iSEEu

The iSEEu package contains material and code that extends the iSEE package (https://github.com/iSEE/iSEE).

We welcome contributions from the community, see below for more instructions. For example, during the Developer Day at the European Bioconductor 2019 conference (#EuroBioc2019, at the UCLouvain, in Brussels, Belgium), we proposed a hackathon-like session, and we focused on the design of "modes", i.e. preconfigured sets of panels and linked content to be used as starting setup when launching iSEE.

Installation

iSEEu can be easily installed from Bioconductor using BiocManager::install():

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("iSEEu")

Optionally, if you want to install the development version from GitHub, you can use:

BiocManager::install("iSEE/iSEEu", dependencies = TRUE)
# or alternatively...
remotes::install_github("iSEE/iSEEu", dependencies = TRUE)

Setting dependencies = TRUE should ensure that all packages, including the ones in the Suggests: field of the DESCRIPTION, are installed - this can be essential if you want to reproduce the code in the vignette, for example.

Expanding the iSEE universe with iSEEu

• install iSEE first - the development version is recommended.

BiocManager::install("iSEE", version = "devel")
# or
remotes::install_github("iSEE/iSEE")

• fork the iSEEu repo (https://github.com/iSEE/iSEEu) and clone it locally.

git clone https://github.com/[your_github_username]/iSEEu.git

• make the desired changes in the files - start from the R folder, then document via roxygen2 - and push to your fork.

• once your contribution (function, panel, mode) is done, consider adding some information in the package. Some examples might be a screenshot of the mode in action (to be placed in the folder inst/modes_img), or a well-documented example use case (maybe an entry in the vignettes folder). Also add yourself as a contributor (ctb) to the DESCRIPTION file.

• make a pull request to the original repo - the GitHub site offers a practical framework to do so, enabling comments, code reviews, and other goodies.

• more on documenting and code guidelines:

  • if possible, please consider adding an example in the dedicated Roxygen preamble to show how to run each function
  • if possible, consider adding one or more unit tests - we use the testthat framework

Some more info

Where do I look for constants within iSEE?

Many of the "global" variables that are used in several places in iSEE are defined in the constants.R script in iSEE. We suggest to use these constants rather than hardcoding (e.g.) column names in the panel specification data frames, to protect against potential future changes of the precise column names. To access a constant, use iSEE:::.constantName.

Is there any example I can check out to understand how things are supposed to work?

There are several modes already defined in the R/ directory.

Are there any style guides I am supposed to follow?

Yes. Mainly guided by common sense of "never changing a working system", please stick to the conventions we have been adopting for developing the existing codebase. A few simple style options:

• keep the indentation as it is in the initial functions already available.
• if writing text (e.g. vignette), please use one sentence per line - this makes git diff operations easier to check.
• in code, use a degree of balance.
• for names, try to keep some consistency with what already is existing. We use camelCase for modes and some other functions, and prepend most unexported elements with a dot.

What if I need a custom panel type?

In addition to the eight standard panel types, custom panels are easily accommodated within iSEE applications. For a guide, see the corresponding vignette. For examples, see this repo.

Are there other examples on how to use iSEE for exploring other datasets/data types?

Yes, you can have a look at the examples in https://github.com/iSEE/iSEE_instances, where we tried to put together fully worked vignettes to re-analyze publicly available datasets, e.g. also trying to replicate some key visualizations of the original publications.

Where can I find a comprehensive introduction to iSEE?

The iSEE package contains several vignettes detailing the main functionality. You can also take a look at this workshop. A compiled version from the Bioc2019 conference (based on Bioconductor release 3.10) is available here.

Code of Conduct

Please note that the iSEEu project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.