Loading homepage
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
Use with AI
Install the MCP server or CLI to instantly fetch CytoTRACE -- Predicting Differentiation State from scRNA-seq documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/cytotrace
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
3 shared topics • 1 shared operation
HTSeq — Python framework for high-throughput sequencing data analysis, primarily used for counting aligned reads overlapping genomic features (genes, exons) from SAM/BAM/CRAM files using GTF/GFF annot
3 shared topics • 1 shared operation
Use when working with openCyto — the Bioconductor framework for automated, reproducible flow cytometry gating. Applies hierarchical gating strategies defined in a CSV template to GatingSet objects (fl
3 shared topics • 1 shared operation
Scrublet — Python toolkit for computational identification of cell doublets in single-cell RNA-seq data. Simulates synthetic doublets from observed transcriptomes and scores cells via k-nearest-neighb
3 shared topics • 1 shared operation
Use this skill for SCTransform normalization of single-cell RNA-seq count matrices. Route here when users ask about variance stabilizing transformation (VST), regularized negative binomial regression
3 shared topics • 1 shared operation