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Single Cell Transcriptomics Pipeline

Discover How Individual Cells Contribute To Biology

  • Cell-level resolution - Stop seeing averages. See exactly what each individual cell is doing inside your tissue
  • Zero-code scRNA-seq pipeline - FASTQ files in. UMAP clusters out. Quality control alignment and cell annotation handled automatically
  • Publication-ready outputs - UMAP plots cell annotations and pathway reports delivered as clean interactive HTML the moment your run finishes
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Single-Cell Resolution. Full Biological Context.

  • Automated scRNA-seq pre-processing and QC
  • Cell clustering and population identification
  • Marker gene detection and cell type annotation
  • Trajectory and pseudotime analysis
  • Pathway enrichment at single-cell resolution

Globally Trusted By Clinicians And Researchers

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  • Pre-Processing
  • Post-Processing
  • Reports
  • Deliverables

Raw Reads In. Clean Cell Matrices Out.

Drop your FASTQ files and walk away. QC trimming alignment and doublet removal run automatically. Your data is clean before analysis even begins.

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Your Clusters. Auto-Identified.

Count matrices normalize then flow into PCA and UMAP. Cells group by expression. Marker genes label each cluster automatically. No manual work needed.

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Built For Modern Research Sharing

UMAP plots violin plots and annotation tables all in one interactive HTML report. Download it. Share it. Submit it.

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Clustered. Annotated. Ready to publish.

UMAP plots, cell annotations, differential expression results, and pathway reports appear in your dashboard automatically once the pipeline finishes.

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 Our Pipeline Modules

Every Layer Of Single-Cell Analysis Covered.

Cell QC and Filtering

FASTQ files go through FastQC trimming STARsolo alignment and doublet detection so only high quality cells move into analysis.

Clustering Analysis

UMAP and Leiden clustering group similar cells automatically while marker genes and reference databases identify cell populations instantly.

Variant Annotation

Differential expression and pathway analysis reveal changing genes across cell groups while pseudo-time tracks cell state transitions.

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Research Teams

See More. Uncover What Bulk RNA-Seq Missed

From raw FASTQ files to fully annotated cell atlases GenomeBeans makes single-cell analysis fast accurate and accessible without writing a single line of code.

What even is single-cell transcriptomics?

Bulk RNA-seq gives you one averaged signal from thousands of mixed cells. Single-cell gives you an individual profile for every single cell in your sample. If rare cell populations are driving your biology bulk will never show you that. Single-cell will.

Do I need to know how to code?

Zero coding required. Upload your FASTQ files choose your reference and GenomeBeans handles filtering clustering annotation and pathway analysis automatically. Your report is ready with visual results and insights.

What does the final report look like?

Your results are delivered in a structured, easy-to-navigate report that highlights key findings, quality metrics, and biological insights relevant to your analysis.

Can report find rare cell types?

Yes and that is the whole point. Clustering resolution is tuned to separate even closely related subtypes. Doublet detection and ambient RNA filtering make sure rare populations show up clean without false positives padding your results.

How is this different from Bulk Transcriptomics?

Bulk averages every cell in your sample into one number per gene. Single-cell keeps every cell separate. Ten cell types in your sample means ten distinct profiles not one blended signal that hides what is actually happening.

Is my sequencing data safe and private?

Completely private. You own everything. Nothing is shared or sold. Your data lives on our servers for 90 days then it is permanently deleted. No exceptions. No fine print.

Ready To Hear Every Cell's Story?

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