scib (single-cell integration benchmarking) -- Python framework for evaluating and benchmarking batch correction and data integration methods in single-cell omics. Computes standardized metrics for bi
Use with AI
Install the MCP server or CLI to instantly fetch scib -- Single-Cell Integration Benchmarking documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/scib
ConsensusClusterPlus — R/Bioconductor package for determining cluster count and membership by stability evidence in unsupervised analysis, implementing the Monti et al. (2003) consensus clustering alg
1 shared topic • 1 shared operation
CytoTRACE -- computational method for predicting relative differentiation state of cells from single-cell RNA-seq data. Uses gene counts (number of detectably expressed genes per cell) as a robust pro
1 shared topic • 1 shared operation
DecontX — R/Bioconductor method in the celda package for estimating and removing ambient RNA contamination from droplet-based single-cell RNA-seq data. Uses a Bayesian Dirichlet mixture model over cel
1 shared topic • 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
1 shared topic • 1 shared operation
Salmon is an ultrafast, bias-correcting tool for quantifying transcript abundances from RNA-seq reads using quasi-mapping or selective alignment. Alevin is Salmon's single-cell mode for generating cel
1 shared topic • 1 shared operation