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README.md

CodeFactor

SCope v1.8.1: Visualization of large-scale and high dimensional single cell data

SCope is a fast visualization tool for large-scale and high dimensional scRNA-seq datasets. Currently the data format supported by SCope is .loom. This file format for very large omics datasets is maintained by the Linnarsson Lab through the loompy Python package (https://github.com/linnarsson-lab/loompy).

View the change log here.

Demo

Visit http://scope.aertslab.org to test out SCope on several published datasets! Personal loom file files can be uploaded but will only be kept for 5 days.

Loom File Generation

Currently there are two packages to generate extended loom files compatible with SCope.

  • R: SCopeLoomR - Dedicated R package
  • Python: pySCENIC - Single function for generation from SCENIC results

Eventually the functionality from pySCENIC will be expanded and put in its own python package.

Run SCope

Standalone App

Standalone apps for macOS and Linux can be downloaded from the releases page..

SCope standalone app requires Node.js (> v9). To install it, go to https://nodejs.org/en/download/.

A Windows app is under development, but currently has no ETA.

Command Line

You will need access to at least Python 3.7 do run this.

  1. Clone the GitHub repository and install,
# Define where you want to clone the SCope repository.
LOCAL_SCOPE_REPO="${HOME}/repos/SCope"
# Clone SCope git repository.
git clone https://github.com/aertslab/SCope "${LOCAL_SCOPE_REPO}"
# Go to your local cloned SCope repository.
cd "${LOCAL_SCOPE_REPO}"
# Install SCope.
npm install
  1. Run,
# Go to your local cloned SCope repository.
cd "${LOCAL_SCOPE_REPO}"
SCOPE_CONFIG=config.json npm run scope

Deploy a Cloud-based Instance

Amazon Web Services

Public AMI

No ETA.

Source

To create a SCope AWS instance from scratch please read the tutorial aws-deployment-source.

Features

Enabling ORCID Functionality

To enable colaborative annotations and login via ORCID ID, API credentials (orcidAPIClientID, orcidAPIClientSecret and orcidAPIRedirectURI) must be added to the config file provided. These can be generated at the orcid developer tools page.

The dataHashSecret entry in the config file should be filled in with a randomly generated string for example from the python secrets package. This string will be used to salt all annotation data, allowing validation of data generated on the instance of SCope. Any changes in this string will invalidate all pre-existing annotations.

Development

  1. Clone the GitHub repository and install,
# Define where you want to clone the SCope repository.
LOCAL_SCOPE_REPO="${HOME}/repos/SCope"
# Clone SCope git repository.
git clone https://github.com/aertslab/SCope "${LOCAL_SCOPE_REPO}"
# Go to your local cloned SCope repository.
cd "${LOCAL_SCOPE_REPO}"
# Install SCope.
npm install
  1. Run,
# Go to your local cloned SCope repository.
cd "${LOCAL_SCOPE_REPO}"

# Start SCope Server (terminal 1).
cd opt
poetry run hypercorn main:scope_api --reload

# Start SCope Client (terminal 2).
cd ..
npm run dev

Configuration file (config.json)

Keys:

  • data: This is a directory containing data files (e.g. the motd.txt message of the day). Can be an absolute path or a relative path from where you start SCope. By default it is ./data/.
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