Overview#

alevin-fry` is a suite of tools for the rapid, accurate and memory-frugal processing single-cell and single-nucleus sequencing data. It consumes RAD files generated by salmon alevin, and performs common operations like generating permit lists, and estimating the number of distinct molecules from each gene within each cell. The focus in alevin-fry` is on safety, accuracy and efficiency (in terms of both time and memory usage).

You can read the paper describing alevin fry, “Alevin-fry unlocks rapid, accurate, and memory-frugal quantification of single-cell RNA-seq data” [here](https://www.nature.com/articles/s41592-022-01408-3), and the pre-print [on bioRxiv](https://www.biorxiv.org/content/10.1101/2021.06.29.450377v1).

Other resources for alevin-fry#

In addition to the current documentation page, there are numerous other resources to help you learn more about alevin-fry, how to process data using this program, and how to further process the output of alevin-fry in downstream analysis.

Tutorials#

A collection of tutorials describing how to process different types of data with alevin-fry and describing different features of alevin-fry is available here.

FAQ#

We hope to make use of GitHub discussions to answer frequently asked questions, and to discuss other issues relevant to the development and use of alevin-fry. You can visit the GitHub discussion page for alevin-fry here. GitHub discussions are also a good place to raise large-scale feature requests to see if they make sense in the context of alevin-fry. For small-scale feature requests, or to report bugs or unexpected behavior you encounter when processing data with alevin-fry, please make use of our GitHub issues page.

Quality Control#

The alevinQC package supports quality control of alevin-fry processed data.

Easy loading of USA-mode data#

The fishpond package contains many methods for making the ingestion of quantification results generated by salmon and alevin-fry into R easy. In particular, you can find documentation on the loadFry function here. This makes it easy to import USA-mode quantification results into a SingleCellExperiment object, and to properly extract or combine the spliced, unspliced, and ambiguous count components.