A method to demultiplex hashtagged single-cell data by first applying a denoising and normalizing step adapted from DSB (Denoised and Scaled by Background).
Project description
hto_dnd
Package for demultiplexing single-cell data after normalizing the data using an adaptation of the DSB algorithm
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
hto_dnd-0.1.0.tar.gz
(12.4 kB
view details)
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 hto_dnd-0.1.0.tar.gz.
File metadata
- Download URL: hto_dnd-0.1.0.tar.gz
- Upload date:
- Size: 12.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ec7232888065dad995bbb173899e4f12e4319da1ba8569bf020a2e37e9ebea33
|
|
| MD5 |
f99f7e5dbedfdfcb620e644d999b516f
|
|
| BLAKE2b-256 |
b9633cfe41b4976668c4ff9e00172b7c019510b4fec05915d5a847b1f99f9eb3
|
File details
Details for the file hto_dnd-0.1.0-py3-none-any.whl.
File metadata
- Download URL: hto_dnd-0.1.0-py3-none-any.whl
- Upload date:
- Size: 8.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
1098185aba2cf67112aeaf3bc95605835a05484f08583b234f3656669fc3d22b
|
|
| MD5 |
dd8ab62cae2d94a4c02d804871d727bf
|
|
| BLAKE2b-256 |
cc5b51fcc94ea96d16e298fdcb27a88b74d26476a9319a32356b60e1a6d365aa
|