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scBERT is a transformer-based single-cell RNA-seq annotation workflow from Tencent AI Lab Healthcare that follows a pretrain-and-fine-tune pattern for cell type labeling. Use this skill when users men
Use with AI
Install the MCP server or CLI to instantly fetch scBERT documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/scbert
WARP (WDL Analysis Research Pipelines) — Broad Institute's cloud-optimized collection of genomics pipelines written in WDL (Workflow Description Language). Covers whole-genome sequencing (WGS), whole-
2 shared topics • 1 shared operation
scJoint integrates atlas-scale single-cell RNA-seq and scATAC-seq data using transfer learning. Transfers cell type labels from annotated RNA datasets to unannotated ATAC datasets via joint neural net
2 shared topics • 1 shared operation
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2 shared topics • 1 shared operation
Use when working with scran pooling normalization — scranpool — the pool-and-deconvolve size-factor estimation method for single-cell RNA-seq normalization. Pools cells to robustly estimate size facto
2 shared topics • 1 shared operation
UCE (Universal Cell Embeddings) — species-agnostic cell embedding model from Stanford SNAP Lab that uses protein language models (ESM-2) to create universal cell representations without species-specif
2 shared topics • 1 shared operation