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Annual Review of Biomedical Data Science

Volume 1, 2018

Alignment-Free Sequence Analysis and Applications

Abstract

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.

Keyword(s): alignment, alignment-free, horizontal gene transfer, Markov chain, metagenomics, phylogeny, sequence comparison, virus–host interaction
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/content/journals/10.1146/annurev-biodatasci-080917-013431
2018-07-20
2024-04-19
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/content/journals/10.1146/annurev-biodatasci-080917-013431
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Alignment-Free Sequence Analysis and Applications
Annual Review of Biomedical Data Science 1, 93 (2018); https://doi.org/10.1146/annurev-biodatasci-080917-013431
/content/journals/10.1146/annurev-biodatasci-080917-013431
/content/journals/10.1146/annurev-biodatasci-080917-013431
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