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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, 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/.

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