diff --git a/pf2/figures/figureA2d_j.py b/pf2/figures/figureA2d_j.py
index f7b7ba7..8bbcb7c 100644
--- a/pf2/figures/figureA2d_j.py
+++ b/pf2/figures/figureA2d_j.py
@@ -30,7 +30,7 @@ def makeFigure():
     ax[0].yaxis.set_ticklabels([])
     
     plot_eigenstate_factors(X, ax[1])
-    plot_gene_factors(X, ax[2], save_genes=True)
+    plot_gene_factors(X, ax[2])
     ax[2].yaxis.set_ticklabels([])
     
     X = X[X.obs["patient_category"] != "Non-Pneumonia Control"] 
diff --git a/pyproject.toml b/pyproject.toml
index 5c437e9..6572865 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -14,7 +14,7 @@ dependencies = [
     "scikit-learn>=1.5",
     "tensorly>=0.8.1",
     "numpy>=1.26.2",
-    "parafac2 @ git+https://github.com/meyer-lab/parafac2.git@6600c677a77d0f242668babf39559cf7953ff534",
+    "parafac2 @ git+https://github.com/meyer-lab/parafac2.git@ccf708fe71c78a106151643e893ea006bba865d9",
     "rise @ git+https://github.com/meyer-lab/RISE.git",
     "pacmap>=0.7.3",
     "anndata>=0.10.3",
@@ -23,8 +23,11 @@ dependencies = [
     "dask[dataframe]>=2024.5.0",
     "setuptools>=69.5",
     "doubletdetection>=4.2",
-    "networkx>=3.3"
-, "gseapy~=1.1.6"]
+    "networkx>=3.3",
+    "gseapy~=1.1.6",
+    "statsmodels>=0.14.5",
+    "scipy<=1.15.3",
+]
 
 
 readme = "README.md"
diff --git a/requirements-dev.lock b/requirements-dev.lock
index 67bba79..9214cec 100644
--- a/requirements-dev.lock
+++ b/requirements-dev.lock
@@ -11,41 +11,23 @@
 
 -e file:.
 absl-py==2.3.0
-    # via chex
-    # via ml-collections
-    # via optax
-    # via orbax-checkpoint
-    # via tensorboard
-aiohappyeyeballs==2.6.1
-    # via aiohttp
-aiohttp==3.12.4
-    # via fsspec
-aiosignal==1.3.2
-    # via aiohttp
+    # via ortools
 anndata==0.11.4
     # via doubletdetection
-    # via mudata
     # via parafac2
     # via pf2
     # via rise
     # via scanpy
-    # via scib
-    # via scvi-tools
 annoy==1.17.3
     # via pacmap
-    # via scanorama
 array-api-compat==1.8
     # via anndata
 asttokens==2.4.1
     # via stack-data
-attrs==25.3.0
-    # via aiohttp
 certifi==2024.8.30
     # via requests
 charset-normalizer==3.3.2
     # via requests
-chex==0.1.89
-    # via optax
 click==8.1.7
     # via dask
 cloudpickle==3.0.0
@@ -58,7 +40,7 @@ contourpy==1.3.0
     # via matplotlib
 coverage==7.6.1
     # via pytest-cov
-cupy-cuda12x==13.3.0
+cupy-cuda12x==13.5.1
     # via parafac2
 cycler==0.12.1
     # via matplotlib
@@ -74,42 +56,17 @@ datashader==0.16.3
     # via rise
 decorator==5.1.1
     # via ipython
-deprecated==1.2.18
-    # via scib
-docrep==0.3.2
-    # via scvi-tools
 doubletdetection==4.2
     # via pf2
     # via rise
-etils==1.12.2
-    # via optax
-    # via orbax-checkpoint
 executing==2.1.0
     # via stack-data
 fastrlock==0.8.2
     # via cupy-cuda12x
-fbpca==1.0
-    # via geosketch
-    # via scanorama
-filelock==3.18.0
-    # via torch
-flax==0.10.6
-    # via scvi-tools
 fonttools==4.53.1
     # via matplotlib
-frozenlist==1.6.0
-    # via aiohttp
-    # via aiosignal
 fsspec==2024.9.0
     # via dask
-    # via etils
-    # via lightning
-    # via pytorch-lightning
-    # via torch
-geosketch==1.3
-    # via scanorama
-grpcio==1.71.0
