https://github.com/dynverse/dynverse

A set of tools supporting the development, execution, and benchmarking of trajectory inference methods. 🌍
https://github.com/dynverse/dynverse

benchmarking scrna-seq single-cell single-cell-omics single-cell-rna-seq trajectory-inference-methods

Last synced: 24 days ago
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A set of tools supporting the development, execution, and benchmarking of trajectory inference methods. 🌍

• Host: GitHub
• URL: https://github.com/dynverse/dynverse
• Owner: dynverse
• License: other
• Created: 2017-10-02T07:05:26.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2021-05-20T06:41:50.000Z (about 3 years ago)
• Last Synced: 2024-05-21T23:05:56.201Z (about 1 month ago)
• Topics: benchmarking, scrna-seq, single-cell, single-cell-omics, single-cell-rna-seq, trajectory-inference-methods
• Language: R
• Homepage: http://dynverse.org
• Size: 566 KB
• Stars: 71
• Watchers: 8
• Forks: 17
• Open Issues: 2
• Metadata Files:
  • Readme: README.Rmd
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

Lists

• awesome_single_cell - dynverse - [R] - [A comparison of single-cell trajectory inference methods: towards more accurate and robust tools](https://doi.org/10.1101/276907) (Software packages / RNA-seq)

README

        
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output: github_document

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# dynverse 

**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](https://doi.org/10.1101/276907). All source code has been made available in the [dynbenchmark](https://github.com/dynverse/dynbenchmark) repository.

> A comparison of single-cell trajectory inference methods: towards more accurate and robust tools  

 Wouter Saelens\*   ,

 Robrecht Cannoodt\*   ,

Helena Todorov ,

 Yvan Saeys    

[bioRxiv:276907](https://www.biorxiv.org/content/early/2018/03/05/276907) [doi:10.1101/276907](https://doi.org/10.1101/276907) 

\*: Equal contribution

## End-users

The **[dyno](https://github.com/dynverse/dyno)** package offers **end-users** a complete TI pipeline. It features:

* a uniform interface to `r nrow(dynmethods::methods)` [TI methods](https://github.com/dynverse/dynmethods#list-of-included-methods),

* an [interactive guideline tool](https://github.com/dynverse/dyno#selecting-the-most-optimal-ti-methods) to help the user select the most appropriate method, 

* the [interpretation and visualisation of trajectories](https://github.com/dynverse/dyno#plotting-the-trajectory), including colouring by gene expression or clusters, and

* downstream analyses such as the [identification of potential marker genes](https://github.com/dynverse/dyno#plotting-relevant-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:

* **[dynmethods](https://github.com/dynverse/dynmethods)**, which is a repository of wrappers for TI methods. If your method has already been included in dynmethods, an [issue](https://github.com/dynverse/dynmethods/issues) will have been created there. 

* **[dynwrap](https://github.com/dynverse/dynwrap)**, the wrapping functions for transforming common trajectory data formats into the common trajectory model supported by dynverse.

* **[dynbenchmark](https://github.com/dynverse/dynbenchmark)**, all source code in order to replicate the benchmarking study by Saelens and Cannoodt ([10.1101/276907](https://doi.org/10.1101/276907)).

* Check out this [overview of all dynverse packages](overview.md) for more information of the functionality of each package.