In Non-hybrid methods71,74, by finding regions that overlap fairly well between reads and taking the consensus of the overlapped regions (i.e. the majority nucleotide at each position), some errors can be eliminated. In many analyses and sequencing data processing pipelines, the first step is to break up the reads into all possible overlapping subsequences of length \(k\) called \(k\)-mers (e.g the 3-mers of ATTGC are ATT, TTG and TGC). Rare \(k\)-mers in the read dataset, i.e. \(k\)-mers that appear only a handful of times in all the reads, are likely the result of an error and filtering them out can improve analysis. One or both of these procedures are implemented in several pieces of commonly used software such as assembler like wtdbg275, and canu76 or standalone long-read correctors like daccord77. In some cases, errors are corrected not on the raw reads but after having assembled the long reads into long continuous sequences (contigs), this process is called polishing. The ntEdit polisher78 also filters out rare \(k\)-mers to correct errors. The Arrow79 and Nanopolish80 polishers correct the assembly using the raw PacBio and ONT long reads respectively, and Racon81 can use bot types of long-reads to polish assemblies.
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