Salmon is a tool for quantifying the expression of transcripts using RNA-seq data. Salmon uses new algorithms (specifically, coupling the concept of quasi-mapping with a two-phase inference procedure) to provide accurate expression estimates very quickly (i.e. wicked-fast) and while using little memory. Salmon performs its inference using an expressive and realistic model of RNA-seq data that takes into account experimental attributes and biases commonly observed in real RNA-seq data.
If you find Salmon useful, or have suggestions for improvement, please let us know! If you use Salmon in your work, please cite the Salmon paper:
Patro, R., Duggal, G., Love, M. I., Irizarry, R. A., & Kingsford, C. (2017). Salmon provides fast and bias-aware quantification of transcript expression. Nature Methods.
You can find other citation formats on Google Scholar here.
- NSF BIO-1564917, CCF-1256087, CCF-1053918, EF-0849899
- NIH 1R21HG006913, 1R21AI085376, 1R01HG005220, 5T32CA009337-35
- Alfred P. Sloan Foundation Sloan Research Fellowship to Carl Kingsford
This material is based upon work supported by the National Science Foundation under Grant Numbers EF-0849899, IIS-0812111, CCF-1053918. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.