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ismb-biovis-2022

Code related to our BioVis talk at ISMB '22

https://github.com/flekschas-ozette/ismb-biovis-2022

Science Score: 54.0%

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    CITATION.cff file
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    Found .zenodo.json file
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    Links to: sciencedirect.com, nature.com, zenodo.org
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    Low similarity (12.1%) to scientific vocabulary
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Repository

Code related to our BioVis talk at ISMB '22

Basic Info
  • Host: GitHub
  • Owner: flekschas-ozette
  • License: apache-2.0
  • Language: Jupyter Notebook
  • Default Branch: main
  • Homepage:
  • Size: 10.9 MB
Statistics
  • Stars: 3
  • Watchers: 2
  • Forks: 1
  • Open Issues: 0
  • Releases: 1
Created about 4 years ago · Last pushed over 3 years ago
Metadata Files
Readme License Citation

README.md

ISMB BioVis '22 Talk on Data Transformations for Effective Visualization of Single-Cell Embeddings

DOI Talk Recording

This repository contains the code to reproduce plots presented in our BioVis talk+poster at ISMB '22. The talk itself is available on YouTube.

ISMB BioVis 2022 Slides
ISMB BioVis 2022 Poster

For a much more elaborate R implementation that includes our FAUST clustering method, please take a look at https://github.com/RGLab/FAUST.

For details about our clustering and visualization methods, please take a look at the related publication:

Greene et al., 2021, New interpretable machine-learning method for single-cell data reveals correlates of clinical response to cancer immunotherapy. Pattern.

Requirements

Install

git clone git@github.com:flekschas-ozette/ismb-biovis-2022.git cd ismb-biovis-2022 conda env create -f environment.yml conda activate ozette-ismb-biovis-2022

Example Data

Download the example data from https://figshare.com/articles/dataset/ISMBBioVis2022_Data/20301639 and place the files under data/mair-2022. The data is from Mair et al., 2022, Extricating human tumour immune alterations from tissue inflammation, Nature.

Get Started

  1. Start JupyterLab:

jupyter-lab

  1. Open one of the following notebooks:

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software or build upon the presented ideas, please cite it as below."
authors:
- family-names: "Greene"
  given-names: "Evan"
- family-names: "Finak"
  given-names: "Greg"
  orcid: "https://orcid.org/0000-0003-4341-9090"
- family-names: "Lekschas"
  given-names: "Fritz"
  orcid: "https://orcid.org/0000-0001-8432-4835"
- family-names: "Smith"
  given-names: "Malisa"
- family-names: "D'Amico"
  given-names: "Leonard A"
- family-names: "Bhardwaj"
  given-names: "Nina"
- family-names: "Church"
  given-names: "Candice D"
- family-names: "Morishima"
  given-names: "Chihiro"
- family-names: "Ramchurren"
  given-names: "Nirasha"
- family-names: "Taube"
  given-names: "Janis M"
- family-names: "Nghiem"
  given-names: "Paul T"
- family-names: "Cheever"
  given-names: "Martin A"
- family-names: "Fling"
  given-names: "Steven P"
- family-names: "Gottardo"
  given-names: "Raphael"
  orcid: "https://orcid.org/0000-0002-3867-0232"
title: "Data Transformations for Effective Visualization of Single-Cell Embeddings"
version: 1.0.0
doi: 10.5281/zenodo.7522322
date-released: 2022-07-13
url: "https://github.com/flekschas-ozette/ismb-biovis-2022"
license: Apache-2.0

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Dependencies

environment.yml conda
  • matplotlib
  • pandas
  • pip
  • pynndescent
  • python 3.9.*
  • requests
  • scikit-learn
  • scipy
  • tensorflow
  • umap-learn