Effect of k-tuple length on sample-comparison with high-throughput sequencing data

Experiments show that our pipeline with long k-tuple features: ①separates genomes with high similarity; ②outperforms short k-tuple models in all experiments. When k ≥ 12, the short k-tuple measures are not applicable anymore. When k is between 20 and 40, long k-tuple pipeline obtains much better grouping results; ③is free from the effect of sequencing platforms/protocols. ③We obtained meaningful and supported biological results on the 40-tuples selected for comparison.