Date of Award
2024
Degree Type
Thesis
Degree Name
Master of Science in Biological and Environmental Sciences (MSBES)
Department
Biological Sciences
First Advisor
Jon Puritz
Abstract
Restriction site-associated DNA sequencing (RADseq) has emerged as an effective tool to survey natural populations for genetic structure and diversity. When undergoing bioinformatic processing, markers generated from RADseq are aligned to a reference sequence prior to variant calling, which may introduce reference bias in downstream analysis. Here, the benefits of building a variant graph are evaluated based on RADseq markers to reduce reference bias, improve variant calling accuracy, and estimate fixation index (FST) and nucleotide diversity (π). Results indicate graph-based alignments improve SNP detection and provide more accurate estimates of per-site FST across a range of demographic conditions. No differences were found in estimates of nucleotide diversity based on simulated data with graph-based methods. On the contrary, in real data, graph-based methods returned greater amounts of genetic variation and higher estimates of average FST and π. This study concludes that graph-based reference construction and alignment improves the accuracy of biological inference drawn from RADseq data.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.
Recommended Citation
Barrett, Gabriel A., "VARIANT GRAPHS IMPROVE ACCURACY OF DOWNSTREAM ANALYSIS IN RESTRICTION SITE-ASSOCIATED SEQUENCING" (2024). Open Access Master's Theses. Paper 2509.
https://digitalcommons.uri.edu/theses/2509