reports to Codecov
       uses: codecov/codecov-action@v4.5.0
diff --git a/doc_conf/conf.py b/doc_conf/conf.py
index a0ff7c9..b93dff3 100644
--- a/doc_conf/conf.py
+++ b/doc_conf/conf.py
@@ -13,12 +13,12 @@
 # serve to show the default.
 
 import os
-import sys
 import warnings
-import sphinx_gallery
-import sphinx_bootstrap_theme
 from distutils.version import LooseVersion
+
 import matplotlib
+import sphinx_bootstrap_theme
+import sphinx_gallery
 
 # Disable agg warnings in doc
 warnings.filterwarnings(
diff --git a/doc_conf/doc-requirements.txt b/doc_conf/doc-requirements.txt
deleted file mode 100644
index 4192564..0000000
--- a/doc_conf/doc-requirements.txt
+++ /dev/null
@@ -1,20 +0,0 @@
---extra-index-url https://download.pytorch.org/whl/cu118
-joblib
-matplotlib
-memory_profiler
-mne
-nilearn
-numpy
-numpydoc
-pandas
-pillow
-PyQt5
-pyvista
-pyvistaqt
-scikit-learn
-scipy
-sphinx-bootstrap-theme
-sphinxcontrib-bibtex
-sphinx-gallery
-torch
-torchmetrics
diff --git a/docs/_downloads/0f0a1edc554c21f6f7fda8f53284928a/plot_2D_simulation_example.py b/docs/_downloads/0f0a1edc554c21f6f7fda8f53284928a/plot_2D_simulation_example.py
index 57bee37..4fdb7dc 100644
--- a/docs/_downloads/0f0a1edc554c21f6f7fda8f53284928a/plot_2D_simulation_example.py
+++ b/docs/_downloads/0f0a1edc554c21f6f7fda8f53284928a/plot_2D_simulation_example.py
@@ -51,20 +51,19 @@
        arXiv preprint arXiv:2106.02590.
 """
 
+import matplotlib.pyplot as plt
 #############################################################################
 # Imports needed for this script
 # ------------------------------
 import numpy as np
-import matplotlib.pyplot as plt
-from sklearn.feature_extraction import image
 from sklearn.cluster import FeatureAgglomeration
+from sklearn.feature_extraction import image
 
-from hidimstat.scenario import multivariate_simulation
-from hidimstat.stat_tools import zscore_from_pval, pval_from_cb
-from hidimstat.desparsified_lasso import desparsified_lasso
 from hidimstat.clustered_inference import clustered_inference
+from hidimstat.desparsified_lasso import desparsified_lasso
 from hidimstat.ensemble_clustered_inference import ensemble_clustered_inference
-
+from hidimstat.scenario import multivariate_simulation
+from hidimstat.stat_tools import pval_from_cb, zscore_from_pval
 
 #############################################################################
 # Specific plotting functions
diff --git a/docs/_downloads/6f624092537330c9f373c01828b2b9ae/plot_diabetes_variable_importance_example.py b/docs/_downloads/6f624092537330c9f373c01828b2b9ae/plot_diabetes_variable_importance_example.py
index 29cf767..f6ccf40 100644
--- a/docs/_downloads/6f624092537330c9f373c01828b2b9ae/plot_diabetes_variable_importance_example.py
+++ b/docs/_downloads/6f624092537330c9f373c01828b2b9ae/plot_diabetes_variable_importance_example.py
@@ -10,10 +10,11 @@
 # Imports needed for this script
 # ------------------------------
 
+import matplotlib.pyplot as plt
 import numpy as np
-from hidimstat.BBI import BlockBasedImportance
 from sklearn.datasets import load_diabetes
-import matplotlib.pyplot as plt
+
+from hidimstat.BBI import BlockBasedImportance
 
 plt.rcParams.update({"font.size": 14})
 
diff --git a/docs/_downloads/76c0979bf6618aa210fd11bb28dcf896/plot_fmri_data_example.py b/docs/_downloads/76c0979bf6618aa210fd11bb28dcf896/plot_fmri_data_example.py
index ef0625f..25b89b8 100644
--- a/docs/_downloads/76c0979bf6618aa210fd11bb28dcf896/plot_fmri_data_example.py
+++ b/docs/_downloads/76c0979bf6618aa210fd11bb28dcf896/plot_fmri_data_example.py
@@ -45,21 +45,21 @@
 # ------------------------------
 import numpy as np
 import pandas as pd
-from sklearn.utils import Bunch
-from sklearn.cluster import FeatureAgglomeration
-from sklearn.feature_extraction import image
-from sklearn.linear_model import Ridge
 from nilearn import datasets
-from nilearn.input_data import NiftiMasker
 from nilearn.image import mean_img
+from nilearn.input_data import NiftiMasker
 from nilearn.plotting import plot_stat_map, show
+from sklearn.cluster import FeatureAgglomeration
+from sklearn.feature_extraction import image
+from sklearn.linear_model import Ridge
+from sklearn.utils import Bunch
 
