Árnason E. Mitochondrial cytochrome b variation in the high-fecundity Atlantic cod: trans-Atlantic clines and shallow gene genealogy. Genetics. 2004; 166:1871–85.

Article
PubMed
PubMed Central
Google Scholar

Árnason E, Halldórsdóttir K.Nucleotide variation and balancing selection at the Ckma gene in Atlantic cod: analysis with multiple merger coalescent models. PeerJ. 2015; e786:3. doi:10.7717/peerj.786.

Google Scholar

Bartoszek K, Jones G, Oxelman B, Sagitov S. Time to a single hybridization event in a group of species with unknown ancestral history. J Theor Biol. 2004; 322:1–6.

Article
Google Scholar

Beckenbach AT. In: (Golding B, editor.)Mitochondrial haplotype frequencies in oysters: neutral alternatives to selection models, Non-neutral Evolution. New York: Chapman & Hall; 1994, pp. 188–98.

Google Scholar

Cardona G, Rossell F, Valiente G. Extended Newick: it is time for a standard representation of phylogenetic networks. BMC Bioinform. 2008; 9:532.

Article
Google Scholar

Degnan JH, Salter LA. Gene tree distributions under the coalescent process. Evolution. 2005; 59:24–37.

Article
PubMed
Google Scholar

Delmas JF, Dhersin JS, Siri-Jegousse A. Asymptotic results on the length of coalescent trees. Ann Appl Prob. 2008; 18:997–1025.

Article
Google Scholar

Donnelly P, Kurtz TG. Particle representations for measure-valued population models. Ann Probab. 1999; 27:166–205.

Article
Google Scholar

Eldon B, Wakeley J. Coalesent processes when the distribution of offspring number among individuals is highly skewed. Genetics. 2006; 172:2621–33.

Article
CAS
PubMed
PubMed Central
Google Scholar

Eldon B, Wakeley J. Coalescence times and *F*
_{
ST
} under a skewed offspring distribution among individuals in a population. Genetics. 2009; 181:615–29.

Article
PubMed
PubMed Central
Google Scholar

Eldon B. Estimation of parameters in large offspring number models and ratios of coalescence times. Theor Popul Biol. 2011; 80:16–28.

Article
PubMed
Google Scholar

Eldon B, Degnan JH. Multiple merger gene genealogies in two species: monophyly, paraphyly, and polyphyly for two examples of Lambda coalescents. Theor Popul Biol. 2012; 82:117–30.

Article
PubMed
Google Scholar

Eldon B, Birkner M, Blath J, Freund F. Can the Site-Frequency Spectrum Distinguish Exponential Population Growth from Multiple-Merger CoalescentsGenetics. 2015; 199:841–56.

Article
PubMed
PubMed Central
Google Scholar

Ewing G, Hermisson J. MSMS: a coalescent simulation program including recombination, demographic structure and selection at a single locus. Bioinformatics. 2010; 26:2064–65.

Article
CAS
PubMed
PubMed Central
Google Scholar

Excoffier L, Foll M. Fastsimcoal: a continuous-time coalescent simulator of genomic diversity under arbitrarily complex evolutionary scenarios. Bioinformatics. 2011; 27:9.

Article
CAS
Google Scholar

Goldstien SJ, Schiel DR, Gemmell NJ. Comparative phylogeography of coastal limpets across a marine disjunction in New Zealand. Mol Ecol. 2009; 15:3259–68.

Article
CAS
Google Scholar

Hedgecock D. In: (Beaumont A, editor.)Does variance in reproductive success limit effective population sizes of marine organisms? Genetics and Evolution of Aquatic Organisms. London: Chapman and Hall; 1994, pp. 1222–344.

Google Scholar

Hedgecock D, Tracey M, Nelson K. In: (Abele LG, editor.)Genetics, The Biology of Crustacea vol. 2. New York: Academic Press; 1982, pp. 297–403.

Google Scholar

Hedgecock D, Pudovkin AI. Sweepstakes reproductive success in highly fecund marine fish and shellfish: a review and commentary. Bull Mar Sci. 2011; 87:971–1002.

Article
Google Scholar

Heled J, Bryant D, Drummond AJ. BMC Evolut Biol. 2013; 13:44.

Article
Google Scholar

Hellenthal G, Stephens M. msHOT: modifying Hudson’s ms simulator to incorporate crossover and gene conversion hotspots. Bioinformatics. 2007; 23:520–21.

Article
CAS
PubMed
Google Scholar

Holland BR, Benthin S, Lockhart PJ, Moulton V, Huber KT. BMC Evol Biol. 2008; 8:202.

Article
CAS
PubMed
PubMed Central
Google Scholar

Hudson RR. Gene genealogies and the coalescent process. Oxford Surv Evol Biol. 1990; 7:1–44.

