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

Avi Srivastava, Hirak Sarkar, Nitish Gupta, Rob Patro
doi: https://doi.org/10.1101/029652
Avi Srivastava
1Department of Computer Science, Stony Brook University Stony Brook, NY 11794-2424.
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Hirak Sarkar
1Department of Computer Science, Stony Brook University Stony Brook, NY 11794-2424.
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Nitish Gupta
1Department of Computer Science, Stony Brook University Stony Brook, NY 11794-2424.
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Rob Patro
1Department of Computer Science, Stony Brook University Stony Brook, NY 11794-2424.
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Abstract

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.

Contact: rob.patro{at}cs.stonybrook.edu

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted January 16, 2016.
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RapMap: A Rapid, Sensitive and Accurate Tool for Mapping RNA-seq Reads to Transcriptomes
Avi Srivastava, Hirak Sarkar, Nitish Gupta, Rob Patro
bioRxiv 029652; doi: https://doi.org/10.1101/029652
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RapMap: A Rapid, Sensitive and Accurate Tool for Mapping RNA-seq Reads to Transcriptomes
Avi Srivastava, Hirak Sarkar, Nitish Gupta, Rob Patro
bioRxiv 029652; doi: https://doi.org/10.1101/029652

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