Marigold: a machine learning-based web app for zebrafish pose tracking.

Journal: BMC bioinformatics
PMID: 39875867

Abstract

BACKGROUND: High-throughput behavioral analysis is important for drug discovery, toxicological studies, and the modeling of neurological disorders such as autism and epilepsy. Zebrafish embryos and larvae are ideal for such applications because they are spawned in large clutches, develop rapidly, feature a relatively simple nervous system, and have orthologs to many human disease genes. However, existing software for video-based behavioral analysis can be incompatible with recordings that contain dynamic backgrounds or foreign objects, lack support for multiwell formats, require expensive hardware, and/or demand considerable programming expertise. Here, we introduce Marigold, a free and open source web app for high-throughput behavioral analysis of embryonic and larval zebrafish.

Authors

  • Gregory Teicher
    Biology Department, University of Massachusetts Amherst, Amherst, MA, USA. gteicher@umass.edu.
  • R Madison Riffe
    Biology Department, University of Massachusetts Amherst, Amherst, MA, USA.
  • Wayne Barnaby
    Biology Department, University of Massachusetts Amherst, Amherst, MA, USA.
  • Gabrielle Martin
    Biology Department, University of Massachusetts Amherst, Amherst, MA, USA.
  • Benjamin E Clayton
    Biology Department, University of Massachusetts Amherst, Amherst, MA, USA.
  • Josef G Trapani
    Neuroscience and Behavior Graduate Program, University of Massachusetts Amherst, Amherst, MA, USA.
  • Gerald B Downes
    Biology Department, University of Massachusetts Amherst, Amherst, MA, USA. gbdownes@umass.edu.

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