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alevin-fry

4.7

Free

Alevin-fry is highly regarded for its speed, accuracy, and memory efficiency in single-cell RNA-seq data processing.

An efficient and flexible tool for processing single-cell sequencing data, focused on single-cell transcriptomics and feature barcoding.

DevelopmentFree pricingUpdated 2026-04-01

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Single-cell RNA-seq quantificationFeature barcoding analysis

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Editorial Note

An efficient and flexible tool for processing single-cell sequencing data, focused on single-cell transcriptomics and feature barcoding.

About alevin-fry

Alevin-fry is a suite of tools designed for rapid, accurate, and memory-frugal processing of single-cell and single-nucleus sequencing data. It consumes RAD files generated by piscem or salmon alevin, performing operations like generating permit lists and estimating the number of distinct molecules from each gene within each cell. The tool prioritizes safety, accuracy, and efficiency in terms of both time and memory. It is designed as a successor to alevin, subsuming its core features while introducing new capabilities and significantly improving performance. Alevin-fry supports enhanced transcriptomes using tools like pyroe, allowing for spliced and intronic or spliced and unspliced analysis. Output can be easily integrated into the R ecosystem using the fishpond package and assessed using alevinqc.

Quick Summary

An efficient and flexible tool for processing single-cell sequencing data, focused on single-cell transcriptomics and feature barcoding.

15-30 minutesSetup: advanced

Bioinformatics PipelinesSingle-Cell Analysis Tools

Product Release Intel

Data Freshness

Checked Apr 1, 2026

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Core Capabilities

Alevin-fry is a suite of tools designed for rapid, accurate, and memory-frugal processing of single-cell and single-nucleus sequencing data.

Use Cases

Quantifying gene expression in single-cell RNA-seq data

Accurate and efficient quantification of gene expression from scRNA-seq data, overcoming limitations of traditional methods.

VIEW EXECUTION STEPS

Generate RAD files using piscem or salmon.

Run alevin-fry to quantify gene expression.

Import the output into R using the fishpond package.

Perform downstream analysis using standard R packages.

Analyzing feature barcoding data

Efficiently process feature barcoding data to link cells to specific features.

VIEW EXECUTION STEPS

Generate RAD files containing feature barcode information.

Run alevin-fry to quantify feature barcodes.

Analyze the output to identify cells associated with each feature.

Integrate with other single-cell data for comprehensive analysis.

Identifying cell types in a heterogeneous population

Uncover distinct cell populations within complex tissues using single-cell transcriptomics.

VIEW EXECUTION STEPS

Process raw sequencing data with alevin-fry for quantification.

Perform dimensionality reduction and clustering analysis.

Identify marker genes for each cluster.

Assign cell types based on marker gene expression.

Studying transcriptional dynamics during development

Capture changes in gene expression over time during development.

VIEW EXECUTION STEPS

Collect single-cell samples at different developmental stages.

Process data with alevin-fry to quantify gene expression.

Perform trajectory analysis to infer developmental trajectories.

Identify genes that are differentially expressed along the trajectories.

Analyzing tumor heterogeneity in cancer research

Characterize the diverse cell populations within tumors to understand cancer progression and drug resistance.

VIEW EXECUTION STEPS

Process single-cell RNA-seq data from tumor samples with alevin-fry.

Identify distinct tumor cell subpopulations.

Analyze the gene expression profiles of each subpopulation.

Identify potential drug targets based on the unique characteristics of each subpopulation.

Analyzing immune cell responses to infection

Dissect the immune response at single-cell resolution to understand mechanisms of protection and pathogenesis.

VIEW EXECUTION STEPS

Isolate immune cells from infected tissues.

Process single-cell RNA-seq data with alevin-fry.

Identify activated immune cell populations.

Analyze the expression of immune-related genes in each population.

Identify key signaling pathways involved in the immune response.

alevin-fry

About alevin-fry

Core Capabilities

Main Tasks

Transcriptome Alignment

What this tool is best suited for

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Key Features

RAD File Processing

Permit List Generation

Molecular Counting

USA Mode Output

Enhanced Transcriptome Support

Simpleaf Integration

Use Cases

Quantifying gene expression in single-cell RNA-seq data

Analyzing feature barcoding data

Identifying cell types in a heterogeneous population

Studying transcriptional dynamics during development

Analyzing tumor heterogeneity in cancer research

Analyzing immune cell responses to infection

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