9. Comparative Assessment of Alignment Algorithms for NGS Data: Features, Considerations, Implementations, and Future

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 [1], quantitative RNA-seq expression analyses [2], the study of secondary RNA structure [3], microRNA discovery [4], identification of protein-binding sites using ChIP-sequencing [5], recognizing histone modification patterns for epigenetic studies [6], simultaneous alignment of multiple genomes for comparative genomics [7], and the assembly of de novo genomes and transcriptomes [8]. In clinical settings, alignment to reference genomes has led to rapid pathogen discovery [9], identification of causative mutations for rare genetic diseases [10–12], detection of chromosomal abnormalities in tumor genomes [13], and many other advances which similarly depend on rapid and cost-effective genome-wide sequencing.