A library to calculate the latent time of scRNA-seq
Project description
scLTNN (single cell latent time neuron network)
A composite regression neural network for latent timing prediction of single-cell RNA-seq data
For more details, please check out our publication.
Directory structure
.
├── scltnn # Main Python package
├── experiments # Experiments and case studies
├── scltnn # the raw code of scltnn
├── model # the pre-model by ANN
├── source # Documentation files
├── LICENSE
└── README.md
Installation
The scLTNN package can be installed via pip:
pip install scltnn
Usage
Please checkout the documentations and tutorials at scltnn.readthedocs.io.
Reproduce results
- Follow instructions in
datato prepare the necessary data, it can be download at https://figshare.com/articles/dataset/scltnn_data/20383416 - Follow instructions in
experimentsfor case studies
Contact
- Zehua Zeng (starlitnightly@163.com)
Project details
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 scltnn-0.1.0.tar.gz.
File metadata
- Download URL: scltnn-0.1.0.tar.gz
- Upload date:
- Size: 57.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.8.13
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d7b5db63c21f744398b2634b7e598066ac804b4ed16e3340fa7ca5bf683dc24a
|
|
| MD5 |
03f0ee64f28b2c7eea32ec39ed75476c
|
|
| BLAKE2b-256 |
d90ca2839e4a5bbbe3b9fd80d184abb3129ef87a831b323fadce315e5e44356b
|
File details
Details for the file scltnn-0.1.0-py3-none-any.whl.
File metadata
- Download URL: scltnn-0.1.0-py3-none-any.whl
- Upload date:
- Size: 58.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.8.13
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8d1303b1cd7a95d1bc09822e3a0c99af871b34a35adc1607c7e33958f4a7cab6
|
|
| MD5 |
1fe76dadd4506a53c3d80df79146fce1
|
|
| BLAKE2b-256 |
65999efa2ac6246657accc8482df9047718358df4e52f69d877021d767d26227
|