Single Cell RNA Sequencing Marker Selection Package
Project description
PicturedRocks Single Cell Analysis Tool
PicturedRocks is a python package that implements some single cell analysis algorithms that we are studying. Currently, we implement two marker selection algorithms:
- 1-bit Compressed Sensing algorithms based on [Conrad, et al. BMC bioinformatics '17]
- variants of mutual information based algorithms (e.g., the "minimum Redundance Maximum Relevance" algorithm [Peng, et al. IEEE TPAMI '05])
Usage
To install, put the picturedrocks
directory in your python path (e.g., in the current working directory).
PicturedRocks in compatible with scanpy
and uses its AnnData
objects. Most methods require cluster labels to be loaded.
from picturedrocks.read import read_clusts, process_clusts
adata = read_clusts(adata, "clust_labels.csv")
adata = process_clusts(adata)
More detailed information can be found on the online documentation.
Code Style
Pull requests are welcome. Please use numpy-style docstrings and format your code with black.
Copyright
Copyright © 2017, 2018 Anna Gilbert, Alexander Vargo, Umang Varma
PicturedRocks is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
PicturedRocks is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with PicturedRocks. If not, see http://www.gnu.org/licenses/.
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
File details
Details for the file picturedrocks-0.2.0a2.tar.gz
.
File metadata
- Download URL: picturedrocks-0.2.0a2.tar.gz
- Upload date:
- Size: 29.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/40.0.0 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.6.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | bc3166e77f45e1663aab29e730a9b034cda773a30446db1ed44b46366cc80bb6 |
|
MD5 | cac68dee7dc4e51cbd1454a1d283ce5e |
|
BLAKE2b-256 | 78a4aaafb3a938ac34f05e558cea86724aca690b78fac521f944c945e764dd66 |
File details
Details for the file picturedrocks-0.2.0a2-py3-none-any.whl
.
File metadata
- Download URL: picturedrocks-0.2.0a2-py3-none-any.whl
- Upload date:
- Size: 23.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/40.0.0 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.6.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2c98657d3dc3821f62531f939be165996530b48948a3cbe269eb42234ec561b5 |
|
MD5 | 615556223d64735591ac514fa2e590ad |
|
BLAKE2b-256 | 210eec10b22acce50ea992af2b795eca4197396ca2eef29371bc2bdf308b2ea8 |