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Abstract
We introduce Salmon, a method for quantifying transcript abundance from RNA-seq reads that is both extremely fast and that supports rich, experiment-specific models to reduce the effects of biases of the RNA-seq protocol. Salmon does this by combining a novel technique for mapping reads to transcripts with a dual-phase stochastic inference algorithm and a feature-rich probabilistic model. These innovations allow Salmon to obtain very accurate estimates of transcript abundance, while improving on the speed of already-fast techniques such as Sailfish.
This is joint work with Rob Patro and Geet Duggal.