-    # via tensorboard
 gseapy==1.1.6
     # via pf2
     # via rise
@@ -119,45 +76,21 @@ h5py==3.11.0
     # via anndata
     # via h5netcdf
     # via scanpy
-    # via scib
-harmonypy==0.0.10
-    # via rise
-humanize==4.12.3
-    # via orbax-checkpoint
 idna==3.8
     # via requests
-    # via yarl
 igraph==0.11.6
     # via leidenalg
     # via louvain
-    # via scib
-importlib-resources==6.5.2
-    # via etils
+immutabledict==4.2.1
+    # via ortools
 iniconfig==2.0.0
     # via pytest
-intervaltree==3.1.0
-    # via scanorama
 ipython==8.27.0
     # via ipywidgets
 ipywidgets==8.1.5
     # via doubletdetection
-jax==0.6.1
-    # via chex
-    # via flax
-    # via numpyro
-    # via optax
-    # via orbax-checkpoint
-    # via scvi-tools
-jaxlib==0.6.1
-    # via chex
-    # via jax
-    # via numpyro
-    # via optax
-    # via scvi-tools
 jedi==0.19.1
     # via ipython
-jinja2==3.1.6
-    # via torch
 joblib==1.4.2
     # via pynndescent
     # via scanpy
@@ -171,70 +104,30 @@ legacy-api-wrap==1.4.1
 leidenalg==0.10.2
     # via doubletdetection
     # via phenograph
-    # via rise
-    # via scib
-lightning==2.5.1.post0
-    # via scvi-tools
-lightning-utilities==0.14.3
-    # via lightning
-    # via pytorch-lightning
-    # via torchmetrics
 llvmlite==0.44.0
     # via numba
     # via pynndescent
-    # via scib
 locket==1.0.0
     # via partd
 louvain==0.8.2
     # via doubletdetection
-markdown==3.8
-    # via tensorboard
-markdown-it-py==3.0.0
-    # via rich
-markupsafe==3.0.2
-    # via jinja2
-    # via werkzeug
 matplotlib==3.9.2
     # via doubletdetection
     # via gseapy
     # via pf2
-    # via scanorama
     # via scanpy
-    # via scib
     # via seaborn
     # via tlviz
 matplotlib-inline==0.1.7
     # via ipython
-mdurl==0.1.2
-    # via markdown-it-py
-ml-collections==1.1.0
-    # via scvi-tools
-ml-dtypes==0.5.1
-    # via jax
-    # via jaxlib
-    # via tensorstore
-mpmath==1.3.0
-    # via sympy
-msgpack==1.1.0
-    # via flax
-    # via orbax-checkpoint
-mudata==0.3.2
-    # via scvi-tools
-multidict==6.4.4
-    # via aiohttp
-    # via yarl
 multipledispatch==1.0.0
     # via datashader
-    # via numpyro
 natsort==8.4.0
     # via anndata
     # via scanpy
-nest-asyncio==1.6.0
-    # via orbax-checkpoint
 networkx==3.3
     # via pf2
     # via scanpy
-    # via torch
 nodeenv==1.9.1
     # via pyright
 numba==0.61.2
@@ -242,31 +135,19 @@ numba==0.61.2
     # via pacmap
     # via pynndescent
     # via scanpy
-    # via scib
-    # via scvi-tools
-    # via sparse
     # via umap-learn
 numpy==2.2.6
     # via anndata
-    # via chex
     # via contourpy
     # via cupy-cuda12x
     # via dask
     # via datashader
     # via doubletdetection
-    # via flax
-    # via geosketch
     # via gseapy
     # via h5py
-    # via harmonypy
-    # via jax
-    # via jaxlib
     # via matplotlib
-    # via ml-dtypes
     # via numba
-    # via numpyro
-    # via optax
-    # via orbax-checkpoint
+    # via ortools
     # via pacmap
     # via pandas
     # via parafac2
@@ -274,87 +155,29 @@ numpy==2.2.6
     # via pf2
     # via phenograph
     # via pyarrow
-    # via pyro-ppl
     # via rise
-    # via scanorama
