Generating samples under a Wright-Fisher neutral model of genetic variation

By R. Hudson. Bioinform., 2002

2,576 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Environmental Engineering, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/c654498e77b46862a5eca337fb486f5fc60a73ab

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Citations in the corpus

Selecting additional tag SNPs for tolerating missing data in genotyping (2005, positive): “The remaining SNPs in each data set are still sufficient to tolerate more missing SNPs. Hudson (2002) [10] provides a program which can simulate a set of haplotypes under the assumption of neutral evolution and uniformly distributed recombination rate using the coalescent model.”
Inferring Phylogenetic Networks Using PhyloNet (2017, methodology): “In particular, the former automates the process of simulating gene trees in the presence of reticulation and incomplete lineage sorting using the program ms (Hudson, 2002).”
Efficient Coalescent Simulation and Genealogical Analysis for Large Sample Sizes (2015, methodology): “The first simulation program published based on Hudson’s algorithm was ms [11].”
Reanalysis suggests that genomic islands of speciation are due to reduced diversity, not reduced gene flow (2014, methodology): “Here, we have focused on reanalyzing the data from loci sequenced in three earlier studies (”
Likelihood-Free Inference of Population Structure and Local Adaptation in a Bayesian Hierarchical Model (2010, background): “Much of this could be achieved by the use of generalpurpose packages (Rambaut and Grassly 1997; Hudson 2002; Laval and Excoffier 2004).”
Comparison of Bayesian and maximum-likelihood inference of population genetic parameters (2006, methodology): “Availability: The program is available from http://popgen.csit.fsu.edu/ Contact: beerli@csit.fsu.edu”
PopGenome: An Efficient Swiss Army Knife for Population Genomic Analyses in R (2014, methodology): “PopGenome is fully integrated with two widely used coalescent simulation tools: Hudson’s MS (Hudson 2002), as well as Ewing’s MSMS (Ewing and Hermisson 2010), which incorporates selection.”
MTML-msBayes: Approximate Bayesian comparative phylogeographic inference from multiple taxa and multiple loci with rate heterogeneity (2011, methodology): “The data generation step is accomplished by msDQH which is a version of Hudson ’ s classic coalescent simulator which simulates finite sites DNA sequence data under specified demographic model [36].”
Inference of Population Structure using Dense Haplotype Data (2012, methodology): “A) True underlying genealogies for eight simulated sequences at three locations along a genomic segment, produced using the program ‘ms’ [52] and showing coalescence times between haplotypes at each position.”
Computer simulations: tools for population and evolutionary genetics (2012, background): “Backwards in time, lineages coalesce progressively with a probability that is influenced by features of the sample and the evolutionary history 69,94,95 .”
Applications of landscape genetics in conservation biology: concepts and challenges (2010, methodology): “ABC analyses are greatly facilitated by the availability of powerful coalescent simulation programs such as MS (Hudson 2002) or SIMCOAL (Laval and Excoffier 2004).”
Minimac2: Faster Genotype Imputation (2015, methodology): “…engineering techniques described in this article helped to speed up Results are based on simulated haplotypes under a coalescent model using ms (Hudson, 2002) under a model consistent with European haplotype diversity (Plagnol and Wall, 2006), and imputed into GWAS data. imputation by an order…”