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<!-- README.md is generated from README.Rmd. Please edit that file -->dynverse <img src="docs/logo.png" align="right" width="140" height="160" />
dynverse is a collection of R packages aimed at supporting the trajectory inference (TI) community on multiple levels: end-users who want to apply TI on their dataset of interest, and developers who seek to easily quantify the performance of their TI method and compare it to other TI methods.
All of these packages were developed as part of a benchmarking study available on bioRxiv. All source code has been made available in the dynbenchmark repository.
A comparison of single-cell trajectory inference methods: towards more accurate and robust tools
<strong> Wouter Saelens* </strong> <a href='https://orcid.org/0000-0002-7114-6248'><img src='https://github.com/dynverse/dynmethods/raw/master/man/figures/orcid_logo.svg?sanitize=true' height='16'></a> <a href='https://github.com/zouter'><img src='https://github.com/dynverse/dynmethods/raw/master/man/figures/github_logo.png' height='16'></a>, <strong> Robrecht Cannoodt* </strong> <a href='https://orcid.org/0000-0003-3641-729X'><img src='https://github.com/dynverse/dynmethods/raw/master/man/figures/orcid_logo.svg?sanitize=true' height='16'></a> <a href='https://github.com/rcannood'><img src='https://github.com/dynverse/dynmethods/raw/master/man/figures/github_logo.png' height='16'></a>, Helena Todorov <a href='https://github.com/Helena-todd'><img src='https://github.com/dynverse/dynmethods/raw/master/man/figures/github_logo.png' height='16'></a>, <em> Yvan Saeys </em> <a href='https://github.com/saeyslab'><img src='https://github.com/dynverse/dynmethods/raw/master/man/figures/github_logo.png' height='16'></a>
bioRxiv:276907 doi:10.1101/276907
*: Equal contribution
End-users
The dyno package offers end-users a complete TI pipeline. It features:
- a uniform interface to 59 TI methods,
- an interactive guideline tool to help the user select the most appropriate method,
- the interpretation and visualisation of trajectories, including colouring by gene expression or clusters, and
- downstream analyses such as the identification of potential marker genes.
Developers
For developers of existing or new TI methods, dyno offers the same features as to end-users. In addition, developers might also want to check out the following packages:
- dynmethods, which is a repository of wrappers for TI methods. If your method has already been included in dynmethods, an issue will have been created there.
- dynwrap, the wrapping functions for transforming common trajectory data formats into the common trajectory model supported by dynverse.
- dynbenchmark, all source code in order to replicate the benchmarking study by Saelens and Cannoodt (10.1101/276907).
- Check out this overview of all dynverse packages for more information of the functionality of each package.