MarcoPolo: a method to discover differentially expressed genes in single-cell RNA-seq data without depending on prior clustering
Project description
MarcoPolo: a method to discover differentially expressed genes in single-cell RNA-seq data without depending on prior clustering.
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
File details
Details for the file marcopolo-pytorch-1.1.1.tar.gz.
File metadata
- Download URL: marcopolo-pytorch-1.1.1.tar.gz
- Upload date:
- Size: 1.4 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.8.11
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 05727922915972fec8443e9373ea885f58ea5a2e8194b74ab7094025da4caa49 |
|
| MD5 | 75891a954420f319fa72d669175ee845 |
|
| BLAKE2b-256 | 1ab6a6c4a1e415c465293c2d26b17417be0a73e28d6faa1f9c5ab6d12358c837 |
File details
Details for the file marcopolo_pytorch-1.1.1-py3-none-any.whl.
File metadata
- Download URL: marcopolo_pytorch-1.1.1-py3-none-any.whl
- Upload date:
- Size: 614.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.8.11
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 781bd85bb307800d65660edbc0dd70ba6c556b7dc507e92e896843384757b1df |
|
| MD5 | b5a7d8f0b504e6aa38172d614dd10358 |
|
| BLAKE2b-256 | 5ad216f3e6bfb630325fc765fefe538636cfa89d4ee13ae4cec9f85eb2d6a7eb |