-from hidimstat.stat_tools import zscore_from_pval, pval_from_scale
-from hidimstat.standardized_svr import standardized_svr
-from hidimstat.permutation_test import permutation_test, permutation_test_cv
 from hidimstat.adaptive_permutation_threshold import ada_svr
 from hidimstat.clustered_inference import clustered_inference
 from hidimstat.ensemble_clustered_inference import ensemble_clustered_inference
+from hidimstat.permutation_test import permutation_test, permutation_test_cv
+from hidimstat.standardized_svr import standardized_svr
+from hidimstat.stat_tools import pval_from_scale, zscore_from_pval
 
 
 #############################################################################
diff --git a/examples/plot_2D_simulation_example.py b/examples/plot_2D_simulation_example.py
index 57bee37..4fdb7dc 100644
--- a/examples/plot_2D_simulation_example.py
+++ b/examples/plot_2D_simulation_example.py
@@ -51,20 +51,19 @@
        arXiv preprint arXiv:2106.02590.
 """
 
+import matplotlib.pyplot as plt
 #############################################################################
 # Imports needed for this script
 # ------------------------------
 import numpy as np
-import matplotlib.pyplot as plt
-from sklearn.feature_extraction import image
 from sklearn.cluster import FeatureAgglomeration
+from sklearn.feature_extraction import image
 
-from hidimstat.scenario import multivariate_simulation
-from hidimstat.stat_tools import zscore_from_pval, pval_from_cb
-from hidimstat.desparsified_lasso import desparsified_lasso
 from hidimstat.clustered_inference import clustered_inference
+from hidimstat.desparsified_lasso import desparsified_lasso
 from hidimstat.ensemble_clustered_inference import ensemble_clustered_inference
-
+from hidimstat.scenario import multivariate_simulation
+from hidimstat.stat_tools import pval_from_cb, zscore_from_pval
 
 #############################################################################
 # Specific plotting functions
diff --git a/examples/plot_diabetes_variable_importance_example.py b/examples/plot_diabetes_variable_importance_example.py
index cb17cf4..51e5c3d 100644
--- a/examples/plot_diabetes_variable_importance_example.py
+++ b/examples/plot_diabetes_variable_importance_example.py
@@ -10,10 +10,11 @@
 # Imports needed for this script
 # ------------------------------
 
+import matplotlib.pyplot as plt
 import numpy as np
-from hidimstat.BBI import BlockBasedImportance
 from sklearn.datasets import load_diabetes
-import matplotlib.pyplot as plt
+
+from hidimstat.BBI import BlockBasedImportance
 
 plt.rcParams.update({"font.size": 14})
 
diff --git a/examples/plot_fmri_data_example.py b/examples/plot_fmri_data_example.py
index ef0625f..25b89b8 100644
--- a/examples/plot_fmri_data_example.py
+++ b/examples/plot_fmri_data_example.py
@@ -45,21 +45,21 @@
 # ------------------------------
 import numpy as np
 import pandas as pd
-from sklearn.utils import Bunch
-from sklearn.cluster import FeatureAgglomeration
-from sklearn.feature_extraction import image
-from sklearn.linear_model import Ridge
 from nilearn import datasets
-from nilearn.input_data import NiftiMasker
 from nilearn.image import mean_img
+from nilearn.input_data import NiftiMasker
 from nilearn.plotting import plot_stat_map, show
+from sklearn.cluster import FeatureAgglomeration
+from sklearn.feature_extraction import image
+from sklearn.linear_model import Ridge
+from sklearn.utils import Bunch
 
-from hidimstat.stat_tools import zscore_from_pval, pval_from_scale
-from hidimstat.standardized_svr import standardized_svr
-from hidimstat.permutation_test import permutation_test, permutation_test_cv
 from hidimstat.adaptive_permutation_threshold import ada_svr
 from hidimstat.clustered_inference import clustered_inference
 from hidimstat.ensemble_clustered_inference import ensemble_clustered_inference
+from hidimstat.permutation_test import permutation_test, permutation_test_cv
+from hidimstat.standardized_svr import standardized_svr
+from hidimstat.stat_tools import pval_from_scale, zscore_from_pval
 
