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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
Use with AI
Install the MCP server or CLI to instantly fetch Salmon / Alevin documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/salmonalevin
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
2 shared topics • 3 shared operations
Scanorama -- efficient batch correction and integration of heterogeneous single-cell RNA-seq datasets using panoramic stitching. Aligns and merges multiple scRNA-seq experiments via mutual nearest nei
2 shared topics • 3 shared operations
alevin-fry — fast, accurate, and memory-frugal Rust-based tool for single-cell and single-nucleus RNA-seq quantification. Processes RAD (Reduced Alignment Data) files from salmon alevin to generate ce
2 shared topics • 2 shared operations
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
2 shared topics • 2 shared operations
Use when performing single-cell QTL (sc-eQTL, sc-sQTL) mapping with SAIGE-QTL. SAIGE-QTL extends the SAIGE framework to single-cell RNA-seq data using Poisson mixed models to handle count overdispersi
2 shared topics • 2 shared operations