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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
Use with AI
Install the MCP server or CLI to instantly fetch scJoint documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/scjoint
CellChat — R package for inference, analysis, and visualization of cell-cell communication networks from single-cell RNA-seq data. Uses a curated ligand-receptor database (CellChatDB) to quantify sign
3 shared topics • 1 shared operation
SCENIC (pySCENIC) — gene regulatory network inference and transcription factor regulon analysis for single-cell RNA-seq data. Infers TF-target gene networks using GRNBoost2/GENIE3, refines regulons vi
3 shared topics • 1 shared operation
Use this skill for SCpubr workflows producing publication-quality visualizations of single-cell RNA-seq data in R. Covers UMAP/dimensionality reduction plots, violin plots, feature plots, dot plots, h
3 shared topics • 1 shared operation
Decoupler -- Python framework for inferring biological activities from omics data. Estimates transcription factor (TF) activities, pathway activities, and ligand-receptor interactions from gene expres
3 shared topics
PROGENy (Pathway RespOnsive GENes) is an R/Bioconductor package and Python decoupler-py model for inferring the activity of 14 cancer-relevant signaling pathways (EGFR, MAPK, PI3K, JAK-STAT, TGFb, TNF
3 shared topics