#54 Seeding methods for read alignment with Markus Schmidt
Dec 16, 2020•1 hr 1 min•Ep. 54
Listen to this episode in Metacast mobile app
Don't just listen to podcasts. Learn from them with transcripts, summaries, and chapters for every episode. Skim, search, and bookmark insights. Learn more
Episode description
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)
If you enjoyed this episode, please consider supporting the podcast on Patreon.
For the best experience, listen in Metacast app for iOS or Android
Open in Metacast