A general near-exact k-mer counting method with low memory consumption enablesde novoassembly of 106× human sequence data in 2.7 hours | Zendy

Christina Huan Shi | Zendy; Kevin Y. Yip | Zendy

Open Access

A general near-exact k-mer counting method with low memory consumption enablesde novoassembly of 106× human sequence data in 2.7 hours

Author(s) -

Christina Huan Shi,

Kevin Y. Yip

Publication year - 2020

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btaa890

Subject(s) - k mer , sequence (biology) , sequence assembly , noise (video) , algorithm , computer science , arithmetic , genome , mathematics , artificial intelligence , biology , genetics , gene , image (mathematics) , gene expression , transcriptome

In de novo sequence assembly, a standard pre-processing step is k-mer counting, which computes the number of occurrences of every length-k sub-sequence in the sequencing reads. Sequencing errors can produce many k-mers that do not appear in the genome, leading to the need for an excessive amount of memory during counting. This issue is particularly serious when the genome to be assembled is large, the sequencing depth is high, or when the memory available is limited.

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