anova-phylogenetique-projet-msv/references.bib

@unpublished{bastideContinuousTraitEvolution,
  title = {Continuous {{Trait Evolution}}},
  author = {Bastide, Paul and Clavel, Julien},
  langid = {english},
  file = {/home/polarolouis/Zotero/storage/VSU34XGF/Bastide et Clavel - Continuous Trait Evolution.pdf}
}

@inbook{bastideModelesEvolutionCaracteres2022,
  title = {Modèles d’évolution de caractères continus},
  booktitle = {Modèles et méthodes pour l’évolution biologique},
  author = {Bastide, Paul and Mariadassou, Mahendra and Robin, Stéphane},
  date = {2022-07},
  pages = {47--85},
  publisher = {ISTE Group},
  doi = {10.51926/ISTE.9069.ch3},
  url = {https://www.istegroup.com/fr/produit/modeles-et-methodes-pour-levolution-biologique/?/47495},
  urldate = {2023-11-14},
  abstract = {On s'intéresse ici à la probabilité de passer d'un état A à un état B mais dans le cas où le caractère d'intérêt est un trait quantitatif comme la taille ou le poids. Les modèles utilisés diffèrent du cas discrets et dérivent principalement du mouvement brownien. Ce chapitre présente les principaux modèles d'évolution de traits quantitatifs ainsi que les méthodes permettant de les appliquer dans le contexte évolutif.},
  bookauthor = {Didier, Gilles and Guindon, Stéphane},
  isbn = {978-1-78948-069-6},
  langid = {french},
  file = {/home/polarolouis/Zotero/storage/D7TPTKWK/Bastide et al. - 2022 - Modèles d’évolution de caractères continus.pdf}
}

@article{bastidePhylogeneticFrameworkSimulate2023,
  title = {A {{Phylogenetic Framework}} to {{Simulate Synthetic Interspecies RNA-Seq Data}}},
  author = {Bastide, Paul and Soneson, Charlotte and Stern, David B and Lespinet, Olivier and Gallopin, Mélina},
  date = {2023-01-01},
  journaltitle = {Molecular Biology and Evolution},
  volume = {40},
  number = {1},
  pages = {msac269},
  issn = {1537-1719},
  doi = {10.1093/molbev/msac269},
  url = {https://doi.org/10.1093/molbev/msac269},
  urldate = {2023-11-20},
  abstract = {Interspecies RNA-Seq datasets are increasingly common, and have the potential to answer new questions about the evolution of gene expression. Single-species differential expression analysis is now a well-studied problem that benefits from sound statistical methods. Extensive reviews on biological or synthetic datasets have provided the community with a clear picture on the relative performances of the available methods in various settings. However, synthetic dataset simulation tools are still missing in the interspecies gene expression context. In this work, we develop and implement a new simulation framework. This tool builds on both the RNA-Seq and the phylogenetic comparative methods literatures to generate realistic count datasets, while taking into account the phylogenetic relationships between the samples. We illustrate the usefulness of this new framework through a targeted simulation study, that reproduces the features of a recently published dataset, containing gene expression data in adult eye tissue across blind and sighted freshwater crayfish species. Using our simulated datasets, we perform a fair comparison of several approaches used for differential expression analysis. This benchmark reveals some of the strengths and weaknesses of both the classical and phylogenetic approaches for interspecies differential expression analysis, and allows for a reanalysis of the crayfish dataset. The tool has been integrated in the R package compcodeR, freely available on Bioconductor.},
  file = {/home/polarolouis/Zotero/storage/8M5PDAVV/Bastide et al. - 2023 - A Phylogenetic Framework to Simulate Synthetic Int.pdf}
}

@book{belModeleLineaireSes,
  title = {Le Modèle Linéaire et ses Extensions},
  author = {Bel, L and family=Daudin, given=JJ, given-i=JJ and Etienne, M and Lebarbier, E and Mary-Huard, T and Robin, S and Vuillet, C},
  langid = {french},
  file = {/home/polarolouis/Zotero/storage/M9LQ4D3S/Bel et al. - Le Modèle Linéaire et ses Extensions.pdf}
}

@online{BgeeGeneExpression,
  title = {Bgee: Gene Expression Data in Animals},
  shorttitle = {Bgee},
  url = {https://www.bgee.org/},
  urldate = {2023-11-20},
  abstract = {Bgee is a database for retrieval and comparison of gene expression patterns across multiple animal species. It provides an intuitive answer to the question -where is a gene expressed?- and supports research in cancer and agriculture as well as evolutionary biology.},
  langid = {english},
  file = {/home/polarolouis/Zotero/storage/HLRP5KL6/www.bgee.org.html}
}

