Annot: A Django-based sample, reagent, and experiment metadata tracking system

Elmar Bucher, Cheryl J. Claunch, Derrick Hee, Rebecca L. Smith, Kaylyn Devlin, Wallace Thompson, James E. Korkola, Laura M. Heiser

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Background: In biological experiments, comprehensive experimental metadata tracking-which comprises experiment, reagent, and protocol annotation with controlled vocabulary from established ontologies-remains a challenge, especially when the experiment involves multiple laboratory scientists who execute different steps of the protocol. Here we describe Annot, a novel web application designed to provide a flexible solution for this task. Results: Annot enforces the use of controlled vocabulary for sample and reagent annotation while enabling robust investigation, study, and protocol tracking. The cornerstone of Annot's implementation is a json syntax-compatible file format, which can capture detailed metadata for all aspects of complex biological experiments. Data stored in this json file format can easily be ported into spreadsheet or data frame files that can be loaded into R ( or Pandas, Python's data analysis library ( Annot is implemented in Python3 and utilizes the Django web framework, Postgresql, Nginx, and Debian. It is deployed via Docker and supports all major browsers. Conclusions: Annot offers a robust solution to annotate samples, reagents, and experimental protocols for established assays where multiple laboratory scientists are involved. Further, it provides a framework to store and retrieve metadata for data analysis and integration, and therefore ensures that data generated in different experiments can be integrated and jointly analyzed. This type of solution to metadata tracking can enhance the utility of large-scale datasets, which we demonstrate here with a large-scale microenvironment microarray study.

Original languageEnglish (US)
Article number542
JournalBMC bioinformatics
Issue number1
StatePublished - Nov 1 2019


  • Annotamentum
  • Annotation
  • Controlled vocabulary
  • Metadata
  • Software

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics


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