Generating heterogeneous data on gene trees
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | |
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| _version_ | 1866913803112808448 |
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| author | Garcia, Martí Cortada Moscardó, Adrià Diéguez Casanellas, Marta |
| author_facet | Garcia, Martí Cortada Moscardó, Adrià Diéguez Casanellas, Marta |
| contents | We introduce GenPhylo, a Python module that simulates nucleotide sequence data along a phylogeny avoiding the restriction of continuous-time Markov processes. GenPhylo uses directly a general Markov model and therefore naturally incorporates heterogeneity across lineages. We solve the challenge of generating transition matrices with a pre-given expected number of substitutions (the branch length information) by providing an algorithm that can be incorporated in other simulation software. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_15855 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Generating heterogeneous data on gene trees Garcia, Martí Cortada Moscardó, Adrià Diéguez Casanellas, Marta Populations and Evolution 92-10 We introduce GenPhylo, a Python module that simulates nucleotide sequence data along a phylogeny avoiding the restriction of continuous-time Markov processes. GenPhylo uses directly a general Markov model and therefore naturally incorporates heterogeneity across lineages. We solve the challenge of generating transition matrices with a pre-given expected number of substitutions (the branch length information) by providing an algorithm that can be incorporated in other simulation software. |
| title | Generating heterogeneous data on gene trees |
| topic | Populations and Evolution 92-10 |
| url | https://arxiv.org/abs/2504.15855 |