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Biostatistical analysis of quantitative immunofluorescence microscopy images
Author(s) -
GILES C.,
ALBRECHT M.A.,
LAM V.,
TAKECHI R.,
MAMO J.C.
Publication year - 2016
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/jmi.12446
Subject(s) - context (archaeology) , workflow , statistical power , replication (statistics) , computer science , sample (material) , immunofluorescence , microscopy , indirect immunofluorescence , sample size determination , statistical analysis , biological system , artificial intelligence , statistics , optics , biology , mathematics , chemistry , physics , paleontology , chromatography , database , genetics , antigen , antibody , immunology
Summary 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.