CARE: context-aware sequencing read error correction

Author:

Kallenborn Felix1ORCID,Hildebrandt Andreas1,Schmidt Bertil1

Affiliation:

1. Department of Computer Science, Johannes Gutenberg University, Mainz 55122, Germany

Abstract

Abstract Motivation Error correction is a fundamental pre-processing step in many Next-Generation Sequencing (NGS) pipelines, in particular for de novo genome assembly. However, existing error correction methods either suffer from high false-positive rates since they break reads into independent k-mers or do not scale efficiently to large amounts of sequencing reads and complex genomes. Results We present CARE—an alignment-based scalable error correction algorithm for Illumina data using the concept of minhashing. Minhashing allows for efficient similarity search within large sequencing read collections which enables fast computation of high-quality multiple alignments. Sequencing errors are corrected by detailed inspection of the corresponding alignments. Our performance evaluation shows that CARE generates significantly fewer false-positive corrections than state-of-the-art tools (Musket, SGA, BFC, Lighter, Bcool, Karect) while maintaining a competitive number of true positives. When used prior to assembly it can achieve superior de novo assembly results for a number of real datasets. CARE is also the first multiple sequence alignment-based error corrector that is able to process a human genome Illumina NGS dataset in only 4 h on a single workstation using GPU acceleration. Availabilityand implementation CARE is open-source software written in C++ (CPU version) and in CUDA/C++ (GPU version). It is licensed under GPLv3 and can be downloaded at https://github.com/fkallen/CARE. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

Deutsche Forschungsgemeinschaft

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Reference31 articles.

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3. SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing;Bankevich;J. Comput. Biol.,2012

4. Assembling large genomes with single-molecule sequencing and locality-sensitive hashing;Berlin;Nat. Biol.,2015

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