 
 #############################################################################
diff --git a/examples_not_exhibited/plot_fig_1_nguyen_et_al.py b/examples_not_exhibited/plot_fig_1_nguyen_et_al.py
index 91efffb..17e8815 100644
--- a/examples_not_exhibited/plot_fig_1_nguyen_et_al.py
+++ b/examples_not_exhibited/plot_fig_1_nguyen_et_al.py
@@ -12,11 +12,12 @@
 """
 import matplotlib.pyplot as plt
 import numpy as np
+from joblib import Parallel, delayed
+from sklearn.preprocessing import StandardScaler
+
 from hidimstat.knockoffs import knockoff_aggregation, model_x_knockoff
 from hidimstat.knockoffs.data_simulation import simu_data
 from hidimstat.knockoffs.utils import cal_fdp_power
-from joblib import Parallel, delayed
-from sklearn.preprocessing import StandardScaler
 
 color_blue = "#1f77b4"
 color_teal = "#1fbecf"
diff --git a/examples_not_exhibited/plot_meg_data_example.py b/examples_not_exhibited/plot_meg_data_example.py
index bc529ea..b3c19b2 100644
--- a/examples_not_exhibited/plot_meg_data_example.py
+++ b/examples_not_exhibited/plot_meg_data_example.py
@@ -23,14 +23,15 @@
 """
 
 import os
-import numpy as np
+
 import matplotlib.image as mpimg
 import matplotlib.pyplot as plt
 import mne
-from scipy.sparse.csgraph import connected_components
+import numpy as np
 from mne.datasets import sample, somato
-from mne.inverse_sparse.mxne_inverse import _prepare_gain, _make_sparse_stc
-from mne.minimum_norm import make_inverse_operator, apply_inverse
+from mne.inverse_sparse.mxne_inverse import _make_sparse_stc, _prepare_gain
+from mne.minimum_norm import apply_inverse, make_inverse_operator
+from scipy.sparse.csgraph import connected_components
 from sklearn.cluster import FeatureAgglomeration
 from sklearn.metrics.pairwise import pairwise_distances
 
diff --git a/hidimstat/BBI.py b/hidimstat/BBI.py
index ccf15f7..297e959 100644
--- a/hidimstat/BBI.py
+++ b/hidimstat/BBI.py
@@ -9,24 +9,17 @@
 from sklearn.base import BaseEstimator, TransformerMixin
 from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor
 from sklearn.linear_model import RidgeCV
-from sklearn.metrics import (
-    log_loss,
-    mean_absolute_error,
-    mean_squared_error,
-    roc_auc_score,
-    r2_score,
-)
-from sklearn.model_selection import KFold, GroupKFold
+from sklearn.metrics import (log_loss, mean_absolute_error, mean_squared_error,
+                             r2_score, roc_auc_score)
+from sklearn.model_selection import GroupKFold, KFold
 from sklearn.pipeline import make_pipeline
 from sklearn.preprocessing import OneHotEncoder, StandardScaler
 from sklearn.utils.validation import check_is_fitted
 
-from .compute_importance import (
-    joblib_compute_conditional,
-    joblib_compute_permutation,
-)
+from .compute_importance import (joblib_compute_conditional,
+                                 joblib_compute_permutation)
 from .Dnn_learner import Dnn_learner
-from .utils import convert_predict_proba, create_X_y, compute_imp_std
+from .utils import compute_imp_std, convert_predict_proba, create_X_y
 
 
 class BlockBasedImportance(BaseEstimator, TransformerMixin):
diff --git a/hidimstat/Dnn_learner.py b/hidimstat/Dnn_learner.py
index 366e9be..c986aa1 100644
--- a/hidimstat/Dnn_learner.py
+++ b/hidimstat/Dnn_learner.py
@@ -1,5 +1,6 @@
 import numpy as np
 from sklearn.base import BaseEstimator
+
 from .Dnn_learner_single import Dnn_learner_single
 
 
diff --git a/hidimstat/Dnn_learner_single.py b/hidimstat/Dnn_learner_single.py
index 64b7a7b..f25b489 100644
--- a/hidimstat/Dnn_learner_single.py
+++ b/hidimstat/Dnn_learner_single.py
@@ -8,15 +8,8 @@
 from sklearn.preprocessing import OneHotEncoder
 from sklearn.utils.validation import check_is_fitted
 
-from .utils import (
-    create_X_y,
-    dnn_net,
-    joblib_ensemble_dnnet,
-    ordinal_encode,
-    relu,
-    sigmoid,
-    softmax,
-)
+from .utils import (create_X_y, dnn_net, joblib_ensemble_dnnet, ordinal_encode,
+                    relu, sigmoid, softmax)
 
 
 class Dnn_learner_single(BaseEstimator):
diff --git a/hidimstat/__init__.py b/hidimstat/__init__.py
index 47c955c..f17c584 100644
--- a/hidimstat/__init__.py
+++ b/hidimstat/__init__.py
@@ -5,8 +5,8 @@
 from .Dnn_learner_single import Dnn_learner_single
 from .ensemble_clustered_inference import ensemble_clustered_inference
 from .importance_functions import compute_loco
-from .knockoffs import model_x_knockoff
 from .knockoff_aggregation import knockoff_aggregation
+from .knockoffs import model_x_knockoff
 from .multi_sample_split import aggregate_quantiles
 from .noise_std import group_reid, reid
 from .permutation_test import permutation_test_cv
diff --git a/hidimstat/clustered_inference.py b/hidimstat/clustered_inference.py
index 1273df9..5202f0a 100644
--- a/hidimstat/clustered_inference.py
+++ b/hidimstat/clustered_inference.py
@@ -1,10 +1,10 @@
 import numpy as np
-from sklearn.utils import resample
 from sklearn.preprocessing import StandardScaler
+from sklearn.utils import resample
 from sklearn.utils.validation import check_memory
 
