Lighter: fast and memory-efficient error correction without counting

Lighter: fast and memory-efficient error correction without counting
Li Song, Liliana Florea, Ben Langmead

Lighter is a fast and memory-efficient tool for correcting sequencing errors in high-throughput sequencing datasets. Lighter avoids counting k-mers in the sequencing reads. Instead, it uses a pair of Bloom filters, one populated with a sample of the input k-mers and the other populated with k-mers likely to be correct based on a simple test. As long as the sampling fraction is adjusted in inverse proportion to the depth of sequencing, the Bloom filter size can be held constant while maintaining near-constant accuracy. Lighter is easily applied to very large sequencing datasets. It is parallelized, uses no secondary storage, and is both faster and more memory-efficient than competing approaches while achieving comparable accuracy. Lighter is free open source software available from https://github.com/mourisl/Lighter/.

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