Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms

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. RNA-seq has become the de facto standard technique to measure gene expression, and it is commonly the first step in an analysis of differential expression among multiple samples1. However, the throughput of technologies used to generate transcriptomic sequencing reads is accelerating faster than the speed of the computers used to analyze these data. The growing repository of data from archived experiments invites reanalysis in the light of new discoveries, but existing methods are too time-consuming to allow frequent reanalysis. The divide between data-acquisition and data-analysis capabilities will only increase as RNA-seq is adopted for clinical use2. Finally, the sensitivity of existing methods to parameter choice