Rxivist logo

Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 54,982 bioRxiv papers from 253,713 authors.

RapMap: A Rapid, Sensitive and Accurate Tool for Mapping RNA-seq Reads to Transcriptomes

By Avi Srivastava, Hirak Sarkar, Nitish Gupta, Rob Patro

Posted 22 Oct 2015
bioRxiv DOI: 10.1101/029652 (published DOI: 10.1093/bioinformatics/btw277)

Motivation: 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. Results: We 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 --- our tool implementing quasi-mapping --- is capable of mapping sequencing reads to a target transcriptome substantially faster than existing alignment tools. The algorithm we employ 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. We 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. Availability: RapMap is implemented in C++11 and is available as open-source software, under GPL v3, at https://github.com/COMBINE-lab/RapMap.

Download data

  • Downloaded 9,360 times
  • Download rankings, all-time:
    • Site-wide: 104 out of 54,982
    • In bioinformatics: 20 out of 5,689
  • Year to date:
    • Site-wide: 648 out of 54,982
  • Since beginning of last month:
    • Site-wide: 443 out of 54,982

Altmetric data


Downloads over time

Distribution of downloads per paper, site-wide


Sign up for the Rxivist weekly newsletter! (Click here for more details.)


News