ShinyCell2: An extended library for simple and sharable visualisation of spatial, peak-based and multi-omic single-cell data
Chen, B. J.; Lim, Y. Y.; Yang, X.; Wang, L.; Rackham, O. J.; Ouyang, J. F.
Show abstract
Single-cell technologies now span multiple modalities, generating large, complex datasets that challenge analysis and sharing. We present ShinyCell2, an enhanced R package for interactive visualisation of single-cell multi-omics and spatial transcriptomics data. ShinyCell2 retains the simplicity and lightweight deployment of its predecessor while introducing advanced visualisations, cross-modality comparisons, and statistical tools tailored to spatial and multi-omic data. It enables intuitive, rapid exploration of high-dimensional data without requiring extensive computational expertise.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- DeepSpaceDB: a spatial transcriptomics atlas for interactive in-depth analysis of tissues and tissue microenvironments 93%
- Single-Cell Signature Explorer for comprehensive visualization of single cell signatures across scRNA-seq data sets 93%
- The Neuroscience Multi-Omic Archive: A BRAIN Initiative resource for single-cell transcriptomic and epigenomic data from the mammalian brain 93%
Similar papers in this journal
Similar papers in this journal
- RNApysoforms: Fast rendering interactive visualization of RNA isoform structure and expression in Python 95%
- cOmicsArt - a customizable Omics Analysis and reporting tool 95%
- AnnSQL: A Python SQL-based package for fast large-scale single-cell genomics analysis using minimal computational resources 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.