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Understanding expression across comparisons and datasets through interactive visualization

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OmicLoupe

Understanding expression across comparisons and datasets

OmicLoupe illustration

Example data

Example data matrices and the corresponding design matrix is present in the folder data/example_data. Upload one or both of the matrices dia_umpire_data.tsv and openswath_data.tsv together with the design.tsv as design matrix. If using both, the options Two datasets and Matched samples should be checked.

Installation

It can be installed either directly from GitHub or by downloading as a Zip. To install it directly from GitHub, open R and run the following command (requires the R package devtools to be installed):

devtools::install_github("ComputationalProteomics/OmicLoupe")

Running it locally

After installation, you can immediately run the program. You can subsequently navigate to the browser to access the software.

OmicLoupe::runApp()

Dependencies

The R packages used by OmicLoupe may have certain system dependences. If working on a Debian-based Linux distribution, these can be installed from the command line:

sudo apt install libcurl4-openssl-dev libxml2-dev libssl-dev libgit2-dev pandoc libfontconfig1-dev

Running it as a Docker container

Docker is a container software which allows execution without needing to prepare local dependencies. It can be downloaded from https://www.docker.com.

Using Docker can be a rapid way to get OmicLoupe running locally without needing to install all dependencies. First, retrieve the container:

docker pull computationalproteomics/omicloupe:latest

This will download the Docker container containing OmicLoupe. Now you are ready to run OmicLoupe:

docker run --rm -p 3838:3838 computationalproteomics/omicloupe

Simply open the provided link (usually localhost:3838) in a browser, and you should have access to OmicLoupe.

Running on a server

If you have a server running Shiny Server you can easily get OmicLoupe running by:

  1. Install OmicLoupe (making sure it get installed at a path which Shiny Server can access)
  2. Place a file called app.R within a folder in the shiny-server directory containing a single line calling OmicLoupe: OmicLoupe::runApp()

Misc

You could make a convenient Bash alias for this, which lets you execute OmicLoupe by simply typing "omicloupe" into a Bash terminal. Add this line to your .bash_aliases or .bashrc file.

alias omicloupe="Rscript -e \"runApp()\""