@article{chenQuantitativeFrameworkCharacterizing2019,
  title = {A Quantitative Framework for Characterizing the Evolutionary History of Mammalian Gene Expression},
  author = {Chen, Jenny and Swofford, Ross and Johnson, Jeremy and Cummings, Beryl B. and Rogel, Noga and Lindblad-Toh, Kerstin and Haerty, Wilfried and family=Palma, given=Federica, prefix=di, useprefix=false and Regev, Aviv},
  date = {2019-01},
  journaltitle = {Genome Res},
  volume = {29},
  number = {1},
  eprint = {30552105},
  eprinttype = {pmid},
  pages = {53--63},
  issn = {1549-5469},
  doi = {10.1101/gr.237636.118},
  abstract = {The evolutionary history of a gene helps predict its function and relationship to phenotypic traits. Although sequence conservation is commonly used to decipher gene function and assess medical relevance, methods for functional inference from comparative expression data are lacking. Here, we use RNA-seq across seven tissues from 17 mammalian species to show that expression evolution across mammals is accurately modeled by the Ornstein-Uhlenbeck process, a commonly proposed model of continuous trait evolution. We apply this model to identify expression pathways under neutral, stabilizing, and directional selection. We further demonstrate novel applications of this model to quantify the extent of stabilizing selection on a gene's expression, parameterize the distribution of each gene's optimal expression level, and detect deleterious expression levels in expression data from individual patients. Our work provides a statistical framework for interpreting expression data across species and in disease.},
  langid = {english},
  pmcid = {PMC6314168},
  keywords = {Animals,Dogs,Evolution Molecular,Gene Expression Regulation,Models Genetic,Rabbits},
  file = {/home/polarolouis/Zotero/storage/EISI6AFB/gr.237636.118.pdf.pdf;/home/polarolouis/Zotero/storage/YSE8ZGL6/Chen et al. - 2019 - A quantitative framework for characterizing the ev.pdf}
}

@article{gomez-mestrePhylogeneticAnalysesReveal2012,
  title = {Phylogenetic {{Analyses Reveal Unexpected Patterns}} in the {{Evolution}} of {{Reproductive Modes}} in {{Frogs}}},
  author = {Gomez-Mestre, Ivan and Pyron, Robert Alexander and Wiens, John J.},
  date = {2012},
  journaltitle = {Evolution},
  volume = {66},
  number = {12},
  pages = {3687--3700},
  issn = {1558-5646},
  doi = {10.1111/j.1558-5646.2012.01715.x},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1558-5646.2012.01715.x},
  urldate = {2023-11-13},
  abstract = {Understanding phenotypic diversity requires not only identification of selective factors that favor origins of derived states, but also factors that favor retention of primitive states. Anurans (frogs and toads) exhibit a remarkable diversity of reproductive modes that is unique among terrestrial vertebrates. Here, we analyze the evolution of these modes, using comparative methods on a phylogeny and matched life-history database of 720 species, including most families and modes. As expected, modes with terrestrial eggs and aquatic larvae often precede direct development (terrestrial egg, no tadpole stage), but surprisingly, direct development evolves directly from aquatic breeding nearly as often. Modes with primitive exotrophic larvae (feeding outside the egg) frequently give rise to direct developers, whereas those with nonfeeding larvae (endotrophic) do not. Similarly, modes with eggs and larvae placed in locations protected from aquatic predators evolve frequently but rarely give rise to direct developers. Thus, frogs frequently bypass many seemingly intermediate stages in the evolution of direct development. We also find significant associations between terrestrial reproduction and reduced clutch size, larger egg size, reduced adult size, parental care, and occurrence in wetter and warmer regions. These associations may help explain the widespread retention of aquatic eggs and larvae, and the overall diversity of anuran reproductive modes.},
  langid = {english},
  keywords = {Amphibians,clutch size,development,egg size,life history,parental care},
  file = {/home/polarolouis/Zotero/storage/GBE54CP9/j.1558-5646.2012.01715.x.pdf.pdf;/home/polarolouis/Zotero/storage/NCIMVLYA/Gomez-Mestre et al. - 2012 - Phylogenetic Analyses Reveal Unexpected Patterns i.pdf;/home/polarolouis/Zotero/storage/UWSX6UBK/j.1558-5646.2012.01715.html}
}

@article{kuznetsovaLmerTestPackageTests2017,
  title = {{{{\textbf{lmerTest}}}} {{Package}}: {{Tests}} in {{Linear Mixed Effects Models}}},
  shorttitle = {{{{\textbf{lmerTest}}}} {{Package}}},
  author = {Kuznetsova, Alexandra and Brockhoff, Per B. and Christensen, Rune H. B.},
  date = {2017},
  journaltitle = {J. Stat. Soft.},
  volume = {82},
  number = {13},
  issn = {1548-7660},
  doi = {10.18637/jss.v082.i13},
  url = {http://www.jstatsoft.org/v82/i13/},
  urldate = {2024-03-01},
  abstract = {One of the frequent questions by users of the mixed model function lmer of the lme4 package has been: How can I get p values for the F and t tests for objects returned by lmer? The lmerTest package extends the ‘lmerMod’ class of the lme4 package, by overloading the anova and summary functions by providing p values for tests for fixed effects. We have implemented the Satterthwaite’s method for approximating degrees of freedom for the t and F tests. We have also implemented the construction of Type I–III ANOVA tables. Furthermore, one may also obtain the summary as well as the anova table using the Kenward-Roger approximation for denominator degrees of freedom (based on the KRmodcomp function from the pbkrtest package). Some other convenient mixed model analysis tools such as a step method, that performs backward elimination of nonsignificant effects – both random and fixed, calculation of population means and multiple comparison tests together with plot facilities are provided by the package as well.},
  langid = {english},
  file = {/home/polarolouis/Zotero/storage/GM4PNU23/Kuznetsova et al. - 2017 - lmerTest Package Tests in Linear Mixed Eff.pdf}
}