     # via scanpy
-    # via scib
     # via scikit-learn
-    # via scikit-misc
     # via scipy
-    # via scvi-tools
     # via seaborn
-    # via sparse
     # via statsmodels
-    # via tensorboard
     # via tensorly
-    # via tensorstore
     # via tlviz
-    # via torchmetrics
-    # via treescope
     # via umap-learn
     # via xarray
-numpyro==0.18.0
-    # via scvi-tools
-nvidia-cublas-cu12==12.6.4.1
-    # via nvidia-cudnn-cu12
-    # via nvidia-cusolver-cu12
-    # via torch
-nvidia-cuda-cupti-cu12==12.6.80
-    # via torch
-nvidia-cuda-nvrtc-cu12==12.6.77
-    # via torch
-nvidia-cuda-runtime-cu12==12.6.77
-    # via torch
-nvidia-cudnn-cu12==9.5.1.17
-    # via torch
-nvidia-cufft-cu12==11.3.0.4
-    # via torch
-nvidia-cufile-cu12==1.11.1.6
-    # via torch
-nvidia-curand-cu12==10.3.7.77
-    # via torch
-nvidia-cusolver-cu12==11.7.1.2
-    # via torch
-nvidia-cusparse-cu12==12.5.4.2
-    # via nvidia-cusolver-cu12
-    # via torch
-nvidia-cusparselt-cu12==0.6.3
-    # via torch
-nvidia-nccl-cu12==2.26.2
-    # via torch
-nvidia-nvjitlink-cu12==12.6.85
-    # via nvidia-cufft-cu12
-    # via nvidia-cusolver-cu12
-    # via nvidia-cusparse-cu12
-    # via torch
-nvidia-nvtx-cu12==12.6.77
-    # via torch
-opt-einsum==3.4.0
-    # via jax
-    # via pyro-ppl
-optax==0.2.4
-    # via flax
-    # via scvi-tools
-orbax-checkpoint==0.11.13
-    # via flax
+ortools==9.14.6206
+    # via rise
 packaging==24.2
     # via anndata
     # via dask
     # via datashader
     # via h5netcdf
-    # via lightning
-    # via lightning-utilities
     # via matplotlib
     # via pytest
-    # via pytorch-lightning
     # via scanpy
     # via statsmodels
-    # via tensorboard
-    # via torchmetrics
     # via xarray
 pacmap==0.7.3
-    # via parafac2
     # via pf2
     # via rise
 pandas==2.2.2
@@ -364,17 +187,15 @@ pandas==2.2.2
     # via datashader
     # via doubletdetection
     # via gseapy
-    # via harmonypy
+    # via ortools
     # via pf2
     # via rise
     # via scanpy
-    # via scib
-    # via scvi-tools
     # via seaborn
     # via statsmodels
     # via tlviz
     # via xarray
-parafac2 @ git+https://github.com/meyer-lab/parafac2.git@6600c677a77d0f242668babf39559cf7953ff534
+parafac2 @ git+https://github.com/meyer-lab/parafac2.git@ccf708fe71c78a106151643e893ea006bba865d9
     # via pf2
     # via rise
 param==2.1.1
@@ -398,12 +219,8 @@ pluggy==1.5.0
     # via pytest
 prompt-toolkit==3.0.47
     # via ipython
-propcache==0.3.1
-    # via aiohttp
-    # via yarl
 protobuf==6.31.1
-    # via orbax-checkpoint
-    # via tensorboard
+    # via ortools
 psutil==6.0.0
     # via phenograph
 ptyprocess==0.7.0
@@ -414,214 +231,116 @@ pyarrow==17.0.0
     # via dask-expr
 pyct==0.5.0
     # via datashader
-pydot==4.0.0
-    # via scib
 pygments==2.18.0
     # via ipython
-    # via rich
 pynndescent==0.5.13
     # via scanpy
     # via umap-learn
 pyparsing==3.1.4
     # via matplotlib
-    # via pydot
 pyright==1.1.380
-pyro-api==0.1.2
-    # via pyro-ppl
-pyro-ppl==1.9.1
-    # via scvi-tools
 pytest==8.3.3
     # via pytest-cov
 pytest-cov==5.0.0
 python-dateutil==2.9.0.post0
     # via matplotlib
     # via pandas
-pytorch-lightning==2.5.1.post0
