# dynwrap

**Repository Path**: baytars/dynwrap

## Basic Information

- **Project Name**: dynwrap
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2022-04-06
- **Last Updated**: 2024-08-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

dynwrap: Representing and Inferring Single-Cell Trajectories
================

<!-- README.md is generated from README.Rmd. Please edit that file -->

[![R-CMD-check](https://github.com/dynverse/dynwrap/workflows/R-CMD-check/badge.svg)](https://github.com/dynverse/dynwrap/actions?query=workflow%3AR-CMD-check)
[![codecov](https://codecov.io/gh/dynverse/dynwrap/branch/master/graph/badge.svg)](https://codecov.io/gh/dynverse/dynwrap)
[**ℹ️ Tutorials**](https://dynverse.org)     [**ℹ️ Reference
documentation**](https://dynverse.org/reference/dynwrap/) </br>
<img src="man/figures/logo.png" align="right" />

**dynwrap** contains the code for a common model of single-cell
trajectories. The package can:

-   Wrap the input data of a trajectory inference method, such as
    expression and prior information
-   Run a trajectory inference method in R, in a docker container or a
    singularity container
-   Wrap the output of a trajectory inference method, such as the
    pseudotime, a clustering or a branch network, and convert it into a
    common trajectory model
-   Further postprocess and adapt the trajectory model, such as
    labelling the milestones and rooting the trajectory

![](man/figures/trajectory_model.png)

Documentation and the API reference for dynwrap can be found at the
dyvnerse documentation website: <https://dynverse.org/> .

dynwrap was used to wrap 50+ trajectory inference method within docker
containers in [dynmethods](https://github.com/dynverse/dynmethods).

![](man/figures/overview_wrapping_v3.png)

The advantage of using a common model is that it allows:

-   Comparison between a prediction and a gold standard, eg. using
    [dyneval](https://github.com/dynverse/dyneval)
-   Comparing two predictions
-   Easily visualise the trajectory, eg. using
    [dynplot](https://github.com/dynverse/dynplot)
-   Extracting relevant features/genes, eg. using
    [dynfeature](https://github.com/dynverse/dynfeature)

## Latest changes

Check out `news(package = "dynwrap")` or [NEWS.md](NEWS.md) for a full
list of changes.

<!-- This section gets automatically generated from inst/NEWS.md -->

### Recent changes in dynwrap 1.2.2

-   MAJOR CHANGE `convert_milestone_percentages_to_progressions()`:
    Rewrite implementation to attain significant speedup.

-   MINOR CHANGE `infer_trajectory()`: Infer command (Rscript/python)
    from file extension if possible and avoid using shebang to execute
    script, because R CMD check for R 4.0 puts Rscript and R dummy
    executables on the path before R CMD check. This means
    `#!/usr/bin/env Rscript` does not work anymore.

-   MINOR CHANGE `add_feature_importance()`: Add a function for adding
    feature importance scores to a trajectory.

-   BUG FIX `project_waypoints()`: Rename milestone waypoints such that
    the names are unique.

-   BUG FIX `infer_trajectory()`: Fix error message printing.

-   BUG FIX: `dyndimred` is used conditionally.

-   BUG FIX: `wrap_expression()` and `add_expression()`: Do not override
    feature\_info when it already exists in dataset.

### Recent changes in dynwrap 1.2.1 (2020-05-11)

-   BUG FIX `project_trajectory()`: Correctly pass parameters.

-   MINOR CHANGES `select_waypoints()`: Do not recompute waypoints if
    trajectory already contains some.

-   MINOR CHANGES `convert_progressions_to_milestone_percentages()`:
    Solve tapply issues ahead of dplyr 1.0 release.

## Dynverse dependencies

<!-- Generated by "update_dependency_graphs.R" in the main dynverse repo -->

![](man/figures/dependencies.png)