title: Biostatistical analysis of quantitative immunofluorescence microscopy images.
abstract: Semiquantitative immunofluorescence microscopy has become a key methodology in biomedical research. Typical statistical workflows are considered in the context of avoiding pseudo-replication and marginalising experimental error. However, immunofluorescence microscopy naturally generates hierarchically structured data that can be leveraged to improve statistical power and enrich biological interpretation. Herein, we describe a robust distribution fitting procedure and compare several statistical tests, outlining their potential advantages/disadvantages in the context of biological interpretation. Further, we describe tractable procedures for power analysis that incorporates the underlying distribution, sample size and number of images captured per sample. The procedures outlined have significant potential for increasing understanding of biological processes and decreasing both ethical and financial burden through experimental optimization.
authors.affiliation: Curtin Health Innovation Research Institute, Curtin University, Western Australia, Australia.|Faculty of Health Sciences, School of Public Health, Curtin University, Western Australia, Australia.
authors.forename: C
authors.initials: C
authors.lastname: Giles
authors.affiliation: Curtin Health Innovation Research Institute, Curtin University, Western Australia, Australia.|Faculty of Health Sciences, School of Public Health, Curtin University, Western Australia, Australia.|Maryland Psychiatric Research Center, School of Medicine, University of Maryland, College Park, Maryland, U.S.A.
authors.forename: M A
authors.initials: MA
authors.lastname: Albrecht
authors.affiliation: Curtin Health Innovation Research Institute, Curtin University, Western Australia, Australia.|Faculty of Health Sciences, School of Public Health, Curtin University, Western Australia, Australia.
authors.forename: V
authors.initials: V
authors.lastname: Lam
authors.affiliation: Curtin Health Innovation Research Institute, Curtin University, Western Australia, Australia.|Faculty of Health Sciences, School of Public Health, Curtin University, Western Australia, Australia.
authors.forename: R
authors.initials: R
authors.lastname: Takechi
authors.affiliation: Curtin Health Innovation Research Institute, Curtin University, Western Australia, Australia.|Faculty of Health Sciences, School of Public Health, Curtin University, Western Australia, Australia.
authors.forename: J C
authors.initials: JC
authors.lastname: Mamo
mesh_terms: D000818:Animals; D056808:Biostatistics; D005260:Female; D006801:Humans; D016013:Likelihood Functions; D008856:Microscopy, Fluorescence / Q000379:methods*; D051381:Rats; D017207:Rats, Sprague-Dawley
keywords: Biological variation; hierarchical analysis; immunofluorescence microscopy; statistics