Our latest paper in Genome Biology is out

Our latest paper in Genome Biology reviews the developments in read alignment algorithms since 1988 until now.  We investigate how the development of read alignment algorithms is impacted by changes in sequencing technologies, such as read length, throughput, and sequencing error rates. 

Mohammed Alser, Jeremy Rotman, Kodi Taraszka, Huwenbo Shi, Pelin Icer Baykal, Harry Taegyun Yang, Victor Xue, Sergey Knyazev, Benjamin D. Singer, Brunilda Balliu, David Koslicki, Pavel Skums, Alex Zelikovsky, Can Alkan, Onur Mutlu, Serghei Mangul, “Technology dictates algorithms: Recent developments in read alignment”, Genome Biology , August 2021.
[arXiv preprint]
[Source Code and Data]

Aligning sequencing reads onto a reference is an essential step of the majority of genomic analysis pipelines. Computational algorithms for read alignment have evolved in accordance with technological advances, leading to today’s diverse array of alignment methods. We provide a systematic survey of algorithmic foundations and methodologies across 107 alignment methods, for both short and long reads. We provide a rigorous experimental evaluation of 11 read aligners to demonstrate the effect of these underlying algorithms on speed and efficiency of read alignment. We discuss how general alignment algorithms have been tailored to the specific needs of various domains in biology.

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