We introduce Sailfish, a computational method for quantifying the abundance of previously annotated RNA isoforms from RNA-seq data. Because Sailfish entirely avoids mapping reads, a time-consuming step in all current methods, it provides quantification estimates much faster than do existing approaches (typically 20 times faster) without loss of accuracy. By facilitating frequent reanalysis of data and reducing the need to optimize parameters, Sailfish exemplifies the potential of lightweight algorithms for efficiently processing sequencing reads.
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This work has been partially funded by the US National Science Foundation (CCF-1256087, CCF-1053918, and EF-0849899) and US National Institutes of Health (R21AI085376, R21HG006913 and R01HG007104). C.K. received support as an Alfred P. Sloan Research Fellow. We would like to thank A. Roberts for helping to diagnose and resolve an artifact in an earlier version of this manuscript pertaining to the synthetic data generated by the Flux Simulator.
The authors declare no competing financial interests.
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Patro, R., Mount, S. & Kingsford, C. Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms. Nat Biotechnol 32, 462–464 (2014). https://doi.org/10.1038/nbt.2862
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