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https://github.com/beliveau-lab/paintshop_pipeline

A scalable machine learning pipeline for probe specificity prediction.

https://github.com/beliveau-lab/paintshop_pipeline

Science Score: 23.0%

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    CITATION.cff file
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    codemeta.json file
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    .zenodo.json file
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    DOI references
    Found 3 DOI reference(s) in README
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    Links to: biorxiv.org
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    Scientific vocabulary similarity
    Low similarity (17.2%) to scientific vocabulary
Last synced: 9 months ago · JSON representation

Repository

A scalable machine learning pipeline for probe specificity prediction.

Basic Info
  • Host: GitHub
  • Owner: beliveau-lab
  • License: mit
  • Language: HTML
  • Default Branch: master
  • Size: 12.1 MB
Statistics
  • Stars: 12
  • Watchers: 4
  • Forks: 6
  • Open Issues: 3
  • Releases: 4
Created over 6 years ago · Last pushed over 2 years ago
Metadata Files
Readme License

README.md

PaintSHOP Pipeline

Snakemake DOI

Overview

PaintSHOP is a technology that enables the interactive design of oligonucleotide FISH experiments at genome and transcriptome-scale and is comprised of two components:

  1. A scalable machine learning pipeline for probe specifity prediction

  2. An interactive Shiny web application for probe design

This repository contains the Snakemake workflow for the machine learning pipeline and the full software stack needed to design probes for additional genomes not already hosted on the web application.

Installation

  1. Make sure you have conda installed.

  2. Install Mamba to facilitate snakemake installation, as recommended in the Snakemake docs.

$ conda install -n base -c conda-forge mamba

  1. Clone this repo, then create and activate the provided environment:

$ git clone https://github.com/beliveau-lab/PaintSHOP_pipeline.git \ && cd PaintSHOP_pipeline/ \ && mamba env create -f environment.yml \ && conda activate paintshop_snakemake

Running the pipeline

A complete example is included to test the pipeline installation. To run the pipeline on the included sample files:

$ cd example_run/ && ./run_pipeline.sh

When this example is run, pipeline output will be generated here. Expected outputs are provided here for comparison.

To run the pipeline on your own data, update the file paths in config.yml with the paths to your genome assembly files. For more information on input and output files, see the documentation.

This pipeline is implemented using Snakemake, and distributed according to best practices. If you are new to Snakemake, the tutorial is a great place to get started to learn more.

PaintSHOP Pipeline

Documentation

Additional information is available in the docs:

Questions

If you have questions or issues, please open an issue on GitHub.

Citation

For usage of the pipeline and/or web application, please cite according to the enclosed citation.bib.

License

We provide this open source software without any warranty under the MIT license.

Owner

  • Name: Beliveau Lab
  • Login: beliveau-lab
  • Kind: organization

The Beliveau Lab at UW Genome Sciences

GitHub Events

Total
  • Issues event: 1
  • Watch event: 3
  • Issue comment event: 3
  • Fork event: 2
Last Year
  • Issues event: 1
  • Watch event: 3
  • Issue comment event: 3
  • Fork event: 2

Dependencies

environment.yml pypi
workflow/envs/environment.yml pypi