-    # via lightning
 pytz==2024.2
     # via pandas
 pyyaml==6.0.2
     # via dask
-    # via flax
-    # via lightning
-    # via ml-collections
-    # via orbax-checkpoint
-    # via pytorch-lightning
 requests==2.32.3
     # via datashader
     # via gseapy
     # via tlviz
-rich==14.0.0
-    # via flax
-    # via scvi-tools
-rise @ git+https://github.com/meyer-lab/RISE.git@7a2f63cd238b6afd3670eff73b4fcdc0f8c7230a
+rise @ git+https://github.com/meyer-lab/RISE.git@f160a1b7a8598627bf507a37e771d2c811a58527
     # via pf2
-scanorama==1.7.4
-    # via rise
 scanpy==1.11.2
     # via doubletdetection
     # via pf2
     # via rise
-    # via scib
-scib==1.1.7
-    # via rise
 scikit-learn==1.6.1
-    # via geosketch
-    # via harmonypy
     # via pacmap
-    # via parafac2
     # via pf2
     # via phenograph
     # via pynndescent
     # via rise
-    # via scanorama
     # via scanpy
-    # via scib
-    # via scvi-tools
     # via umap-learn
-scikit-misc==0.5.1
-    # via scib
-scipy==1.14.1
+scipy==1.15.3
     # via anndata
     # via datashader
     # via doubletdetection
     # via gseapy
-    # via harmonypy
-    # via jax
-    # via jaxlib
     # via parafac2
+    # via pf2
     # via phenograph
     # via pynndescent
     # via rise
-    # via scanorama
     # via scanpy
-    # via scib
     # via scikit-learn
-    # via scvi-tools
     # via statsmodels
     # via tensorly
     # via tlviz
     # via umap-learn
-scvi-tools==1.3.1.post1
-    # via rise
 seaborn==0.13.2
     # via rise
     # via scanpy
-    # via scib
 session-info2==0.1.2
     # via scanpy
 setuptools==74.1.2
-    # via chex
-    # via lightning-utilities
     # via pf2
     # via phenograph
-    # via tensorboard
-    # via torch
-    # via triton
-simplejson==3.20.1
-    # via orbax-checkpoint
 six==1.16.0
     # via asttokens
-    # via docrep
     # via patsy
     # via python-dateutil
-    # via tensorboard
-sortedcontainers==2.4.0
-    # via intervaltree
-sparse==0.17.0
-    # via scvi-tools
 stack-data==0.6.3
     # via ipython
-statsmodels==0.14.4
+statsmodels==0.14.5
+    # via pf2
     # via rise
     # via scanpy
     # via tlviz
-sympy==1.14.0
-    # via torch
-tensorboard==2.19.0
-    # via scvi-tools
-tensorboard-data-server==0.7.2
-    # via tensorboard
 tensorly==0.8.1
     # via parafac2
     # via pf2
     # via rise
-tensorstore==0.1.75
-    # via flax
-    # via orbax-checkpoint
 texttable==1.7.0
     # via igraph
 threadpoolctl==3.5.0
     # via scikit-learn
 tlviz==0.1.1
-    # via parafac2
     # via pf2
     # via rise
 toolz==0.12.1
-    # via chex
     # via dask
     # via datashader
     # via partd
-torch==2.7.0
-    # via lightning
-    # via pyro-ppl
-    # via pytorch-lightning
-    # via scvi-tools
-    # via torchmetrics
-torchmetrics==1.7.2
-    # via lightning
-    # via pytorch-lightning
-    # via scvi-tools
 tqdm==4.66.5
     # via doubletdetection
-    # via lightning
-    # via numpyro
     # via parafac2
-    # via pyro-ppl
-    # via pytorch-lightning
     # via rise
     # via scanpy
-    # via scvi-tools
     # via umap-learn
 traitlets==5.14.3
     # via comm
     # via ipython
     # via ipywidgets
     # via matplotlib-inline
