Seeding methods for read alignment with Markus Schmidt — the bioinformatics chat, a podcast about bioinformatics

Seeding methods for read alignment with Markus Schmidt (#54)

December 16, 2020

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.

Download MP3

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)

Music: Eric Skiff — Come and Find Me (modified, licensed under CC BY 4.0).

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