Genome and metagenome comparisons based on large amounts of next-generation sequencing (NGS) data pose significant challenges for alignment-based approaches due to the huge data size and the relatively short length of the reads. Alignment-free approaches based on the counts of word patterns in NGS data do not depend on the complete genome and are generally computationally efficient. Thus, they contribute significantly to genome and metagenome comparison. Recently, novel statistical approaches have been developed for the comparison of both long and shotgun sequences. These approaches have been applied to many problems, including the comparison of gene regulatory regions, genome sequences, metagenomes, binning contigs in metagenomic data, identification of virus–host interactions, and detection of horizontal gene transfers. We provide an updated review of these applications and other related developments of word count–based approaches for alignment-free sequence analysis.
Suggested Citation: Suggested Citation
Ren, Jie and Bai, Xin and Lu, Yang Young and Tang, Kujin and Wang, Yiamen and Reinert, Gesine and Sun, Fengzhu, Alignment-Free Sequence Analysis and Applications (July 2018). Annual Review of Biomedical Data Science, Vol. 1, pp. 93-114, 2018, Available at SSRN: https://ssrn.com/abstract=3329801 or http://dx.doi.org/10.1146/annurev-biodatasci-080917-013431
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