Google Scholar

Hudson RR. Generating samples under a Wright-Fisher neutral model. Bioinformatics. 2002; 18:337–38.

Article
CAS
PubMed
Google Scholar

Huson D, Rupp R, Scornavacca C. Phylogenetic Networks: Concepts, Algorithms and Applications: Cambridge University Press; 2010.

Jones G, Sagitov S, Oxelman B. Statistical inference of allopolyploid species networks in the presence of incomplete lineage sorting. Syst Biol. 2013; 62:467–78.

Article
PubMed
Google Scholar

Kingman JFC. On the genealogy of large populations. J App Probab. 1982; 19A:27–43.

Article
Google Scholar

Kubatko LS. Identifying hybridization events in the presence of coalescence via model selection. Syst Biol. 2009; 58:478–88.

Article
CAS
PubMed
Google Scholar

Laval G, Excoffier L. SIMCOAL 2.0: a program to simulate genomic diversity over large recombining regions in a subdivided population with a complex history. Bioinformatics. 2004; 20:2485–87.

Article
CAS
PubMed
Google Scholar

Liang L, Zöllner S, Abecasis GR. GENOME: a rapid coalescent-based whole genome simulator. Bioinformatics. 2007; 23:1565–67.

Article
CAS
PubMed
Google Scholar

Meng C, Kubatko LS. Detecting hybrid speciation in the presence of incomplete lineage sorting using gene tree incongruence: A model. Theor Popul Biol. 2009; 75:35–45.

Article
PubMed
Google Scholar

Mailund T, Schierup H, Pedersen CNS, Mechlenborg PJM, Madsen JN, Schauser L, et al. CoaSim a flexible environment for simulating genetic data under coalescent models. BMC Bioinforma. 2005; 6:252.

Article
CAS
Google Scholar

Olsen G. Gary Olsen’s interpretation of the “Newick’s 8:45” tree format standard. 1990. http://evolution.genetics.washington.edu/phylip/newick_doc.html. Access date 2/Sep/2015.

Perrin C, Wing SR, Roy MS. Effects of hydrographic barriers on population genetic structure of the sea star Coscinasterias muricata (Echinodermata, Asteroidea) in the New Zealand fiords. Mol Ecol. 2004; 13:2183–95.

Article
CAS
PubMed
Google Scholar

Pitman J. Coalescents with multiple collisions. Ann Probab. 1999; 27:1870–902.

Article
Google Scholar

Sagitov S. The general coalescent with asynchronous mergers of ancestral lines. J Appl Probab. 1999; 36:1116–125.

Article
Google Scholar

R Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2015. http://www.R-project.org/.

Sargsyan O, Wakeley J. A coalescent process with simultaneous multiple mergers for approximating the gene genealogies of many marine organisms. Theor Popul Biol. 2008; 74:104–114.

Article
PubMed
Google Scholar

Schweinsberg J. Coalescent processes obtained from supercritical Galton-Watson processes. Stoch Proc Appl. 2003; 106:107–39.

Article
Google Scholar

Slatkin M. Inbreeding coefficients and coalescence times. Genet. Res. 1991; 58:167–175.

Article
CAS
PubMed
Google Scholar

Staab PR, Zhu S, Metzler D, Lunter G. Scrm: efficiently simulating long sequences using the approximated coalescent with recombination. Bioinformatics. 2015; 31(10):1680–82.

Article
CAS
PubMed
PubMed Central
Google Scholar

Tellier A, Lemaire C.Coalescence 2.0: a multiple branching of recent theoretical developments and their applications. Mol Ecol. 2014; 23:2637–52.

Article
PubMed
Google Scholar

Than C, Ruths D, Nakhleh L. PhyloNet: a software package for analyzing and reconstructing reticulate evolutionary relationships. BMC Bioinforma. 2008; 9:322. doi:10.1186/1471-2105-9-322.

Article
CAS
Google Scholar

Waters JM, Roy MS. Phylogeography of a high-dispersal New Zealand sea-star: does upwelling block gene-flowMol Ecol. 2004; 13:2797–806.

Article
CAS
PubMed
Google Scholar

Yu Y, Than C, Degnan JH, Nakhleh L. Coalescent histories on phylogenetic networks and detection of hybridization despite incomplete lineage sorting. Syst Biol. 2011; 60:138–49.

Article
CAS
PubMed
PubMed Central
Google Scholar

Yu Y, Degnan JH, Nakhleh L. The probability of a gene tree topology within a phylogenetic network with applications to hybridization detection. PLoS Genet. 2012; e1002660:8. doi:10.1371/journal.pgen.1002660.

Google Scholar