ShinySyn

ShinySyn is a shiny application to help user investigate synteny blocks identified by mcscan, which is a part of jcvi (https://github.com/tanghaibao/jcvi) library developed by @tanghaibao, and provide a intuitive connection between macrosynteny and microsynteny (genes).

If you use ShinySyn, please cite:

Zhixia Xiao, Hon-Ming Lam, ShinySyn: a Shiny/R application for the interactive visualization and integration of macro- and micro-synteny data, Bioinformatics, 2022;, btac503, https://doi.org/10.1093/bioinformatics/btac503

If you use the mcscan pipeline in ShinySyn, please also remember to cite its orignal paper:

Tang, H., Bowers, J. E., Wang, X., Ming, R., Alam, M., & Paterson, A. H. (2008). Synteny and collinearity in plant genomes. Science, 320(5875), 486-488.

and the paper of last:

Kiełbasa, S. M., Wan, R., Sato, K., Horton, P., & Frith, M. C. (2011). Adaptive seeds tame genomic sequence comparison. Genome research, 21(3), 487-493.

Features

• Interactive visualization for both macro- and microsynteny

• Intuitive connection between macrosynteny and microsynteny

• Integration of mcscan pipeline

Main Page View

Usage Demo

• Select macrosynteny block of interest and investigate gene pairs within

• Select dots (gene pairs) from dot plot and get detail gene list

Installation

Dependencies

• jcvi/mcscan (https://github.com/tanghaibao/jcvi/wiki/MCscan-%28Python-version%29)

• LASTAL (https://gitlab.com/mcfrith/last)

• R packages

  • {shiny}
  • {bslib}
  • {shinyjs}
  • {shinyWidgets}
  • {DT}
  • {shinyalert}
  • {colourpicker}
  • {waiter}
  • {tidyverse}
  • {vroom}

We recommand to install the dependencies via conda or directly use the docker image if docker was installed. Please follow their official document for installation:

• miniconda: https://docs.conda.io/en/latest/miniconda.html

• docker: https://docs.docker.com/get-docker/

Conda env was tested on both linux and OSX. Windows user could use docker desktop to run ShinySyn as linux container. Please follow this instruction to install it firstly.

Install packages from conda

• create conda env

Since conda is bit slow, use mamba instead

conda install mamba -n base -c conda-forge

## clone app repo
git clone https://github.com/obenno/ShinySyn.git
## cd app directory
cd ShinySyn
## create conda env with yml file
mamba env create -f shinysyn_env.yml

• activate env and run application

conda activate shinysyn
Rscript -e "options(shiny.port = 3838, shiny.host = '0.0.0.0', sass.cache = FALSE); shiny::runApp()"

The application will be run locally at http://127.0.0.1:3838, user could open the address with google chrome or other modern browsers.

Use docker image

We have prepared docker images for ShinySyn. With docker installed, user could simplely invoke the app with command below, and will be able to invoke the application directly from "Containers/ Apps" menu when opening Docker Desktop next time.

docker run -p 3838:3838 obenno/shinysyn

To remove container after usage, use command:

docker run --rm -p 3838:3838 obenno/shinysyn

The application will be run locally at http://127.0.0.1:3838, user could open the address with browsers.

To only pull the pre-built image from dockerhub, use:

docker pull obenno/shinysyn

Users in the mainland of China could use the image below:

docker run -p 3838:3838 registry-intl.cn-hangzhou.aliyuncs.com/obenno/shinysyn

Note:

• Windows users needs to install docker desktop, and type the same command above in any terminal app, e.g. PowerShell.

• The image is a bit large, please reserve 5 GB space for it.