+from .desparsified_lasso import desparsified_group_lasso, desparsified_lasso
 from .stat_tools import pval_from_cb
-from .desparsified_lasso import desparsified_lasso, desparsified_group_lasso
 
 
 def _subsampling(n_samples, train_size, groups=None, seed=0):
diff --git a/hidimstat/compute_importance.py b/hidimstat/compute_importance.py
index ec99a75..58437fc 100644
--- a/hidimstat/compute_importance.py
+++ b/hidimstat/compute_importance.py
@@ -1,15 +1,14 @@
+import itertools
 import warnings
 from collections import Counter
-import itertools
+
 import numpy as np
 from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor
 from sklearn.metrics import mean_absolute_error, r2_score, roc_auc_score
 from sklearn.model_selection import GridSearchCV
 
-from .RandomForestModified import (
-    RandomForestClassifierModified,
-    RandomForestRegressorModified,
-)
+from .RandomForestModified import (RandomForestClassifierModified,
+                                   RandomForestRegressorModified)
 from .utils import convert_predict_proba, ordinal_encode, sample_predictions
 
 warnings.filterwarnings("ignore")
diff --git a/hidimstat/desparsified_lasso.py b/hidimstat/desparsified_lasso.py
index a6169ce..aaa5e03 100644
--- a/hidimstat/desparsified_lasso.py
+++ b/hidimstat/desparsified_lasso.py
@@ -1,12 +1,12 @@
 import numpy as np
+from joblib import Parallel, delayed
 from numpy.linalg import multi_dot
 from scipy import stats
 from scipy.linalg import inv
-from joblib import Parallel, delayed
-from sklearn.utils.validation import check_memory
 from sklearn.linear_model import Lasso
+from sklearn.utils.validation import check_memory
 
-from .noise_std import reid, group_reid
+from .noise_std import group_reid, reid
 from .stat_tools import pval_from_two_sided_pval_and_sign
 
 
diff --git a/hidimstat/ensemble_clustered_inference.py b/hidimstat/ensemble_clustered_inference.py
index d44a277..73bbdad 100644
--- a/hidimstat/ensemble_clustered_inference.py
+++ b/hidimstat/ensemble_clustered_inference.py
@@ -1,8 +1,8 @@
 import numpy as np
 from joblib import Parallel, delayed
 
-from .multi_sample_split import aggregate_medians, aggregate_quantiles
 from .clustered_inference import clustered_inference
+from .multi_sample_split import aggregate_medians, aggregate_quantiles
 
 
 def _ensembling(
diff --git a/hidimstat/gaussian_knockoff.py b/hidimstat/gaussian_knockoff.py
index 68c8f03..6228be5 100644
--- a/hidimstat/gaussian_knockoff.py
+++ b/hidimstat/gaussian_knockoff.py
@@ -5,7 +5,8 @@
 import warnings
 
 import numpy as np
-from sklearn.covariance import GraphicalLassoCV, empirical_covariance, ledoit_wolf
+from sklearn.covariance import (GraphicalLassoCV, empirical_covariance,
+                                ledoit_wolf)
 from sklearn.utils.validation import check_memory
 
 
diff --git a/hidimstat/importance_functions.py b/hidimstat/importance_functions.py
index c6c61c8..b912d97 100644
--- a/hidimstat/importance_functions.py
+++ b/hidimstat/importance_functions.py
@@ -1,10 +1,11 @@
-from hidimstat.Dnn_learner_single import Dnn_learner_single
 import numpy as np
 from scipy.stats import ttest_1samp
 from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor
 from sklearn.model_selection import GridSearchCV
 from sklearn.preprocessing import OneHotEncoder
 
+from hidimstat.Dnn_learner_single import Dnn_learner_single
+
 
 def compute_loco(X, y, ntree=100, problem_type="regression", use_dnn=True, seed=2024):
     """
diff --git a/hidimstat/knockoff_aggregation.py b/hidimstat/knockoff_aggregation.py
index 9e7ebd8..63a53c0 100644
--- a/hidimstat/knockoff_aggregation.py
+++ b/hidimstat/knockoff_aggregation.py
@@ -6,7 +6,8 @@
 from sklearn.utils import check_random_state
 from sklearn.utils.validation import check_memory
 
