RapMap – a rapid, sensitive and accurate tool for mapping RNA-seq reads to transcriptomes

The alignment of sequencing reads to a transcriptome is a common and important step in many RNA-seq analysis tasks. When aligning RNA-seq reads directly to a transcriptome (as is common in the de novo setting or when a trusted reference annotation is available), care must be taken to report the potentially large number of multi-mapping locations per read. This can pose a substantial computational burden for existing aligners, and can considerably slow downstream analysis.

Researchers at Stony Brook University introduce a novel concept, quasi-mapping, and an efficient algorithm implementing this approach for mapping sequencing reads to a transcriptome. By attempting only to report the potential loci of origin of a sequencing read, and not the base-to-base alignment by which it derives from the reference, RapMap-their tool implementing quasi-mapping-is capable of mapping sequencing reads to a target transcriptome substantially faster than existing alignment tools. The algorithm they use to implement quasi-mapping uses several efficient data structures and takes advantage of the special structure of shared sequence prevalent in transcriptomes to rapidly provide highly-accurate mapping information. The researchers demonstrate how quasi-mapping can be successfully applied to the problems of transcript-level quantification from RNA-seq reads and the clustering of contigs from de novo assembled transcriptomes into biologically meaningful groups.


The transcriptome (consisting of transcripts t1,,t6) is converted into a $-separated string, T, on which a suffix array, SA[T], and a hash table, h, are constructed. The mapping operation begins with a k-mer (here, k = 3) mapping to an interval [b,e)  in SA[T]. Given this interval and the read, MMPi and NIP(MMPi) are calculated as described in section 2. The search for the next hashable k-mer begins k bases before NIP(MMPi)

Availability – RapMap is implemented in C ++11 and is available as open-source software, under GPL v3, at https://github.com/COMBINE-lab/RapMap


Srivastava A, Sarkar H, Gupta N, Patro R. (2016) RapMap: a rapid, sensitive and accurate tool for mapping RNA-seq reads to transcriptomes. Bioinformatics 32(12):i192-i200. [article]

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