CelliVerse

Wed, 19 Aug 2026 00:00:00 +0000

Overview

celliverse provides an integrated framework for single-cell RNA-seq analysis with a focus on data-driven clustering, marker discovery, marker assessment and cell type annotation. Its methods use cell-intrinsic expression organisation to support robust characterisation of cellular populations while remaining practical within common single-cell workflows.

The package includes ClustoCell for unsupervised cell clustering and sub-clustering, tools for positive and negative marker discovery, marker purity assessment, dataset-level feature selection, label transfer and annotation workflows. It also provides CelliVerse MarkerDB, a curated marker resource containing positive and negative markers for human and mouse cell types.

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ClustoCell

Sun, 24 May 2026 00:00:00 +0000

Overview

ClustoCell is a reference-independent framework for resolving cell types and states from single-cell transcriptomes by modelling cellular relationships using cell-intrinsic expression organisation rather than relying on global transcriptional variance or external reference labels.

ClustoCell stratifies expression within each cell and uses this structure to build cell-similarity graphs, identify biologically coherent populations, discover cluster-specific markers and optionally resolve sub-clusters. It is implemented in the CelliVerse R package and is designed to support the recovery of stable cellular communities, rare or transitional states, and malignant versus non-malignant populations.

Beyond clustering, the broader CelliVerse workflow connects ClustoCell results to marker assessment, feature selection and cell type annotation, including annotation with CelliVerse MarkerDB.

Marker Discovery | Adrian Salavaty

CelliVerse

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ClustoCell

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