-from .gaussian_knockoff import _estimate_distribution, gaussian_knockoff_generation
+from .gaussian_knockoff import (_estimate_distribution,
+                                gaussian_knockoff_generation)
 from .stat_coef_diff import stat_coef_diff
 from .utils import fdr_threshold, quantile_aggregation
 
diff --git a/hidimstat/knockoffs.py b/hidimstat/knockoffs.py
index c7c646b..d62f74a 100644
--- a/hidimstat/knockoffs.py
+++ b/hidimstat/knockoffs.py
@@ -10,7 +10,8 @@
 from sklearn.preprocessing import StandardScaler
 from sklearn.utils.validation import check_memory
 
-from .gaussian_knockoff import _estimate_distribution, gaussian_knockoff_generation
+from .gaussian_knockoff import (_estimate_distribution,
+                                gaussian_knockoff_generation)
 from .stat_coef_diff import _coef_diff_threshold, stat_coef_diff
 
 
diff --git a/hidimstat/noise_std.py b/hidimstat/noise_std.py
index 64080ef..4d953ea 100644
--- a/hidimstat/noise_std.py
+++ b/hidimstat/noise_std.py
@@ -1,6 +1,6 @@
 import numpy as np
 from numpy.linalg import norm
-from scipy.linalg import toeplitz, solve
+from scipy.linalg import solve, toeplitz
 from sklearn.linear_model import LassoCV, MultiTaskLassoCV
 from sklearn.model_selection import KFold
 
diff --git a/hidimstat/permutation_test.py b/hidimstat/permutation_test.py
index a3249bd..3492385 100644
--- a/hidimstat/permutation_test.py
+++ b/hidimstat/permutation_test.py
@@ -1,11 +1,10 @@
 import numpy as np
 from joblib import Parallel, delayed
-
 from sklearn.base import clone
-from sklearn.utils import _safe_indexing
-from sklearn.svm import LinearSVR
 from sklearn.model_selection import GridSearchCV
 from sklearn.pipeline import Pipeline
+from sklearn.svm import LinearSVR
+from sklearn.utils import _safe_indexing
 
 from hidimstat.stat_tools import pval_from_two_sided_pval_and_sign
 
diff --git a/hidimstat/standardized_svr.py b/hidimstat/standardized_svr.py
index 9158e2d..e6dcca3 100644
--- a/hidimstat/standardized_svr.py
+++ b/hidimstat/standardized_svr.py
@@ -1,8 +1,8 @@
 import numpy as np
 from numpy.linalg import norm
-from sklearn.svm import LinearSVR
 from sklearn.model_selection import GridSearchCV
 from sklearn.pipeline import Pipeline
+from sklearn.svm import LinearSVR
 
 
 def standardized_svr(X, y, Cs=np.logspace(-7, 1, 9), n_jobs=1):
diff --git a/hidimstat/test/test_BBI.py b/hidimstat/test/test_BBI.py
index b442d27..3674eab 100644
--- a/hidimstat/test/test_BBI.py
+++ b/hidimstat/test/test_BBI.py
@@ -4,10 +4,11 @@
 
 import numpy as np
 import pandas as pd
-from hidimstat.BBI import BlockBasedImportance
 from sklearn.datasets import make_classification, make_regression
 from sklearn.model_selection import train_test_split
 
+from hidimstat.BBI import BlockBasedImportance
+
 # Fixing the random seed
 rng = np.random.RandomState(2024)
 
diff --git a/hidimstat/test/test_adaptive_permutation_threshold.py b/hidimstat/test/test_adaptive_permutation_threshold.py
index 88939a1..7886253 100644
--- a/hidimstat/test/test_adaptive_permutation_threshold.py
+++ b/hidimstat/test/test_adaptive_permutation_threshold.py
@@ -5,9 +5,9 @@
 import numpy as np
 from numpy.testing import assert_almost_equal
 
+from hidimstat.adaptive_permutation_threshold import ada_svr
 from hidimstat.scenario import multivariate_1D_simulation
 from hidimstat.stat_tools import pval_from_scale
-from hidimstat.adaptive_permutation_threshold import ada_svr
 
 
 def test_ada_svr():
diff --git a/hidimstat/test/test_clustered_inference.py b/hidimstat/test/test_clustered_inference.py
index 59f0ad5..1e1a71b 100644
--- a/hidimstat/test/test_clustered_inference.py
+++ b/hidimstat/test/test_clustered_inference.py
@@ -3,13 +3,13 @@
 """
 
 import numpy as np
+from numpy.testing import assert_almost_equal
 from sklearn.cluster import FeatureAgglomeration
 from sklearn.feature_extraction import image
-from numpy.testing import assert_almost_equal
 
