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Reproducible evaluation of transposable element detectors with McClintock 2 guides accurate inference of Ty insertion patterns in yeast.

Jingxuan ChenPreston J BastingShunhua HanDavid J GarfinkelCasey M Bergman
Published in: Mobile DNA (2023)
McClintock ( https://github.com/bergmanlab/mcclintock/ ) provides a user-friendly pipeline for the identification of TEs in short-read WGS data using multiple TE detectors, which should benefit researchers studying TE insertion variation in a wide range of different organisms. Application of the improved McClintock system to simulated and empirical yeast genome data reveals best-in-class methods and novel biological insights for one of the most widely-studied model eukaryotes and provides a paradigm for evaluating and selecting non-reference TE detectors in other species.
Keyphrases
  • electronic health record
  • big data
  • saccharomyces cerevisiae
  • high resolution
  • single cell
  • cell wall
  • data analysis
  • machine learning
  • mass spectrometry
  • low cost
  • multidrug resistant