A Structural Analysis of Population Graphs
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866915445951430656 |
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| author | Ayers, Kimberly Kooiker, Maxwell |
| author_facet | Ayers, Kimberly Kooiker, Maxwell |
| contents | The format of graphing algorithms for genomic data has been a debate in recent biotechnology. In this paper, we discuss the construction of population graphs using said genomic data. We first examine the GENPOFAD distance measurement, developed by Joly et. al., and prove that this constitutes a metric function. We develop an algorithm to construct graphs to visualize the relationships between individuals in a population. We then provide a statistical analysis of these simulated population graphs, and show that they are distinct from randomly generated graphs, and also show differences from small-world graphs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_10058 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Structural Analysis of Population Graphs Ayers, Kimberly Kooiker, Maxwell Quantitative Methods 05C90 The format of graphing algorithms for genomic data has been a debate in recent biotechnology. In this paper, we discuss the construction of population graphs using said genomic data. We first examine the GENPOFAD distance measurement, developed by Joly et. al., and prove that this constitutes a metric function. We develop an algorithm to construct graphs to visualize the relationships between individuals in a population. We then provide a statistical analysis of these simulated population graphs, and show that they are distinct from randomly generated graphs, and also show differences from small-world graphs. |
| title | A Structural Analysis of Population Graphs |
| topic | Quantitative Methods 05C90 |
| url | https://arxiv.org/abs/2508.10058 |