https://github.com/berenslab/elephant-in-the-room

Companion repository to our Lause, Berens & Kobak (2024) paper "The art of seeing the elephant in the room: 2D embeddings of single-cell data do make sense" (PLOS Computational Biology)

https://github.com/berenslab/elephant-in-the-room

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Repository

Companion repository to our Lause, Berens & Kobak (2024) paper "The art of seeing the elephant in the room: 2D embeddings of single-cell data do make sense" (PLOS Computational Biology)

Basic Info
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Created over 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

The art of seeing the elephant in the room:
2D embeddings of single-cell data do make sense

Main figure

This repository holds the code to reproduce the analysis in our Lause, Berens & Kobak (2024) PLOS CB paper and contains the main and supplementary figures.

To reproduce our analysis, follow the steps below. We assume you have git and conda installed.

Install

  • Clone this repository. git clone git@github.com:berenslab/elephant-in-the-room.git

  • Inside the main folder of the repo, go to the src folder.

  • In src, clone our Picasso fork.

  • Go back to main folder. cd src git clone git@github.com:berenslab/picasso.git cd ..

  • Install the conda environment for Picasso. conda env create -f src/picasso/env/env3.7_LINUX.yml

  • From the main folder of the elephant-in-the-room repo, activate the picasso_env environment and install our Picasso fork with pip. conda activate picasso_env pip install -e .

  • Install our conda analysis environment. conda env create -f environment.yml

Run the analysis

  • Activate our conda analysis environment.
  • Start jupyter lab to run notebooks 1&2 in the scripts folder. This will download the data, run preprocesing and compute PCA, t-SNE and UMAP embeddings. conda activate elephant_analysis_env jupyter lab

  • After that, activate the Picasso anvironment and start jupyter notebook to run notebook 3. This will run Picasso and create the elephant embeddings. conda activate picasso_env jupyter notebook

  • After that, again activate our analysis environment.

  • Start jupyter lab to run the remaining notebooks 4&5. This will run the evaluations and prepare the plots. conda activate elephant_analysis_env jupyter lab

System information

We used conda 23.11.0 on a recent laptop with 16GB RAM running LINUX 6.5.0-18-generic #18~22.04.1-Ubuntu. See environment.yml for more information on the analysis environment, and env3.7_LINUX.yml for more information on the Picasso environment.

Copyright information

Notebook 1 and notebook 3 use code adapted from the github repository CP_2023 by Chari & Pachter, which is subject to the following licence:

``` BSD 2-Clause License

Copyright (c) 2021, Pachter Lab All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

  1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

  2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. ```

Owner

  • Name: Berens Lab @ University of Tübingen
  • Login: berenslab
  • Kind: organization
  • Email: philipp.berens@uni-tuebingen.de
  • Location: Tübingen, Germany

Department of Data Science at the Hertie Institute for AI in Brain Health, University of Tübingen

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Dependencies

setup.py pypi
environment.yml pypi