-treescope==0.1.9
-    # via flax
-triton==3.3.0
-    # via torch
 typing-extensions==4.13.2
-    # via chex
-    # via etils
-    # via flax
-    # via lightning
-    # via lightning-utilities
-    # via orbax-checkpoint
-    # via pytorch-lightning
+    # via ortools
     # via scanpy
-    # via torch
 tzdata==2024.1
     # via pandas
 umap-learn==0.5.6
     # via scanpy
-    # via scib
 urllib3==2.2.3
     # via requests
 wcwidth==0.2.13
     # via prompt-toolkit
-werkzeug==3.1.3
-    # via tensorboard
 widgetsnbextension==4.0.13
     # via ipywidgets
-wrapt==1.17.2
-    # via deprecated
 xarray==2024.9.0
     # via datashader
-    # via scvi-tools
     # via tlviz
-yarl==1.20.0
-    # via aiohttp
-zipp==3.22.0
-    # via etils
diff --git a/requirements.lock b/requirements.lock
index 1c3e9db..b560815 100644
--- a/requirements.lock
+++ b/requirements.lock
@@ -11,41 +11,23 @@
 
 -e file:.
 absl-py==2.3.0
-    # via chex
-    # via ml-collections
-    # via optax
-    # via orbax-checkpoint
-    # via tensorboard
-aiohappyeyeballs==2.6.1
-    # via aiohttp
-aiohttp==3.12.4
-    # via fsspec
-aiosignal==1.3.2
-    # via aiohttp
+    # via ortools
 anndata==0.11.4
     # via doubletdetection
-    # via mudata
     # via parafac2
     # via pf2
     # via rise
     # via scanpy
-    # via scib
-    # via scvi-tools
 annoy==1.17.3
     # via pacmap
-    # via scanorama
 array-api-compat==1.8
     # via anndata
 asttokens==2.4.1
     # via stack-data
-attrs==25.3.0
-    # via aiohttp
 certifi==2024.8.30
     # via requests
 charset-normalizer==3.3.2
     # via requests
-chex==0.1.89
-    # via optax
 click==8.1.7
     # via dask
 cloudpickle==3.0.0
@@ -56,7 +38,7 @@ comm==0.2.2
     # via ipywidgets
 contourpy==1.3.0
     # via matplotlib
-cupy-cuda12x==13.3.0
+cupy-cuda12x==13.5.1
     # via parafac2
 cycler==0.12.1
     # via matplotlib
@@ -72,42 +54,17 @@ datashader==0.16.3
     # via rise
 decorator==5.1.1
     # via ipython
-deprecated==1.2.18
-    # via scib
-docrep==0.3.2
-    # via scvi-tools
 doubletdetection==4.2
     # via pf2
     # via rise
-etils==1.12.2
-    # via optax
-    # via orbax-checkpoint
 executing==2.1.0
     # via stack-data
 fastrlock==0.8.2
     # via cupy-cuda12x
-fbpca==1.0
-    # via geosketch
-    # via scanorama
-filelock==3.18.0
-    # via torch
-flax==0.10.6
-    # via scvi-tools
 fonttools==4.53.1
     # via matplotlib
-frozenlist==1.6.0
-    # via aiohttp
-    # via aiosignal
 fsspec==2024.9.0
     # via dask
-    # via etils
-    # via lightning
-    # via pytorch-lightning
-    # via torch
-geosketch==1.3
-    # via scanorama
-grpcio==1.71.0
-    # via tensorboard
 gseapy==1.1.6
     # via pf2
     # via rise
@@ -117,43 +74,19 @@ h5py==3.11.0
     # via anndata
     # via h5netcdf
     # via scanpy
-    # via scib
-harmonypy==0.0.10
-    # via rise
-humanize==4.12.3
-    # via orbax-checkpoint
 idna==3.8
     # via requests
-    # via yarl
 igraph==0.11.6
     # via leidenalg
     # via louvain
-    # via scib
-importlib-resources==6.5.2
-    # via etils
-intervaltree==3.1.0
-    # via scanorama
+immutabledict==4.2.1
+    # via ortools
 ipython==8.27.0
     # via ipywidgets
 ipywidgets==8.1.5
     # via doubletdetection
