lcUMAPtSNE: Use of non-linear dimensionality reduction techniques with genotype likelihoods

This repository contains genotype likelihood estimations derived from open-access whole-genome re-sequencing datasets of the scimitar-horned oryx (SO). The dataset was downsampled to exhibit varying coverage levels, including 6x, 2x, and 0.5x. Genotype likelihoods were estimated, followed by the calculation of principal components and subsequent application of UMAP and t-SNE with varying parameter settings, as detailed in Uzel et al. (2025). All intermediate and input files generated from these datasets are available here. Genotype likelihood estimations are provided in the formats '.beagle.gz' and '.mafs.gz'. Additionally, the repository contains the input covariance matrix ('.cov') for each dataset and the population information file for each group, which were employed in the non-linear dimensionality reduction steps described in Uzel et al. (2025).

Raw data resources

All raw sequencing data we used in this study were downloaded from public databases, and no new data were generated.

The scimitar-horned oryx data were acquired from NCBI BioProject PRJEB37295  (Humble et al. 2023)

Code/Software

All bioinformatic codes used for generating the results and guidelines presented in Çilingir et al. (2024) are available at https://github.com/fgcilingir/lcUMAPtSNE.

Literature Cited

Humble, E., Stoffel, M. A., Dicks, K., Ball, A. D., Gooley, R. M., Chuven, J., Pusey, R., Remeithi, M. A., Koepfli, K.-P., Pukazhenthi, B., Senn, H., & Ogden, R. (2023). Conservation management strategy impacts inbreeding and mutation load in scimitar-horned oryx. Proceedings of the National Academy of Sciences of the United States of America, 120(18), e2210756120.Uzel, K., Grossen, C., Çilingir, F.G. (2025) lcUMAPtSNE: Use of non-linear dimensionality reduction techniques with genotype likelihoods. bioRxiv, https://doi.org/10.1101/2024.04.01.587545.