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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:

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: