2025/11/27 by Shawn T. Schwartz, Whitney L. E. Tsai, Elizabeth A Karan +5 · 1 voice
Agricultural and Biological Sciences · Mathematics · Biochemistry, Genetics and Molecular Biology · #Animal Behavior and Reproduction #Morphological variations and asymmetry #Retinal Development and Disorders
paper · doi:10.1101/2025.11.25.690362
openalex publication_date 2025/11/27 · openalex created_date 2025/11/28 · openalex updated_date 2026/07/14
1. Advances in digital imaging and software tools have provided increasingly accessible datasets and methods for analyzing color evolution. Despite the variety of computational packages available, most rely on color classification before running analyses. Previous methods to characterize color limit the ability to analyze large-scale image databases and are not always representative of biologically relevant color classes, which decrease the accuracy of downstream analyses. 2. Here, we present charisma, an R package designed to characterize the distribution of distinct color classes in images suitable for large-scale studies of biological organisms. Here, we demonstrate the utility of our package through an analysis of color evolution in a sample of diverse and charismatic birds, tanagers, in the subfamily Thraupinae. 3. We show that charisma can quickly and accurately classify every pixel in an image and validate these results using pre-identified, canonical color swatches. We find that charisma color classifications are consistent with those made by color-pattern experts in the field. Applying charisma to tanager color evolution, we find that charisma outputs seamlessly integrate with downstream evolutionary analyses. 4. Our results demonstrate that using charisma to manually curate and characterize colors in images provides a standardized, reliable, and reproducible framework for high-throughput color classification.