bioRxivCell BiologyPreprint
AutoMorFi: Automated Whole-image Morphometry in Fiji/ImageJ for Diverse Analyses and Discoveries
Ouzéna BouadiiD, Chenkai Yao, Jason ZengiD, Danielle Beason, Nyomi Inda, Zoe Malone, Jonathan Yoshihara, Amritha Vinayak Manjally, Clifton Johnson, Jonathan D. CherryiD, Chin‐Yi CheniD, Tzu-Chieh HuangiD, B. PopovićiD, Maria HenleyiD, Guangmei LiuiD, Hannah E. AichelmaniD, Sarah W. DaviesiD, Yuan TianiD, Heng‐Ye ManiD, Thomas D. GilmoreiD, Elif Naz OzseniD, Kristen Harder, Peter WalentekiD, Elizabeth K. KharitonovaiD, Ella ZeldichiD, , Tuan Leng TayiD
Abstract
Running on the highly popular and accessible ImageJ/Fiji platform for biological image analysis, we have established AutoMorFi as a streamlined interface for automated whole-image morphometric analysis that generates at least 47 measurements per cell or object in under 1 minute. We performed multiple validated cluster and principal component analyses on nonredundant morphometric parameters derived from AutoMorFi for various cell types, objects, and organisms. We used images of rodent macrophages, human postmortem brain tissues from multiple sclerosis (MS) and Alzheimers disease (AD) patients, iPSC/animal models for Downs syndrome and autism spectrum disorder (ASD), and organisms such as sea anemone and corals. AutoMorFis adaptability extends across diverse imaging modalities including brightfield, confocal, or widefield fluorescence microscopy as well as underwater photography. Due to its unlimited and unbiased sampling across any image and high potential for modification and customization, using AutoMorFi has led to the discovery of new distinguishing features in previously studied cell types and organisms as well as the development of rapid diagnostic approaches. AutoMorFi represents a transformative tool that will accelerate morphometric analysis and offer broad relevance in biological studies.
- organism: human
- organism: mouse
- organism: rat
- assay: fluorescence / live-cell microscopy
- assay: imaging
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- approach: experimental assay
- Citations
- 2
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