Kmer counting is usually the first step in analysis of NGS sequences. In Kmer Counting a 2014 Recap, we brought the topic of kmer counting up to date. To further speed up execution, some researchers are designing algorithms to skip the k-mer counting step altogether, as you can see in this paper.
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/.