Systematic replication enables normalization of high-throughput imaging assays

Gregory J. Hunt, Mark A. Dane, James E. Korkola, Laura M. Heiser, Johann A. Gagnon-Bartsch

Research output: Contribution to journalArticlepeer-review

Abstract

MOTIVATION: High-throughput fluorescent microscopy is a popular class of techniques for studying tissues and cells through automated imaging and feature extraction of hundreds to thousands of samples. Like other high-throughput assays, these approaches can suffer from unwanted noise and technical artifacts that obscure the biological signal. In this work, we consider how an experimental design incorporating multiple levels of replication enables the removal of technical artifacts from such image-based platforms. RESULTS: We develop a general approach to remove technical artifacts from high-throughput image data that leverages an experimental design with multiple levels of replication. To illustrate the methods, we consider microenvironment microarrays (MEMAs), a high-throughput platform designed to study cellular responses to microenvironmental perturbations. In application to MEMAs, our approach removes unwanted spatial artifacts and thereby enhances the biological signal. This approach has broad applicability to diverse biological assays. AVAILABILITY AND IMPLEMENTATION: Raw data are on synapse (syn2862345), analysis code is on github: gjhunt/mema_norm, a reproducible Docker image is available on dockerhub: gjhunt/mema_norm. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Original languageEnglish (US)
Pages (from-to)4934-4940
Number of pages7
JournalBioinformatics (Oxford, England)
Volume38
Issue number21
DOIs
StatePublished - Oct 31 2022

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

Fingerprint

Dive into the research topics of 'Systematic replication enables normalization of high-throughput imaging assays'. Together they form a unique fingerprint.

Cite this