EBSeq is an R/Bioconductor package implementing an empirical Bayes hierarchical model for identifying differentially expressed (DE) genes and isoforms in RNA-seq experiments. It supports both two-cond
Use with AI
Install the MCP server or CLI to instantly fetch Ebseq documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/ebseq
Corset — C++ tool for clustering de novo assembled transcripts into gene-level groups and producing gene-level counts for differential expression analysis. Groups contigs from Trinity, Trans-ABySS, or
2 shared topics • 1 shared operation
EnhancedVolcano — R/Bioconductor package for creating publication-ready volcano plots with enhanced colouring and labeling from differential expression results. Visualize DESeq2, limma, edgeR output w
2 shared topics • 1 shared operation
sciPENN — neural network model for single-cell protein expression imputation and multi-omics integration. Transfers protein predictions from CITE-seq (paired RNA+protein) training data to unpaired RNA
2 shared topics • 1 shared operation
Use when working with MAST — an R/Bioconductor package for differential expression analysis of single-cell RNA-seq data. Fits a hurdle model (zero-inflated two-component regression) via zlm() to handl
1 shared topic • 2 shared operations
t-SNE (t-distributed Stochastic Neighbor Embedding) for nonlinear dimensionality reduction and visualization of high-dimensional data. Covers Barnes-Hut and exact modes, FIt-SNE/openTSNE interpolation
2 shared topics