CellBender removes ambient RNA contamination and technical noise from droplet-based single-cell RNA-seq data using a deep generative model (VAE). Processes raw 10x Genomics feature-barcode matrices to
Use with AI
Install the MCP server or CLI to instantly fetch CellBender documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/cellbender
Cellranger-arc — 10x Genomics pipeline for processing Multiome ATAC + Gene Expression data from the Chromium Multiome kit. Aligns FASTQ reads, calls peaks, quantifies gene expression and chromatin acc
3 shared topics • 2 shared operations
CopyKAT (Copy number Karyotyping of Tumors) — R package for inferring genome-wide aneuploidy and copy number variations from single-cell RNA-seq data. Uses Bayesian segmentation to distinguish tumor (
3 shared topics • 1 shared operation
Use when working with EmptyDrops or DropletUtils — the Bioconductor R package for distinguishing real cells from empty droplets in droplet-based single-cell RNA-seq data (10x Genomics, Drop-seq, inDro
3 shared topics • 1 shared operation
Use when performing single-cell QTL (sc-eQTL, sc-sQTL) mapping with SAIGE-QTL. SAIGE-QTL extends the SAIGE framework to single-cell RNA-seq data using Poisson mixed models to handle count overdispersi
3 shared topics • 1 shared operation
salmon — Fast, bias-aware transcript quantification from RNA-seq data using selective alignment to the transcriptome. Supports bulk RNA-seq (mapping-based and alignment-based modes), single-cell RNA-s
3 shared topics • 1 shared operation