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radish

https://github.com/genom-ic-cochin/radish

Science Score: 49.0%

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    CITATION.cff file
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    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
    Found .zenodo.json file
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    DOI references
    Found 2 DOI reference(s) in README
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    Academic publication links
    Links to: ncbi.nlm.nih.gov
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    Academic email domains
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    Institutional organization owner
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    Scientific vocabulary similarity
    Low similarity (10.5%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: GENOM-IC-Cochin
  • License: mit
  • Language: R
  • Default Branch: master
  • Size: 168 MB
Statistics
  • Stars: 4
  • Watchers: 1
  • Forks: 3
  • Open Issues: 0
  • Releases: 4
Created over 4 years ago · Last pushed over 2 years ago
Metadata Files
Readme License Citation

README.md

Table of Contents

Introduction

Radish is a shiny application for the visualisation and analysis of pre-processed RNA-seq data, specifically differential expression analysis. Given data processed with GENOM'IC's pipeline, it is able to produce customisable plots, such as PCA plots, Volcano plots and Heatmaps. It also allows one to explore the counts and results table interactively.

Radish is an exploration tool, it relies on data already processed from raw reads, following a STAR -> RSEM -> DESeq2 pipeline, with gene name annotation with Biomart.

Usage

Installation

Installation is only available through docker for now.

  • First, install Docker : https://docs.docker.com/get-docker/

  • Then run (on Windows, use the command prompt):

    docker pull bsgenomique/radish
docker run -dp 80:3838 --rm bsgenomique/radish

  • Access the app through your usual web navigator (Chromium-based, there is an issue with Firefox and the tutorial videos), at the adress http://localhost/.

  • Load your result.rds file in the Data tab

  • Explore!

  • Don't forget to stop the container afterwards!

Using the app

Follow the instructions in the app. Load the results.rds file provided by GENOM'IC in the Data tab, and then proceed to explore the dataset and produce your figures!

Demo data

To experiment with the app, you can use demo data kindly provided by Juliette Paillet (Kroemer team, UMRS1138), from this article by Paillet et al. (raw data otherwise available from Gene Expression Omnibus, under accession no. GSE180289). It is accessible by a simple button press!

Contact

If you have any comment, suggestion or question, feel free to post an issue.

Acknowledgement

Main contributors to this project are Paul Etheimer (Developpement, documentation, testing) under the supervision of Juliette Hamroune (Initiator, evaluation, feature suggestions).

Owner

  • Name: GENOM-IC-Cochin
  • Login: GENOM-IC-Cochin
  • Kind: organization

GitHub Events

Total
  • Watch event: 2
Last Year
  • Watch event: 2

Dependencies

DESCRIPTION cran
  • BiocGenerics * imports
  • ComplexHeatmap * imports
  • ComplexUpset * imports
  • DESeq2 * imports
  • DT * imports
  • RColorBrewer * imports
  • SummarizedExperiment * imports
  • bs4Dash * imports
  • colourpicker * imports
  • datasets * imports
  • dplyr * imports
  • fresh * imports
  • ggplot2 * imports
  • ggrepel * imports
  • magrittr * imports
  • markdown * imports
  • matrixStats * imports
  • pkgload * imports
  • plotly * imports
  • purrr * imports
  • ragg * imports
  • rprojroot * imports
  • scales * imports
  • shiny * imports
  • shinyWidgets * imports
  • shinyvalidate * imports
  • stringr * imports
  • svglite * imports
  • tibble * imports
  • tidyr * imports
  • waiter * imports
  • shinytest2 * suggests
Dockerfile docker
  • rocker/r-ver 4.2.3 build