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Online doc update 03 26 run2 #106

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ramosv merged 2 commits into from
Mar 25, 2026
+3 −22
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Online doc update 03 26 run2 #106

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633fe42
added tqdm due to error from read the docs build
ramosv Mar 25, 2026
fe77798
removed old reference from manifest
ramosv Mar 25, 2026
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1 change: 0 additions & 1 deletion MANIFEST.in
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Expand Up @@ -16,7 +16,6 @@ recursive-include bioneuralnet/datasets/example *.csv
recursive-include bioneuralnet/datasets/brca *.csv
recursive-include bioneuralnet/datasets/lgg *.csv
recursive-include bioneuralnet/datasets/kipan *.csv
recursive-include bioneuralnet/datasets/paad *.csv

# Include documentation source files
prune docs
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1 change: 1 addition & 0 deletions docs/requirements.txt
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Expand Up @@ -7,3 +7,4 @@ nbsphinx
myst_nb
furo
sphinx-copybutton
tqdm
21 changes: 0 additions & 21 deletions docs/source/gnns.rst
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Expand Up @@ -94,25 +94,4 @@ How DPMON Utilizes GNN Embeddings

`View full-size image: Disease Prediction (DPMON) <https://bioneuralnet.readthedocs.io/en/latest/_images/DPMON.png>`_

Example Code: Training a GNN Embedding Model
--------------------------------------------
Below is a simplified example showing how to train GNN embeddings guided by phenotype correlations:

.. code-block:: python

from bioneuralnet.network_embedding import GNNEmbedding
import pandas as pd

gnn = GNNEmbedding(
adjacency_matrix=adjacency_matrix,
omics_data=omics_data,
phenotype_data=phenotype_data,
clinical_data=clinical_data,
phenotype_col='finalgold_visit',
model_type='GAT',
hidden_dim=64
)
gnn.fit()
node_embeds = gnn.embed()

Return to :doc:`../index`
1 change: 1 addition & 0 deletions requirements.txt
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Expand Up @@ -8,5 +8,6 @@ python-louvain
pydantic
ray[tune]
statsmodels
tqdm
# torch
# torch_geometric
1 change: 1 addition & 0 deletions setup.cfg
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Expand Up @@ -33,6 +33,7 @@ install_requires =
networkx>=3.4.2
pydantic>=2.12.5
ray[tune]>=2.46.0
tqdm>=4.66.0

[options.packages.find]
where = .
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