ScarfWeb

ScarfWeb is a browser-based single-cell omics analysis platform designed for researchers who need to explore, annotate, and share single-cell RNA sequencing data without writing code or managing local compute infrastructure. Built by Nygen, it brings together every stage of single-cell analysis — from data ingestion and quality control through to differential expression, visualization, and collaboration — in one unified workspace accessible entirely through the browser.

Used by over 1,500 researchers across more than 100 top global institutions, ScarfWeb is designed for both bench scientists and bioinformaticians working on the same datasets. It is ISO 27001 certified and SOC 2 compliant, making it suitable for teams with strict data governance requirements.

Data Management Capabilities

• Upload preprocessed count matrices in common formats including MTX, H5AD, H5, and CSV via a simple drag-and-drop interface.
• Ingest CITE-Seq and multi-modal data, with ADT and HTO data automatically detected and separated during import.
• Merge datasets across samples, batches, or experimental conditions, and demultiplex HTO-labeled pools without requiring external tools.
• Import existing metadata, sample annotations, condition labels, and clustering results from Seurat, Scanpy, or other pipelines without reformatting.
• Edit cell-level and sample-level annotations across an entire dataset in a single step using the bulk metadata editor.

Analysis Pipeline and Visualization

• Every step from QC to differential expression runs through a visual interface with adjustable parameters, enabling researchers to drive their own analysis without bioinformatics queues.
• All workflows are fully reproducible, versioned, and auditable, with every parameter, filter, and selection logged and shareable.
• Interactive visual exploration of clusters and embeddings is built into the workspace alongside statistical testing tools.
• Publication-ready figures, exportable tables, and auto-generated methods sections are produced directly from the platform, with every output traceable to the exact parameters used.

AI-Powered Cell Annotation with CyteType

• CyteType runs directly inside the ScarfWeb analysis session, providing automated cell type annotation without requiring a separate tool or data export.
• Annotation includes confidence scoring, marker-level evidence, ontology mapping, and literature linking.
• Researchers can review and override annotations at the cluster level, maintaining full control over characterization decisions.

Collaboration and Sharing

• Bench scientists and bioinformaticians can work simultaneously within the same dataset and session.
• Results can be shared via public links or private access controls.
• Analyses can be published to the Nygen Database or exported for use in scripted pipelines.
• The entire analysis remains in one place regardless of how many collaborators need access, eliminating file transfers and version confusion.

ScarfWeb runs on scalable cloud infrastructure across 22 AWS regions with no local installation or pipeline setup required. Data is encrypted at rest and in transit, with comprehensive backups and full GDPR adherence, ensuring that research outputs are both secure and defensible for peer review and publication.