1. High-throughput phenotyping methods for quantifying hair fiber morphology.
- Author
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Lasisi T, Zaidi AA, Webster TH, Stephens NB, Routch K, Jablonski NG, and Shriver MD
- Subjects
- Cross-Sectional Studies, Humans, Hair anatomy & histology, Image Processing, Computer-Assisted, Scalp
- Abstract
Quantifying the continuous variation in human scalp hair morphology is of interest to anthropologists, geneticists, dermatologists and forensic scientists, but existing methods for studying hair form are time-consuming and not widely used. Here, we present a high-throughput sample preparation protocol for the imaging of both longitudinal (curvature) and cross-sectional scalp hair morphology. Additionally, we describe and validate a new Python package designed to process longitudinal and cross-sectional hair images, segment them, and provide measurements of interest. Lastly, we apply our methods to an admixed African-European sample (n = 140), demonstrating the benefit of quantifying hair morphology over classification, and providing evidence that the relationship between cross-sectional morphology and curvature may be an artefact of population stratification rather than a causal link.
- Published
- 2021
- Full Text
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