KCMBT: a k-mer Counter based on Multiple Burst Trees.

ABSTRACT:

Motivation

A massive number of bioinformatics applications require counting of k-length substrings in genetically important long strings. A k-mer counter generates the frequencies of each k-length substring in genome sequences. Genome assembly, repeat detection, multiple sequence alignment, error detection and many other related applications use a k-mer counter as a building block. Very fast and efficient algorithms are necessary to count k-mers in large data sets to be useful in such applications.

Results

We propose a novel trie-based algorithm for this k-mer counting problem. We compare our devised algorithm k-mer Counter based on Multiple Burst Trees (KCMBT) with available all well-known algorithms. Our experimental results show that KCMBT is around 30% faster than the pr

SUBMITTER: Mamun AA 

PROVIDER: S-EPMC5939891 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature