Understand your cells,
layer by layer

Matisse brings isoform-resolved splicing and chromatin accessibility into your single-cell workflow — on top of Seurat and Signac, using the same cells, the same clusters, the same UMAP.

Install View walkthrough →

What you can discover

Questions Matisse is built to answer

1

Cell-type-specific splicing

Do my neurons and astrocytes process this exon differently — and by how much?

2

Chromatin shapes isoforms

Is the splicing switch I see linked to chromatin accessibility changes at the same locus?

3

Isoform switches along a trajectory

Is there a coordinated splicing change as my cells differentiate or respond to a stimulus?

4

Context for bulk RNA-seq

I see a splicing difference in bulk data — which cell type is responsible?

PSI values for Ptbp1 exon 9 on a UMAP of mouse cortex cells. Neurons (blue) consistently skip this exon (low PSI); astrocytes (red) include it (high PSI). Same gene — different isoforms — visible at single-cell resolution.

Works with your existing setup

Matisse layers on top of Seurat and Signac — your clusters, UMAP, and cell labels stay intact

Short-read RNA (10x) STAR / STARsolo junction count matrix

Long-read / isoform Bagpiper FLAMES LIQA PacBio MAS-seq

ATAC / chromatin 10x Multiome Signac ArchR

Event annotations SUPPA2 generateEvents rMATS BuildSimpleEvents()

Installation

install.packages("remotes")
remotes::install_github("avisrilab/Matisse")

Ready to explore your data?

View the full walkthrough →