VISION aids in the interpretation of single-cell RNA-seq (scRNA-seq) data by selecting for gene signatures which describe coordinated variation between cells. While the software only requires an expression matrix and a signature library (available in online databases), it is also designed to integrate into existing scRNA-seq analysis pipelines by taking advantage of precomputed dimensionality reductions, trajectory inferences or clustering results. The results of this analysis are made available through a dynamic web-app which can be shared with collaborators without requiring them to install any additional software.
We recommend installing VISION via github using devtools:
See the DESCRIPTION file for a complete list of R dependencies. If the R dependencies are already installed, installation should finish in a few minutes.
VISION generally follows the same pipeline from iteration to iteration, where minor differences can be specified via the various parameters in a VISION object. On a typical VISION run:
For general instructions on running VISION, see the Getting Started vignette.
More information can be found throughout the rest of the tutorials on the Documentation site.