Hierarchical Manifold Approximation and Projection for Single Cell Data
Project description
HMAP: Hierarchical Manifold Approximation and Projection
HMAP develop a hierarchical deep generative topographic mapping algorithm to realize the recovery of both global and local manifolds underlying the given data.
Example
Metacell calling
HMAP also provides the supervised mode, allowing the computation of global and local embeddings under the supervision of given metacells.
Installation
- Download HMAP and enter the directory
git clone https://github.com/ZengFLab/HMAP.git && cd HMAP
- Create a virtual environment and activate it
conda create -n HMAP python=3.10 && conda activate HMAP
- Install PyTorch following the official instruction.
pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu126
- Install HMAP
pip install HMAP-tool
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file hmap_tool-1.0.tar.gz.
File metadata
- Download URL: hmap_tool-1.0.tar.gz
- Upload date:
- Size: 21.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.10.18
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ffd87e56e8c6c35bf1230b8c4a9adda20881a1c2ee6e781e3eb4f61dc008bccb
|
|
| MD5 |
1c8c0a18ad1809058c3cb90d8781d127
|
|
| BLAKE2b-256 |
2390f18e600f8d931e6632f0a67c58df6dc659fb54d32275bc69cb4fc777d1ff
|
File details
Details for the file hmap_tool-1.0-py3-none-any.whl.
File metadata
- Download URL: hmap_tool-1.0-py3-none-any.whl
- Upload date:
- Size: 22.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.10.18
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
28d9838e33624cd3d7c9a41213a0599405ca8cffe508b7bd1b7482c2de52893e
|
|
| MD5 |
28727fba643a93e3512577f23619e1cf
|
|
| BLAKE2b-256 |
6912f9e65676ce86c6772a0b38e8cd95bdde2fab04b9b1596583ed560cf37a59
|
