#54 Seeding methods for read alignment with Markus Schmidt - a podcast by Roman Cheplyaka

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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