-from hidimstat.scenario import multivariate_1D_simulation
-from hidimstat.scenario import multivariate_temporal_simulation
 from hidimstat.clustered_inference import clustered_inference
+from hidimstat.scenario import (multivariate_1D_simulation,
+                                multivariate_temporal_simulation)
 
 
 def test_clustered_inference():
diff --git a/hidimstat/test/test_desparsified_lasso.py b/hidimstat/test/test_desparsified_lasso.py
index bd70d83..5e32d4f 100644
--- a/hidimstat/test/test_desparsified_lasso.py
+++ b/hidimstat/test/test_desparsified_lasso.py
@@ -6,10 +6,10 @@
 from numpy.testing import assert_almost_equal, assert_equal
 from scipy.linalg import toeplitz
 
-from hidimstat.scenario import multivariate_1D_simulation
-from hidimstat.scenario import multivariate_temporal_simulation
-from hidimstat.desparsified_lasso import desparsified_lasso
-from hidimstat.desparsified_lasso import desparsified_group_lasso
+from hidimstat.desparsified_lasso import (desparsified_group_lasso,
+                                          desparsified_lasso)
+from hidimstat.scenario import (multivariate_1D_simulation,
+                                multivariate_temporal_simulation)
 
 
 def test_desparsified_lasso():
diff --git a/hidimstat/test/test_ensemble_clustered_inference.py b/hidimstat/test/test_ensemble_clustered_inference.py
index bc8a7ed..926c3f5 100644
--- a/hidimstat/test/test_ensemble_clustered_inference.py
+++ b/hidimstat/test/test_ensemble_clustered_inference.py
@@ -3,13 +3,13 @@
 """
 
 import numpy as np
+from numpy.testing import assert_almost_equal
 from sklearn.cluster import FeatureAgglomeration
 from sklearn.feature_extraction import image
-from numpy.testing import assert_almost_equal
 
-from hidimstat.scenario import multivariate_1D_simulation
-from hidimstat.scenario import multivariate_temporal_simulation
 from hidimstat.ensemble_clustered_inference import ensemble_clustered_inference
+from hidimstat.scenario import (multivariate_1D_simulation,
+                                multivariate_temporal_simulation)
 
 
 def test_ensemble_clustered_inference():
diff --git a/hidimstat/test/test_generate_knockoff.py b/hidimstat/test/test_generate_knockoff.py
index 54056f7..094fdc9 100644
--- a/hidimstat/test/test_generate_knockoff.py
+++ b/hidimstat/test/test_generate_knockoff.py
@@ -2,10 +2,8 @@
 # Authors: Binh Nguyen <tuan-binh.nguyen@inria.fr>
 
 from hidimstat.data_simulation import simu_data
-from hidimstat.gaussian_knockoff import (
-    _estimate_distribution,
-    gaussian_knockoff_generation,
-)
+from hidimstat.gaussian_knockoff import (_estimate_distribution,
+                                         gaussian_knockoff_generation)
 
 SEED = 42
 fdr = 0.1
diff --git a/hidimstat/test/test_importance_funtions.py b/hidimstat/test/test_importance_funtions.py
index 8ee3127..80f6b32 100644
--- a/hidimstat/test/test_importance_funtions.py
+++ b/hidimstat/test/test_importance_funtions.py
@@ -2,11 +2,12 @@
 Test the importance functions module
 """
 
-from hidimstat.importance_functions import compute_loco
 import numpy as np
 import pandas as pd
 from sklearn.datasets import make_classification, make_regression
 
+from hidimstat.importance_functions import compute_loco
+
 # Fixing the random seed
 rng = np.random.RandomState(2024)
 
diff --git a/hidimstat/test/test_knockoff_aggregation.py b/hidimstat/test/test_knockoff_aggregation.py
index d4895b8..a20c8c8 100644
--- a/hidimstat/test/test_knockoff_aggregation.py
+++ b/hidimstat/test/test_knockoff_aggregation.py
@@ -1,4 +1,5 @@
 import numpy as np
+
 from hidimstat import knockoff_aggregation, model_x_knockoff
 from hidimstat.data_simulation import simu_data
 from hidimstat.utils import cal_fdp_power
diff --git a/hidimstat/test/test_model_x_knockoff.py b/hidimstat/test/test_model_x_knockoff.py
index 42bbae7..504e469 100644
--- a/hidimstat/test/test_model_x_knockoff.py
+++ b/hidimstat/test/test_model_x_knockoff.py
@@ -1,5 +1,5 @@
-from hidimstat.data_simulation import simu_data
 from hidimstat import model_x_knockoff
+from hidimstat.data_simulation import simu_data
 from hidimstat.utils import cal_fdp_power
 
 seed = 42
diff --git a/hidimstat/test/test_noise_std.py b/hidimstat/test/test_noise_std.py
index 6d5ec6a..82d4588 100644
--- a/hidimstat/test/test_noise_std.py
+++ b/hidimstat/test/test_noise_std.py
@@ -6,9 +6,9 @@
 from numpy.testing import assert_almost_equal
 from scipy.linalg import toeplitz
 