@book{petersenMatrixCookbook2012,
  title = {The {{Matrix Cookbook}}},
  author = {Petersen, Kaare Brandt and Pedersen, Michael Syskind},
  date = {2012},
  edition = {Version 20121115},
  url = {http://matrixcookbook.com},
  langid = {english},
  file = {/home/polarolouis/Zotero/storage/45U262HQ/Petersen et Pedersen - [ httpmatrixcookbook.com ].pdf}
}

@article{rohlfsPhylogeneticANOVAExpression2015,
  title = {Phylogenetic {{ANOVA}}: {{The Expression Variance}} and {{Evolution Model}} for {{Quantitative Trait Evolution}}},
  shorttitle = {Phylogenetic {{ANOVA}}},
  author = {Rohlfs, Rori V. and Nielsen, Rasmus},
  date = {2015-09-01},
  journaltitle = {Systematic Biology},
  volume = {64},
  number = {5},
  pages = {695--708},
  issn = {1063-5157},
  doi = {10.1093/sysbio/syv042},
  url = {https://doi.org/10.1093/sysbio/syv042},
  urldate = {2024-03-06},
  abstract = {A number of methods have been developed for modeling the evolution of a quantitative trait on a phylogeny. These methods have received renewed interest in the context of genome-wide studies of gene expression, in which the expression levels of many genes can be modeled as quantitative traits. We here develop a new method for joint analyses of quantitative traits within- and between species, the Expression Variance and Evolution (EVE) model. The model parameterizes the ratio of population to evolutionary expression variance, facilitating a wide variety of analyses, including a test for lineage-specific shifts in expression level, and a phylogenetic ANOVA that can detect genes with increased or decreased ratios of expression divergence to diversity, analogous to the famous Hudson Kreitman Aguadé (HKA) test used to detect selection at the DNA level. We use simulations to explore the properties of these tests under a variety of circumstances and show that the phylogenetic ANOVA is more accurate than the standard ANOVA (no accounting for phylogeny) sometimes used in transcriptomics. We then apply the EVE model to a mammalian phylogeny of 15 species typed for expression levels in liver tissue. We identify genes with high expression divergence between species as candidates for expression level adaptation, and genes with high expression diversity within species as candidates for expression level conservation and/or plasticity. Using the test for lineage-specific expression shifts, we identify several candidate genes for expression level adaptation on the catarrhine and human lineages, including genes putatively related to dietary changes in humans. We compare these results to those reported previously using a model which ignores expression variance within species, uncovering important differences in performance. We demonstrate the necessity for a phylogenetic model in comparative expression studies and show the utility of the EVE model to detect expression divergence, diversity, and branch-specific shifts.},
  file = {/home/polarolouis/Zotero/storage/ES45EYZH/Rohlfs et Nielsen - 2015 - Phylogenetic ANOVA The Expression Variance and Ev.pdf;/home/polarolouis/Zotero/storage/HWPUQ995/sysbio%252Fsyv042.pdf.pdf;/home/polarolouis/Zotero/storage/944V85WY/1686874.html}
}

@article{satterthwaiteApproximateDistributionEstimates1946,
  title = {An {{Approximate Distribution}} of {{Estimates}} of {{Variance Components}}},
  author = {Satterthwaite, F. E.},
  date = {1946-12},
  journaltitle = {Biometrics Bulletin},
  volume = {2},
  number = {6},
  eprint = {10.2307/3002019},
  eprinttype = {jstor},
  pages = {110},
  issn = {00994987},
  doi = {10.2307/3002019},
  url = {https://www.jstor.org/stable/10.2307/3002019?origin=crossref},
  urldate = {2024-01-08},
  file = {/home/polarolouis/Zotero/storage/3LCFSKSP/3002019.pdf.pdf;/home/polarolouis/Zotero/storage/PN8NJFRS/Satterthwaite - 1946 - An Approximate Distribution of Estimates of Varian.pdf}
}

@online{WideCrossSpecies,
  title = {Wide Cross‐species {{RNA}}‐{{Seq}} Comparison Reveals Convergent Molecular Mechanisms Involved in Nickel Hyperaccumulation across Dicotyledons - {{García}} de La {{Torre}} - 2021 - {{New Phytologist}} - {{Wiley Online Library}}},
  url = {https://nph.onlinelibrary.wiley.com/doi/full/10.1111/nph.16775},
  urldate = {2023-11-20},
  file = {/home/polarolouis/Zotero/storage/KBJ8GALG/nph.html}
}