DeBoni03/BSc-Thesis-R — reverse-engineered prompt

Build me a reproducible R analysis project for my bachelor thesis about visual cortex cell measurements in different mammals.

I want to start from the synthetic dataset in the repo, clean the messy output from automated cell detection, handle obvious artifacts and outliers, scale the morphometric variables, then run several unsupervised clustering approaches. Please include K Means, hierarchical clustering with dendrograms, and DBSCAN, and make clear plots so I can compare what each method is finding.

After that, add a simple evaluation section that calculates cluster quality metrics and mismatch comparisons, so the results are not just based on looking at plots. Also include PERMANOVA style statistical testing to check whether the groups differ by species or phylogenetic relationships if those columns are available.

Please organize it so I can run the workflow from start to finish, save important figures and tables, and understand each step from comments in the code. Look up current R package docs online if needed.