Motivations: Short-read accuracy is important for downstream analyses such as genome assembly and hybrid long-read correction. Despite much work on short-read correction, present-day correctors either do not scale well on large data sets or consider reads as mere suites of k-mers, without taking into account their full-length read information. Results: We propose a new method to correct short reads using de Bruijn graphs, and implement it as a tool called Bcool. As a first step, Bcool constructs a compacted de Bruijn graph from the reads. This graph is filtered on the basis of k-mer abundance then of unitig abundance, thereby removing most sequencing errors. The cleaned graph is then used as a reference on which the reads are mapped to correct them. We show that this approach yields more accurate reads than k-mer-spectrum correctors while being scalable to human-size genomic datasets and beyond. Availability and Implementation: The implementation is open source and available at http://github.com/Malfoy/BCOOL under the Affero GPL license and as a Bioconda package. Contact: Antoine Limasset firstname.lastname@example.org & Jean-Francois Flot email@example.com & Pierre Peterlongo firstname.lastname@example.org
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