-jax==0.6.1
-    # via chex
-    # via flax
-    # via numpyro
-    # via optax
-    # via orbax-checkpoint
-    # via scvi-tools
-jaxlib==0.6.1
-    # via chex
-    # via jax
-    # via numpyro
-    # via optax
-    # via scvi-tools
 jedi==0.19.1
     # via ipython
-jinja2==3.1.6
-    # via torch
 joblib==1.4.2
     # via pynndescent
     # via scanpy
@@ -167,100 +100,48 @@ legacy-api-wrap==1.4.1
 leidenalg==0.10.2
     # via doubletdetection
     # via phenograph
-    # via rise
-    # via scib
-lightning==2.5.1.post0
-    # via scvi-tools
-lightning-utilities==0.14.3
-    # via lightning
-    # via pytorch-lightning
-    # via torchmetrics
 llvmlite==0.44.0
     # via numba
     # via pynndescent
-    # via scib
 locket==1.0.0
     # via partd
 louvain==0.8.2
     # via doubletdetection
-markdown==3.8
-    # via tensorboard
-markdown-it-py==3.0.0
-    # via rich
-markupsafe==3.0.2
-    # via jinja2
-    # via werkzeug
 matplotlib==3.9.2
     # via doubletdetection
     # via gseapy
     # via pf2
-    # via scanorama
     # via scanpy
-    # via scib
     # via seaborn
     # via tlviz
 matplotlib-inline==0.1.7
     # via ipython
-mdurl==0.1.2
-    # via markdown-it-py
-ml-collections==1.1.0
-    # via scvi-tools
-ml-dtypes==0.5.1
-    # via jax
-    # via jaxlib
-    # via tensorstore
-mpmath==1.3.0
-    # via sympy
-msgpack==1.1.0
-    # via flax
-    # via orbax-checkpoint
-mudata==0.3.2
-    # via scvi-tools
-multidict==6.4.4
-    # via aiohttp
-    # via yarl
 multipledispatch==1.0.0
     # via datashader
-    # via numpyro
 natsort==8.4.0
     # via anndata
     # via scanpy
-nest-asyncio==1.6.0
-    # via orbax-checkpoint
 networkx==3.3
     # via pf2
     # via scanpy
-    # via torch
 numba==0.61.2
     # via datashader
     # via pacmap
     # via pynndescent
     # via scanpy
-    # via scib
-    # via scvi-tools
-    # via sparse
     # via umap-learn
 numpy==2.2.6
     # via anndata
-    # via chex
     # via contourpy
     # via cupy-cuda12x
     # via dask
     # via datashader
     # via doubletdetection
-    # via flax
-    # via geosketch
     # via gseapy
     # via h5py
-    # via harmonypy
-    # via jax
-    # via jaxlib
     # via matplotlib
-    # via ml-dtypes
     # via numba
-    # via numpyro
-    # via optax
-    # via orbax-checkpoint
+    # via ortools
     # via pacmap
     # via pandas
     # via parafac2
@@ -268,86 +149,28 @@ numpy==2.2.6
     # via pf2
     # via phenograph
     # via pyarrow
-    # via pyro-ppl
     # via rise
-    # via scanorama
     # via scanpy
-    # via scib
     # via scikit-learn
-    # via scikit-misc
     # via scipy
-    # via scvi-tools
     # via seaborn
-    # via sparse
     # via statsmodels
-    # via tensorboard
     # via tensorly
-    # via tensorstore
     # via tlviz
-    # via torchmetrics
-    # via treescope
     # via umap-learn
     # via xarray
-numpyro==0.18.0
-    # via scvi-tools
-nvidia-cublas-cu12==12.6.4.1
-    # via nvidia-cudnn-cu12
-    # via nvidia-cusolver-cu12
-    # via torch
-nvidia-cuda-cupti-cu12==12.6.80
-    # via torch
-nvidia-cuda-nvrtc-cu12==12.6.77
-    # via torch
-nvidia-cuda-runtime-cu12==12.6.77
-    # via torch
-nvidia-cudnn-cu12==9.5.1.17
