DOI: 10.5281/zenodo.4289251
title: Real and simulated cross-sectional and longitudinal images of hair

description: This is the dataset containing simulated and real data used in the analyses for the paper "<em>High-throughput phenotyping methods for quantifying hair fiber morphology" </em>and is part of the<em> Hair Phenotyping Methods Project </em>run by Tina Lasisi. The data can be analyzed with the <em>fibermorph</em> Python package available on PyPi and Github. This repository has 2 datasets with 2 different types of data: Simulated hair data Cross-sectional data (simulated ellipses) Curvature data (simulated arcs) Real hair data Cross-sectional data (micrographs of hair fiber cross-sections) Curvature data (longitudinal images of hair fiber fragments) Visit the <em>Hair Phenotyping Methods Project</em> website for the most up to date information about this project and any updates relevant to this dataset. ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- <strong>Details</strong> <strong>Simulated data</strong> Cross-sectional data These ellipses were simulated with a python script developed as part of <em>fibemorph</em>. A version of that code that doesn't require the original Python package has been made available with the dataset (sim_ellipse.py). The script simulates a single cross-section per image. Each image has a width of 5200px and a height of 3900 with a resolution set to 4.25 px/micron. Curvature data An R script used for curvature simulation, written by Arslan Zaidi, has also been made available with this dataset (sim_curvature.R). The script generates 25 arcs per image. We used a set length of 1.57. Each image has a resolution of 132 px/mm. Please note that due to the use of random generations, it is not possible to recreate the exact same datasets that are saved here. <strong>Real data</strong> The real data images are very large files and have been split into multiple zip files. Please check the specific instructions for unzipping split zip files for your OS. The images are from hair samples collected by the Shriver Lab at Penn State. There were a total of 192 samples, although not all images made it past quality control so certain IDs may have cross-section images but not curvature images or vice versa. The images have been de-identified and the hair samples for these individuals were collected with informed consent and ethical approval by The Pennsylvania State University Institutional Review Board (#44929 and #45727). Cross-sectional data We developed and used this protocol to embed, section, and image the hairs. We embedded 6 samples per person and took images of both sides of the sectioned sample (A and B). These should be mirror images of each other. Curvature data We developed and used this protocol to cut, wash, and image the hairs. We used 3-5 hairs per person where available. A number of samples did not have enough hair for this, so the images contain fewer fragments. We have made these available for full transparency although we filtered them from our analyses downstream. Please see the GitHub repository for additional related participant data we used in our analyses.
description: This research was funded by the National Science Foundation (No. 1847845) and the Wenner-Gren Foundation (Gr. 9911).