-from hidimstat.scenario import multivariate_1D_simulation
-from hidimstat.scenario import multivariate_temporal_simulation
-from hidimstat.noise_std import reid, group_reid, empirical_snr
+from hidimstat.noise_std import empirical_snr, group_reid, reid
+from hidimstat.scenario import (multivariate_1D_simulation,
+                                multivariate_temporal_simulation)
 
 
 def test_reid():
diff --git a/hidimstat/test/test_permutation_test.py b/hidimstat/test/test_permutation_test.py
index c33ae4e..6e1835d 100644
--- a/hidimstat/test/test_permutation_test.py
+++ b/hidimstat/test/test_permutation_test.py
@@ -5,8 +5,8 @@
 import numpy as np
 from numpy.testing import assert_almost_equal
 
-from hidimstat.scenario import multivariate_1D_simulation
 from hidimstat.permutation_test import permutation_test_cv
+from hidimstat.scenario import multivariate_1D_simulation
 
 
 def test_permutation_test():
diff --git a/hidimstat/test/test_scenario.py b/hidimstat/test/test_scenario.py
index e655e43..dc3f9e8 100644
--- a/hidimstat/test/test_scenario.py
+++ b/hidimstat/test/test_scenario.py
@@ -5,9 +5,9 @@
 import numpy as np
 from numpy.testing import assert_almost_equal, assert_equal
 
-from hidimstat.scenario import multivariate_1D_simulation
-from hidimstat.scenario import multivariate_simulation
-from hidimstat.scenario import multivariate_temporal_simulation
+from hidimstat.scenario import (multivariate_1D_simulation,
+                                multivariate_simulation,
+                                multivariate_temporal_simulation)
 
 ROI_SIZE_2D = 2
 SHAPE_2D = (12, 12)
diff --git a/hidimstat/test/test_standardized_svr.py b/hidimstat/test/test_standardized_svr.py
index 945108e..a6665c5 100644
--- a/hidimstat/test/test_standardized_svr.py
+++ b/hidimstat/test/test_standardized_svr.py
@@ -6,8 +6,8 @@
 from numpy.testing import assert_almost_equal
 
 from hidimstat.scenario import multivariate_1D_simulation
-from hidimstat.stat_tools import pval_from_scale
 from hidimstat.standardized_svr import standardized_svr
+from hidimstat.stat_tools import pval_from_scale
 
 
 def test_standardized_svr():
diff --git a/hidimstat/test/test_stat_tools.py b/hidimstat/test/test_stat_tools.py
index 7761110..9635cbf 100644
--- a/hidimstat/test/test_stat_tools.py
+++ b/hidimstat/test/test_stat_tools.py
@@ -5,18 +5,13 @@
 import numpy as np
 from numpy.testing import assert_almost_equal, assert_equal
 
-from hidimstat.stat_tools import (
-    _replace_infinity,
-    pval_corr_from_pval,
-    pval_from_scale,
-    zscore_from_cb,
-    pval_from_cb,
-    two_sided_pval_from_zscore,
-    two_sided_pval_from_cb,
-    zscore_from_pval,
-    pval_from_two_sided_pval_and_sign,
-    two_sided_pval_from_pval,
-)
+from hidimstat.stat_tools import (_replace_infinity, pval_corr_from_pval,
+                                  pval_from_cb, pval_from_scale,
+                                  pval_from_two_sided_pval_and_sign,
+                                  two_sided_pval_from_cb,
+                                  two_sided_pval_from_pval,
+                                  two_sided_pval_from_zscore, zscore_from_cb,
+                                  zscore_from_pval)
 
