STEM: species tree estimation using maximum likelihood for gene trees under coalescence

By Laura Salter Kubatko, Bryan C. Carstens, L. Lacey Knowles. Bioinform., 2009

458 citations recorded by the source corpus.

Subfields: Ecological Modeling, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/0dae2d6a36615953df913376339357b4c3887464

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Citations in the corpus

Bayesian Inference of Species Trees from Multilocus Data (2009, background): “This is the rooted equivalent of the “branch score” metric suggested by Kuhner and Felsenstein (1994) and is defined in Appendix.”
Phylogeographic studies of plants in China: Advances in the past and directions in the future (2012, background): “Because the gene coalescent times always predate the species divergence times, minimum coalescent times can be used to reconstruct species trees roughly (Kubatko et al., 2009).”
Quartet Inference from SNP Data Under the Coalescent Model (2014, unknown): “The most popular approaches in this category are Maximum Tree (Liu et al. , 2009b) [also implemented in the program STEM (Kubatko et al. , 2009)], STAR (Liu et al. , 2009c), STEAC (Liu et al. , 2009c), MP-EST (Liu et al. , 2010) and Minimize Deep Coalescences [as implemented in the program PhyloNet ”
How to fail at species delimitation (2013, methodology): “Because the –lnL (ST|GTs) is computed directly by STEM (Kubatko et al. 2009), rather than estimated, phylogenetic uncertainty in the species tree does not affect species delimitations.”
A maximum pseudo-likelihood approach for estimating species trees under the coalescent model (2010, background): “Although it would be highly desirable to estimate branch lengths of species trees directly in units of substitutions per site as in traditional phylogenies and some species tree algorithms (STEM [33] and BEST [9]), such an estimation procedure would require properly modelling the mutation rate varia”
Phylogeography's past, present, and future: 10 years after Avise, 2000. (2010, methodology): “Another common statistical approach is to assume a single model and estimate parameters under the model using full likelihood/Bayesian approaches that make use of all of the data (Beerli and Felsenstein, 2001; Hey and Nielsen, 2004, 2007; Kuhner, 2006; Kuhner et al., 1998).”
Inferring Phylogenies from RAD Sequence Data (2012, methodology): “Other methods for reconstructing species trees from gene trees are prohibitively slow on large data sets (BEST; [43]), or have not been tested on data sets consisting of large amounts of missing data (*BEAST, STEM; [22,23]).”
Applications of next-generation sequencing to phylogeography and phylogenetics. (2013, methodology): “Alternatively, algorithmic methods such as STEM (Kubatko et al., 2009) take gene trees as input, thus allowing gene trees from individual loci to be estimated in parallel prior to species tree estimation.”
Species Delimitation: A Decade After the Renaissance (2013, unknown): “This new theoretical framework allows prediction of the probability distribution of gene trees given the species tree, and consequently, several methods were developed for estimating species trees from a collection of multiple gene trees under different algorithms [64,65].”
Multi‐gene phylogenetic analysis of south‐east Asian pest members of the Bactrocera dorsalis species complex (Diptera: Tephritidae) does not support current taxonomy (2014, methodology): “…gene trees in this study were unresolved and therefore prevented the use of the speciestree software (e.g.,Ane et al. 2007; Liu 2008; Liu et al. 2009; Kubatko 2009; Kubatko et al. 2009; Heled and Drummond 2010; Than and Nakhleh 2009; Than et al. 2008; Huang et al. 2010; Knowles and Kubatko 2010).”
High-Throughput Genomic Data in Systematics and Phylogenetics (2013, methodology): “F or p er so na l u se o nl y. ES44CH06-Lemmon ARI 29 October 2013 10:2 Heled & Drummond 2010), directly from biallelic markers (SNAPP: Bryant et al. 2012), indirectly from a set of gene trees (e.g., STEM: Kubatko et al. 2009; MP-EST: Liu et al. 2010), or indirectly using summary statistics (e.g., S”
Ecological opportunity and the origin of adaptive radiations (2010, background): “Whereas population genetic processes have explicitly been incorporated into phylogeny estimation (e.g. Maddison, 1997; Maddison & Knowles, 2006; Drummond & Rambaut, 2007; Kubatko et al., 2009; Liu et al., 2009), little has been made in this regard for comparative methods (but see Estes & Arnold, 200”
Error in Phylogenetic Estimation for Bushes in the Tree of Life (2013, background): “1a [56] to &nd maximum likelihood (ML) estimates of species trees by reconciling gene trees.”
Integrative taxonomy, or iterative taxonomy? (2011, methodology): “…methods use gene trees as input data and the congruence between individual input trees calculated via various optimality criteria, e.g. likelihood in stem (Kubatko et al., 2009), or maximising the coalescence probabilities of gene trees for a given species tree (esp-coal; Carstens & Knowles, 2007).”