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Next generation sequencing (NGS) technologies like Illumina and third generation sequencing (TGS) technologies like PacBio and Oxford Nanopore Technology use different techniques for sequencing and provide reads of different lengths and error profiles. Many tools exist for error correction of such sequencing data, improving the quality of downstream analyses. In this chapter, we evaluate the performance of 23 error-correction tools, providing insight into their strengths and weaknesses. This is accomplished through a set of algorithms we have developed and implemented as SPECTACLE, a Software Package for Error Correction Tool Assessment on nuCLEic acid sequences, and a dataset for NGS and TGS reads that we compiled emphasizing challenging scenarios for error correction tools. This chapter provides the reader an understanding of available tools, including advice on selecting appropriate tools for different circumstances. It also provides insights regarding aspects of sequencing data to be addressed to improve tool accuracy.
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