scvelo

Version:

2.4

Category:

bio

Cluster:

Loki

Author / Distributor

https://scvelo.readthedocs.io/

Description

ScVelo is a scalable toolkit for RNA velocity analysis in single cells. RNA velocity enables the recovery of directed dynamic information by leveraging splicing kinetics. ScVelo generalizes concept of RNA velocity by relaxing previously made assumptions with a stochastic and a dynamical model that solves the full transcriptional dynamics. It adapts RNA velocity to widely varying specifications such as non-stationary populations.

Documentation

>>> import scvelo as scv
>>> scv.__version__
'0.2.4'

Core commands:
--------------
scv.read()                   Load data from .loom or .h5ad
scv.pp.filter_and_normalize Normalize & log transform
scv.pp.moments()            Compute nearest-neighbor graph
scv.tl.velocity()           Compute RNA velocity (stochastic/dynamical)
scv.tl.latent_time()        Infer latent time from dynamics
scv.pl.velocity_embedding() Visualize velocity on UMAP or PCA

Help:
  >>> help(scv)
  >>> scv.settings

Examples/Usage

  • Load the module:

$ module load bio/scvelo/0.2.4

  • Start a Python session and analyze a .loom file:

import scvelo as scv
adata = scv.read("data.loom", cache=True)
scv.pp.filter_and_normalize(adata)
scv.pp.moments(adata)
scv.tl.velocity(adata)
scv.tl.velocity_graph(adata)
scv.pl.velocity_embedding_stream(adata, basis='umap')

  • Plot latent time:

scv.tl.recover_dynamics(adata)
scv.tl.latent_time(adata)
scv.pl.scatter(adata, color='latent_time', color_map='gnuplot')

  • Unload the module:

$ module unload bio/scvelo/0.2.4

Installation

Source code is obtained from scVelo