Technology dictates algorithms: recent developments in read alignment

  • Mohammed Alser (Creator)
  • Jeremy Rotman (Creator)
  • Dhrithi Deshpande (Creator)
  • Kodi Taraszka (Creator)
  • Huwenbo Shi (Creator)
  • Pelin Icer Baykal (Creator)
  • Harry Taegyun Yang (Creator)
  • Victor Xue (Creator)
  • Sergey Knyazev (Creator)
  • Benjamin Singer (Creator)
  • Brunilda Balliu (Creator)
  • David Koslicki (Creator)
  • Pavel Skums (Creator)
  • Alex Zelikovsky (Creator)
  • Can Alkan (Creator)
  • Onur Mutlu (Creator)
  • Serghei Mangul (University of Southern California) (Creator)

Dataset

Description

Abstract 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.
Date made available2021
Publisherfigshare
  • Technology dictates algorithms: recent developments in read alignment

    Alser, M., Rotman, J., Deshpande, D., Taraszka, K., Shi, H., Baykal, P. I., Yang, H. T., Xue, V., Knyazev, S., Singer, B. D., Balliu, B., Koslicki, D., Skums, P., Zelikovsky, A., Alkan, C., Mutlu, O. & Mangul, S., Dec 2021, In: Genome biology. 22, 1, 249.

    Research output: Contribution to journalReview articlepeer-review

    Open Access
    49 Scopus citations

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