-    # via torch
-nvidia-cufft-cu12==11.3.0.4
-    # via torch
-nvidia-cufile-cu12==1.11.1.6
-    # via torch
-nvidia-curand-cu12==10.3.7.77
-    # via torch
-nvidia-cusolver-cu12==11.7.1.2
-    # via torch
-nvidia-cusparse-cu12==12.5.4.2
-    # via nvidia-cusolver-cu12
-    # via torch
-nvidia-cusparselt-cu12==0.6.3
-    # via torch
-nvidia-nccl-cu12==2.26.2
-    # via torch
-nvidia-nvjitlink-cu12==12.6.85
-    # via nvidia-cufft-cu12
-    # via nvidia-cusolver-cu12
-    # via nvidia-cusparse-cu12
-    # via torch
-nvidia-nvtx-cu12==12.6.77
-    # via torch
-opt-einsum==3.4.0
-    # via jax
-    # via pyro-ppl
-optax==0.2.4
-    # via flax
-    # via scvi-tools
-orbax-checkpoint==0.11.13
-    # via flax
+ortools==9.14.6206
+    # via rise
 packaging==24.2
     # via anndata
     # via dask
     # via datashader
     # via h5netcdf
-    # via lightning
-    # via lightning-utilities
     # via matplotlib
-    # via pytorch-lightning
     # via scanpy
     # via statsmodels
-    # via tensorboard
-    # via torchmetrics
     # via xarray
 pacmap==0.7.3
-    # via parafac2
     # via pf2
     # via rise
 pandas==2.2.2
@@ -357,17 +180,15 @@ pandas==2.2.2
     # via datashader
     # via doubletdetection
     # via gseapy
-    # via harmonypy
+    # via ortools
     # via pf2
     # via rise
     # via scanpy
-    # via scib
-    # via scvi-tools
     # via seaborn
     # via statsmodels
     # via tlviz
     # via xarray
-parafac2 @ git+https://github.com/meyer-lab/parafac2.git@6600c677a77d0f242668babf39559cf7953ff534
+parafac2 @ git+https://github.com/meyer-lab/parafac2.git@ccf708fe71c78a106151643e893ea006bba865d9
     # via pf2
     # via rise
 param==2.1.1
@@ -389,12 +210,8 @@ pillow==10.4.0
     # via matplotlib
 prompt-toolkit==3.0.47
     # via ipython
-propcache==0.3.1
-    # via aiohttp
-    # via yarl
 protobuf==6.31.1
-    # via orbax-checkpoint
-    # via tensorboard
+    # via ortools
 psutil==6.0.0
     # via phenograph
 ptyprocess==0.7.0
@@ -405,210 +222,112 @@ pyarrow==17.0.0
     # via dask-expr
 pyct==0.5.0
     # via datashader
-pydot==4.0.0
-    # via scib
 pygments==2.18.0
     # via ipython
-    # via rich
 pynndescent==0.5.13
     # via scanpy
     # via umap-learn
 pyparsing==3.1.4
     # via matplotlib
-    # via pydot
-pyro-api==0.1.2
-    # via pyro-ppl
-pyro-ppl==1.9.1
-    # via scvi-tools
 python-dateutil==2.9.0.post0
     # via matplotlib
     # via pandas
-pytorch-lightning==2.5.1.post0
-    # via lightning
 pytz==2024.2
     # via pandas
 pyyaml==6.0.2
     # via dask
-    # via flax
-    # via lightning
-    # via ml-collections
-    # via orbax-checkpoint
-    # via pytorch-lightning
 requests==2.32.3
     # via datashader
     # via gseapy
     # via tlviz
-rich==14.0.0
-    # via flax
-    # via scvi-tools
-rise @ git+https://github.com/meyer-lab/RISE.git@7a2f63cd238b6afd3670eff73b4fcdc0f8c7230a
+rise @ git+https://github.com/meyer-lab/RISE.git@f160a1b7a8598627bf507a37e771d2c811a58527
     # via pf2
-scanorama==1.7.4
-    # via rise
 scanpy==1.11.2
     # via doubletdetection
     # via pf2
     # via rise
-    # via scib
-scib==1.1.7
-    # via rise
 scikit-learn==1.6.1
-    # via geosketch
-    # via harmonypy
