LAUSR

MOTIVATION Error correction is a fundamental preprocessing step in many 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 hours on a single workstation using GPU acceleration. AVAILABILITY 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.