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This is the development version of veloviz; for the stable release version, see veloviz.

VeloViz: RNA-velocity informed 2D embeddings for visualizing cell state trajectories

Bioconductor version: Development (3.20)

VeloViz uses each cell’s current observed and predicted future transcriptional states inferred from RNA velocity analysis to build a nearest neighbor graph between cells in the population. Edges are then pruned based on a cosine correlation threshold and/or a distance threshold and the resulting graph is visualized using a force-directed graph layout algorithm. VeloViz can help ensure that relationships between cell states are reflected in the 2D embedding, allowing for more reliable representation of underlying cellular trajectories.

Author: Lyla Atta [aut, cre] , Jean Fan [aut] , Arpan Sahoo [aut]

Maintainer: Lyla Atta <lylaatta at>

Citation (from within R, enter citation("veloviz")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

Visualizing cell cycle trajectory in MERFISH data using VeloViz HTML R Script
Reference Manual PDF


biocViews DimensionReduction, GeneExpression, RNASeq, Sequencing, Software, Transcriptomics, Visualization
Version 1.11.0
In Bioconductor since BioC 3.14 (R-4.1) (2.5 years)
License GPL-3
Depends R (>= 4.1)
Imports Rcpp, Matrix, igraph, mgcv, RSpectra, grDevices, graphics, stats
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Suggests knitr, rmarkdown, testthat
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Source Package veloviz_1.11.0.tar.gz
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macOS Binary (arm64) veloviz_1.11.0.tgz
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