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Comparative assessment of alignment algorithms for NGS data: features, considerations, implementations, and future. (English) Zbl 1457.68339

Elloumi, Mourad (ed.), Algorithms for next-generation sequencing data. Techniques, approaches, and applications. Cham: Springer. 187-202 (2017).
Summary: Due to the nature of massively parallel sequencing use of shorter reads, the algorithms developed for alignment have been crucial to the widespread adoption of Next-Generation Sequencing (NGS). There has been great progress in the development of a variety of different algorithms for different purposes. Researchers are now able to use sensitive and efficient alignment algorithms for a wide variety of applications, including genome-wide variation studies, quantitative RNA-seq expression analyses, the study of secondary RNA structure, microRNA discovery, identification of protein-binding sites using ChIP-sequencing, recognizing histone modification patterns for epigenetic studies, simultaneous alignment of multiple genomes for comparative genomics, and the assembly of de novo genomes and transcriptomes. In clinical settings, alignment to reference genomes has led to rapid pathogen discovery, identification of causative mutations for rare genetic diseases, detection of chromosomal abnormalities in tumor genomes, and many other advances which similarly depend on rapid and cost-effective genome-wide sequencing.
For the entire collection see [Zbl 1383.68005].

MSC:

68W32 Algorithms on strings
92D10 Genetics and epigenetics
92D20 Protein sequences, DNA sequences
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