DeepTAN
A novel graph-based multi-task framework designed to infer large-scale multi-omics trait-associated networks (TANs) and reconstruct phenotype-specific omics states
Quick start
conda create -n deeptan python=3.12 -y
conda activate deeptan
pip install torch==2.7.0 torchvision==0.22.0 torchaudio==2.7.0 --index-url https://download.pytorch.org/whl/cu128
pip install torch_geometric
pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.7.0+cu128.html
pip install deeptan
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Metadata
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Release files for deeptan 0.1.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| deeptan-0.1.5.tar.gz | 110.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| deeptan-0.1.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 192.6 kB
Release files / deeptan-0.1.5.tar.gz
| Download URL | deeptan-0.1.5.tar.gz |
|---|---|
| Size | 110.9 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / deeptan-0.1.5-py3-none-any.whl
| Download URL | deeptan-0.1.5-py3-none-any.whl |
|---|---|
| Size | 81.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
uv/0.7.11
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