Correcting Illumina sequencing errors for human data
classification
🧬 q-bio.GN
keywords
dataerrorsevaluationhumanilluminasequencingaccuracyalgorithm
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Summary: We present a new tool to correct sequencing errors in Illumina data produced from high-coverage whole-genome shotgun resequencing. It uses a non-greedy algorithm and shows comparable performance and higher accuracy in an evaluation on real human data. This evaluation has the most complete collection of high-performance error correctors so far. Availability and implementation: https://github.com/lh3/bfc Contact: hengli@broadinstitute.org
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