 
 def test__replace_infinity():
diff --git a/hidimstat/utils.py b/hidimstat/utils.py
index 1e30337..4fd16ce 100644
--- a/hidimstat/utils.py
+++ b/hidimstat/utils.py
@@ -1,6 +1,7 @@
 # -*- coding: utf-8 -*-
 # Authors: Binh Nguyen & Jerome-Alexis Chevalier & Ahmad Chamma
 import copy
+
 import numpy as np
 import torch
 import torch.nn as nn
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..ba6dcbb
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,71 @@
+[build-system]
+requires = ["hatchling", "hatch-vcs"]
+build-backend = "hatchling.build"
+
+[project]
+name = "HiDimStat"
+version = "0.0.1"
+dependencies = [
+    "joblib>=1.4.2",
+    "numpy>=2.0.0",
+    "pandas>=2.2.2",
+    "scikit-learn>=1.5.1",
+    "scipy>=1.14.0",
+    "torch>=2.3.1",
+    "torchmetrics>=1.4.0.post0",
+]
+requires-python = ">=3.12"
+authors = [{name = "HiDimStat developers"}]
+maintainers = [
+  {name = "Bertrand Thirion", email = "bertrand.thirion@inria.fr"}
+]
+description = "High-dimensional statistical inference tools for Python"
+readme = "README.md"
+classifiers = [
+    "Intended Audience :: Science/Research",
+    "Intended Audience :: Developers",
+    "Operating System :: Microsoft :: Windows",
+    "Operating System :: Unix",
+    "Operating System :: MacOS",
+    "Programming Language :: Python :: 3.12",
+    "Topic :: Software Development",
+    "Topic :: Scientific/Engineering",
+]
+license = {file = "LICENSE"}
+
+
+[project.optional-dependencies]
+# A combination of dependencies useful for developers
+
+# Requirements necessary for building the documentation
+doc = [
+    "memory_profiler>=0.61.0",
+    "mne>=1.7.1",
+    "nilearn>=0.10.4",
+    "numpydoc>=1.7.0",
+    "pillow>=10.4.0",
+    "PyQt5>=5.15.10",
+    "pyvista>=0.44.0",
+    "pyvistaqt>=0.11.1",
+    "sphinx-bootstrap-theme>=0.8.1",
+    "sphinxcontrib-bibtex>=2.6.2",
+    "sphinx-gallery>=0.16.0",
+]
+plotting = [
+    "matplotlib>=3.9.1",
+]
+style = [
+    "black>=24.4.2",
+    "isort>=5.13.2",
+]
+# For running unit and docstring tests
+test = [
+    "coverage>=7.6.0",
+    "pytest>=8.2.2",
+    "pytest-cov>=5.0.0"
+]
+
+[project.urls]
+Development = "https://github.com/nilearn/nilearn"
+Homepage = "https://mind-inria.github.io/hidimstat"
+Repository = "https://github.com/mind-inria/hidimstat"
diff --git a/requirements.txt b/requirements.txt
deleted file mode 100644
index 2372b18..0000000
--- a/requirements.txt
+++ /dev/null
@@ -1,9 +0,0 @@
---extra-index-url https://download.pytorch.org/whl/cpu
-numpy
-joblib
-scipy
-scikit-learn
-torch
-torchmetrics
-pandas
-mne
diff --git a/setup.py b/setup.py
deleted file mode 100644
index 67a37e1..0000000
--- a/setup.py
+++ /dev/null
@@ -1,65 +0,0 @@
-#!/usr/bin/env python
-
-import os
-import sys
-
-from setuptools import find_packages
-
-PKG = "hidimstat"
-DESCRIPTION = "High-dimensional statistical inference tools for Python"
-LONG_DESCRIPTION = open("README.md").read()
-MAINTAINER = "Chevalier (ja-che), Nguyen (tbng), Alexandre Blain (alexblnn), Ahmad Chamma (achamma723) and Bertrand Thirion (bthirion)"
-MAINTAINER_EMAIL = "bertrand.thirion@inria.fr"
-URL = "https://github.com/Parietal-INRIA/hidimstat"
-DOWNLOAD_URL = "https://github.com/Parietal-INRIA/hidimstat"
-LICENSE = "BSD"
-
-
-def load_version():
-    """Executes hidimstat/version.py in a globals dictionary and return it.
-    Following format from Nilearn repo on github.
-    """
-    # load all vars into globals, otherwise
-    #   the later function call using global vars doesn't work.
-    globals_dict = {}
-    with open(os.path.join("hidimstat", "version.py")) as fp:
-        exec(fp.read(), globals_dict)
-
-    return globals_dict
-
-
-def setup_package(version):
-    local_path = os.path.dirname(os.path.abspath(sys.argv[0]))
-
-    os.chdir(local_path)
-    sys.path.insert(0, local_path)
-
-    from numpy.distutils.core import setup
-
-    setup(
-        packages=find_packages(exclude=["contrib", "docs", "tests"]),
-        name=PKG,
-        maintainer=MAINTAINER,
-        include_package_data=True,
-        maintainer_email=MAINTAINER_EMAIL,
-        description=DESCRIPTION,
-        long_description=LONG_DESCRIPTION,
-        long_description_content_type="text/markdown",
-        license=LICENSE,
-        url=URL,
-        version=version,
-        # download_url=DOWNLOAD_URL,
-        zip_safe=False,  # the package can run out of an .egg file
-        classifiers=[
-            "Programming Language :: Python",
-            "Programming Language :: Python :: 3.5",
-            "Development Status :: 3 - Alpha",
-        ],
-    )
-
-
-_VERSION_GLOBALS = load_version()
-VERSION = _VERSION_GLOBALS["__version__"]
-
-if __name__ == "__main__":
-    setup_package(VERSION)