Benchmarking of human Y-chromosomal haplogroup classifiers with whole-genome and whole-exome sequence data

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Abstract

In anthropological, medical, and forensic studies, the nonrecombinant region of the human Y chromosome (NRY) enables accurate reconstruction of pedigree relationships and retrieval of ancestral information. Using high-throughput sequencing (HTS) data, we present a benchmarking analysis of command-line tools for NRY haplogroup classification. The evaluation was performed using paired Illumina data from whole-genome sequencing (WGS) and whole-exome sequencing (WES) experiments from 50 unrelated donors. Additionally, as a validation, we also used paired WGS/WES datasets of 54 individuals from the 1000 Genomes Project. Finally, we evaluated the tools on data from third-generation HTS obtained from a subset of donors and one reference sample. Our results show that WES, despite typically offering less genealogical resolution than WGS, is an effective method for determining the NRY haplogroup. Y-LineageTracker and Yleaf showed the highest accuracy for WGS data, classifying precisely 98% and 96% of the samples, respectively. Yleaf outperforms all benchmarked tools in the WES data, classifying approximately 90% of the samples. Yleaf, Y-LineageTracker, and pathPhynder can correctly classify most samples (88%) sequenced with third-generation HTS. As a result, Yleaf provides the best performance for applications that use WGS and WES. Overall, our study offers researchers with a guide that allows them to select the most appropriate tool to analyze the NRY region using both second-and third generation HTS data.

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García-Olivares, V., Muñoz-Barrera, A., Rubio-Rodríguez, L. A., Jáspez, D., Díaz-de Usera, A., Iñigo-Campos, A., Veeramah, K. R., Alonso, S., Thomas, M. G., Lorenzo-Salazar, J. M., González-Montelongo, R., & Flores, C. (2023). Benchmarking of human Y-chromosomal haplogroup classifiers with whole-genome and whole-exome sequence data. Computational and Structural Biotechnology Journal, 21, 4613–4618. https://doi.org/10.1016/j.csbj.2023.09.012

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Except where otherwise noted, this item's license is described as Attribution 4.0 International