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.
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
50\% while ensuring high computational efficiency.
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