Single Cell RNA Sequencing Marker Selection Package
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])
To install the latest GitHub version of PicturedRocks, do an "editable" installation of PicturedRocks:
git clone firstname.lastname@example.org:umangv/picturedrocks.git cd picturedrocks pip install -e .
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.
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/.
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|Filename, size & hash SHA256 hash help||File type||Python version||Upload date|
|picturedrocks-0.2.1-py3-none-any.whl (27.7 kB) Copy SHA256 hash SHA256||Wheel||py3|
|picturedrocks-0.2.1.tar.gz (30.2 kB) Copy SHA256 hash SHA256||Source||None|