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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. 1-bit Compressed Sensing algorithms based on [Conrad, et al. BMC bioinformatics '17]
  2. variants of mutual information based algorithms (e.g., the "minimum Redundance Maximum Relevance" algorithm [Peng, et al. IEEE TPAMI '05])

Usage

To install the latest GitHub version of PicturedRocks, do an "editable" installation of PicturedRocks:

git clone git@github.com: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.

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


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