KlugerLab / GeneTrajectory

R implementation of GeneTrajectory
https://www.nature.com/articles/s41587-024-02186-3
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Gene Trajectory Inference

GeneTrajectory is a method for inferring gene trajectories in scRNA-seq data, which facilitates understanding of gene dynamics underlying biological processes. The major workflow of GeneTrajectory comprises the following four main steps:

Workflow

Install

GeneTrajectory can be installed in R as follows:

install.packages("devtools")
devtools::install_github("KlugerLab/GeneTrajectory")

A Python implementation is available at https://github.com/KlugerLab/GeneTrajectory-python.

Example tutorial

Please check GeneTrajectory tutorial.

References

References of GeneTrajectory functions can be found here.

Data used in the tutorial can be downloaded from Figshare.

Install GeneTrajectory-python

The easiest way is to create a virtualenv for gene_trajectory using reticulate

if(!reticulate::virtualenv_exists('gene_trajectory')){
  reticulate::virtualenv_create('gene_trajectory', packages=c('gene_trajectory'))
}
reticulate::use_virtualenv('gene_trajectory')

or to add to an existing virtualenv using

reticulate::py_install("gene-trajectory")

In general (especially in a conda environment) it can be installed with pip as

system(sprintf('%s -m pip install gene-trajectory', reticulate::py_exe()))

The development version can be installed as

system(sprintf('%s -m pip install git+https://github.com/Klugerlab/GeneTrajectory-python.git', reticulate::py_exe()))

This works both on virtualenv and conda.