the bioinformatics chat

#54 Seeding methods for read alignment with Markus Schmidt

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In this episode, Markus Schmidt explains how seeding in read alignment works.

We define and compare k-mers, minimizers, MEMs, SMEMs, and maximal spanning seeds.
Markus also presents his recent work on computing variable-sized seeds (MEMs,
SMEMs, and maximal spanning seeds) from fixed-sized seeds (k-mers and
minimizers) and his Modular Aligner.

Links:

  • A performant bridge between fixed-size and variable-size seeding
    • (Arne Kutzner, Pok-Son Kim, Markus Schmidt)
  • MA the Modular Aligner
  • Calibrating Seed-Based Heuristics to Map Short Reads With Sesame
    • (Guillaume J. Filion, Ruggero Cortini, Eduard Zorita) — another
    interesting recent work on seeding methods (though we didn’t get to discuss
    it in this episode)

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