Generating Heterogeneous Data on Gene Trees

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.

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Publication Details

Journal
Journal of Computational Biology
Published
2025-05-09
DOI
https://doi.org/10.1089/cmb.2024.0843
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
0.00

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article

Generating Heterogeneous Data on Gene Trees

Marta Casanellas, Melissa N. Garcia, Adrià Diéguez Moscardó
Journal of Computational Biology
Bioinformatics and Genomic Networks
article

Generating Heterogeneous Data on Gene Trees

Marta Casanellas, Melissa N. Garcia, Adrià Diéguez Moscardó
article en

Abstract

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.

Journal of Computational BiologyVol. 32(6)
Centre de Recerca Matemàtica (ES), Universitat Politècnica de Catalunya (ES)
Agència de Gestió d'Ajuts Universitaris i de Recerca, Agencia Estatal de Investigación
Openalex Percentile: Top 91%
Bioinformatics and Genomic Networks
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