KlugerLab / GeneTrajectory

R implementation of GeneTrajectory

Home Page: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:

  • Step 1. Build a cell-cell kNN graph in which each cell is connected to its k-nearest neighbors. Find the shortest path connecting each pair of cells in the graph and denote its length as the graph distance between cells.
  • Step 2. Compute pairwise graph-based Wasserstein distance between gene distributions, which quantifies the minimum cost of transporting the distribution of a given gene into the distribution of another gene in the cell graph.
  • Step 3. Generate a low-dimensional representation of genes (using Diffusion Map by default) based on the gene-gene Wasserstein distance matrix. Identify gene trajectories in a sequential manner.
  • Step 4. Determine the order of genes along each gene trajectory.

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.

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.

About

R implementation of GeneTrajectory

https://www.nature.com/articles/s41587-024-02186-3


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