High‐frequency k‐mer counting at low memory footprint

Abstract Genomics data analysis requires efficient tools to address the vast amount of data generated by current next‐generation sequencing technologies. K‐mer counting works face difficulties in balancing high memory overhead with statistical precision. We designed a high‐frequency k‐mer statistical computation based on the Space Saving algorithm and a novel hash table structure, which reduces the memory overhead by 46% while ensuring high computational efficiency