loading page

High-Frequency K-mer Counting at Low Memory Footprint
  • +1
  • Li Mocheng,
  • Yang Liu,
  • Nong Xiao,
  • Zhiguang Chen
Li Mocheng
National University of Defense Technology College of Computers

Corresponding Author:lmc@nudt.edu.cn

Author Profile
Yang Liu
Author Profile
Nong Xiao
National University of Defense Technology
Author Profile
Zhiguang Chen
Sun Yat-sen University School of Data and Computer Science
Author Profile


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.
22 Aug 2022Submitted to Electronics Letters
23 Aug 2022Submission Checks Completed
23 Aug 2022Assigned to Editor
12 Sep 2022Reviewer(s) Assigned
08 Oct 2022Review(s) Completed, Editorial Evaluation Pending
11 Oct 2022Editorial Decision: Revise Minor
12 Oct 20221st Revision Received
13 Oct 2022Submission Checks Completed
13 Oct 2022Assigned to Editor
13 Oct 2022Review(s) Completed, Editorial Evaluation Pending
13 Oct 2022Editorial Decision: Accept
Dec 2022Published in Electronics Letters volume 58 issue 25 on pages 940-942. 10.1049/ell2.12661