Chan Zuckerburg proposes an initative to advance support and development of the open source Salmon and Alevin software for gene expression quantification of single-cell and bulk RNA-seq

Salmon: Improving RNA-seq Quantification & Building an Inclusive Community

Gene expression quantification is a fundamental computational inference problem at the intersection of genomics, machine learning, and biology. The expression levels (abundances) of genes and transcripts must be computationally inferred from high-throughput RNA sequencing (RNA-seq). The open source software called Salmon and its single-cell mode Alevin are some of the most widely used and feature-rich tools for computing accurate expression measurements from raw sequencing data. Salmon is distributed in BioConda, DockerHub, and GitHub. Salmon has a large user base, active support community, and strong documentation and tutorials, and is an essential component of many biologist’s analysis pipelines. This project will expand the set of features available in Salmon and Alevin, improving their capabilities, usability and flexibility. Additionally, this project will fund the creation of improved documentation, tutorials and learning resources to help both new and experienced users alike get the most out of Salmon and Alevin.


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