Asc-Seurat documentation

Asc-Seurat is a web application for single-cell RNA-seq analysis, built around Seurat v5. It walks you through the full scRNA-seq workflow — quality control, normalization, clustering, differential expression, trajectory inference, cell-type annotation, and publication-ready visualization — without writing any R code.

This documentation covers Asc-Seurat v3, the current release. v3 builds on the original Asc-Seurat published in BMC Bioinformatics (2021) and keeps the same end-to-end click-driven workflow.

Asc-Seurat home screen.

Asc-Seurat home screen.

What you can do with Asc-Seurat

  • Load data from many formats — 10X Genomics directories, 10X HDF5, CSV/TSV count matrices, AnnData (.h5ad), and existing Seurat objects.

  • Quality control and filtering — interactive violin plots, per-cell metric thresholds, and optional doublet removal.

  • Normalization and clustering — LogNormalize or SCTransform, UMAP and t-SNE embeddings, and an inline control to rename clusters with biological labels.

  • Differential expression — cluster markers, between-cluster DE, and between-sample DE for integrated datasets.

  • Multi-sample integration — declare samples inline, set per-sample QC, and integrate with RPCA (Seurat) or Harmony.

  • Trajectory inference — three supported methods: Slingshot, PAGA, and Monocle 3, plus method-specific gene discovery.

  • Cell-type annotation — automated labelling against reference atlases via SingleR.

  • Advanced plots — stacked violin and multi-gene dot plots, with control over gene and cluster ordering.

  • Per-gene plot bundles — download a zipped collection of every plot for a selected gene in one click.

  • Bookmarking and session reports — capture an analysis state and reproduce or share it later.

Where to start