Seq-Gen. Sequence-Generator: An application for the Monte Carlo simulation of molecular sequence evolution along phylogenetic trees. Seq-Gen is a program that will simulate the evolution of nucleotide or amino acid sequences along a phylogeny, using common models of the substitution process. A range of models of molecular evolution are implemented including the general reversible model. Nucleotide/Amino acid frequencies and other parameters of the model may be given and site-specific rate heterogeneity may also be incorporated in a number of ways. Any number of trees may be read in and the program will produce any number of data sets for each tree. Thus large sets of replicate simulations can be easily created. It has been designed to be a general purpose simulator that incorporates most of the commonly used (and computationally tractable) models of molecular sequence evolution. The paper cited above contains details of the algorithm and a short discussion about the uses of Seq-Gen.

References in zbMATH (referenced in 33 articles )

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  1. Richards, A.; Kubatko, L.: Site pattern probabilities under the multispecies coalescent and a relaxed molecular clock: theory and applications (2022)
  2. Richards, Andrew; Kubatko, Laura: Bayesian-weighted triplet and quartet methods for species tree inference (2021)
  3. Paeng, Seong-Hun; Park, Chunjae: Spectral method for reconstructing phylogenetic tree (2019)
  4. Elworth, Ryan A. Leo; Allen, Chabrielle; Benedict, Travis; Dulworth, Peter; Nakhleh, Luay: (D_\textGEN): a test statistic for detection of general introgression scenarios (2018)
  5. DeGiorgio, Michael; Rosenberg, Noah A.: Consistency and inconsistency of consensus methods for inferring species trees from gene trees in the presence of ancestral population structure (2016)
  6. Mykowiecka, Agnieszka; Górecki, Pawel: Bootstrapping algorithms for gene duplication and speciation events (2016)
  7. Jhwueng, Dwueng-Chwuan; Huzurbazar, Snehalata; O’Meara, Brian C.; Liu, Liang: Investigating the performance of AIC in selecting phylogenetic models (2014)
  8. Loza-Reyes, E.; Hurn, M. A.; Robinson, A.: Classification of molecular sequence data using Bayesian phylogenetic mixture models (2014)
  9. Prangle, Dennis; Fearnhead, Paul; Cox, Murray P.; Biggs, Patrick J.; French, Nigel P.: Semi-automatic selection of summary statistics for ABC model choice (2014)
  10. Paradis, Emmanuel: Analysis of phylogenetics and evolution with R (2012)
  11. Pratas, Frederico; Trancoso, Pedro; Sousa, Leonel; Stamatakis, Alexandros; Shi, Guochun; Kindratenko, Volodymyr: Fine-grain parallelism using multi-core, cell/BE, and GPU systems (2012) ioport
  12. Radice, Rosalba: A Bayesian approach to modelling reticulation events with application to the ribosomal protein gene rps11 of flowering plants (2012)
  13. Brinkmeyer, Malte; Griebel, Thasso; Böcker, Sebastian: Polynomial supertree methods revisited (2011) ioport
  14. Carbone, A.; Dib, L.: Co-evolution and information signals in biological sequences (2011)
  15. Darlu, Pierre; Guénoche, Alain: TreeOfTrees method to evaluate the congruence between gene trees (2011)
  16. Gilks, Walter R.; Nye, Tom M. W.; Lio, Pietro: A variance-components model for distance-matrix phylogenetic reconstruction (2011)
  17. Nye, Tom M. W.: Principal components analysis in the space of phylogenetic trees (2011)
  18. Hao, Weilong: Orgconv: detection of gene conversion using consensus sequences and its application in plant mitochondrial and chloroplast homologs (2010) ioport
  19. Ionescu, Tudor B.; Polaillon, Géraldine; Boulanger, Frédéric: Minimum tree cost quartet puzzling (2010)
  20. Elias, Isaac; Lagergren, Jens: Fast neighbor joining (2009)

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