     # via pacmap
-    # via parafac2
     # via pf2
     # via phenograph
     # via pynndescent
     # via rise
-    # via scanorama
     # via scanpy
-    # via scib
-    # via scvi-tools
     # via umap-learn
-scikit-misc==0.5.1
-    # via scib
-scipy==1.14.1
+scipy==1.15.3
     # via anndata
     # via datashader
     # via doubletdetection
     # via gseapy
-    # via harmonypy
-    # via jax
-    # via jaxlib
     # via parafac2
+    # via pf2
     # via phenograph
     # via pynndescent
     # via rise
-    # via scanorama
     # via scanpy
-    # via scib
     # via scikit-learn
-    # via scvi-tools
     # via statsmodels
     # via tensorly
     # via tlviz
     # via umap-learn
-scvi-tools==1.3.1.post1
-    # via rise
 seaborn==0.13.2
     # via rise
     # via scanpy
-    # via scib
 session-info2==0.1.2
     # via scanpy
 setuptools==74.1.2
-    # via chex
-    # via lightning-utilities
     # via pf2
     # via phenograph
-    # via tensorboard
-    # via torch
-    # via triton
-simplejson==3.20.1
-    # via orbax-checkpoint
 six==1.16.0
     # via asttokens
-    # via docrep
     # via patsy
     # via python-dateutil
-    # via tensorboard
-sortedcontainers==2.4.0
-    # via intervaltree
-sparse==0.17.0
-    # via scvi-tools
 stack-data==0.6.3
     # via ipython
-statsmodels==0.14.4
+statsmodels==0.14.5
+    # via pf2
     # via rise
     # via scanpy
     # via tlviz
-sympy==1.14.0
-    # via torch
-tensorboard==2.19.0
-    # via scvi-tools
-tensorboard-data-server==0.7.2
-    # via tensorboard
 tensorly==0.8.1
     # via parafac2
     # via pf2
     # via rise
-tensorstore==0.1.75
-    # via flax
-    # via orbax-checkpoint
 texttable==1.7.0
     # via igraph
 threadpoolctl==3.5.0
     # via scikit-learn
 tlviz==0.1.1
-    # via parafac2
     # via pf2
     # via rise
 toolz==0.12.1
-    # via chex
     # via dask
     # via datashader
     # via partd
-torch==2.7.0
-    # via lightning
-    # via pyro-ppl
-    # via pytorch-lightning
-    # via scvi-tools
-    # via torchmetrics
-torchmetrics==1.7.2
-    # via lightning
-    # via pytorch-lightning
-    # via scvi-tools
 tqdm==4.66.5
     # via doubletdetection
-    # via lightning
-    # via numpyro
     # via parafac2
-    # via pyro-ppl
-    # via pytorch-lightning
     # via rise
     # via scanpy
-    # via scvi-tools
     # via umap-learn
 traitlets==5.14.3
     # via comm
     # via ipython
     # via ipywidgets
     # via matplotlib-inline
-treescope==0.1.9
-    # via flax
-triton==3.3.0
-    # via torch
 typing-extensions==4.13.2
-    # via chex
-    # via etils
-    # via flax
-    # via lightning
-    # via lightning-utilities
-    # via orbax-checkpoint
-    # via pytorch-lightning
+    # via ortools
     # via scanpy
-    # via torch
 tzdata==2024.1
     # via pandas
 umap-learn==0.5.6
     # via scanpy
-    # via scib
 urllib3==2.2.3
     # via requests
 wcwidth==0.2.13
     # via prompt-toolkit
-werkzeug==3.1.3
-    # via tensorboard
 widgetsnbextension==4.0.13
     # via ipywidgets
-wrapt==1.17.2
-    # via deprecated
 xarray==2024.9.0
     # via datashader
-    # via scvi-tools
     # via tlviz
-yarl==1.20.0
-    # via aiohttp
-zipp==3.22.0
-    # via etils