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An up-to-date reference book on phylogenetic methods and applications for evolutionary biologistsThe increasingly widespread availability of genomic data is transforming how biologists estimate evolutionary relationships among organisms and broadening the range of questions that researchers can test in a phylogenetic framework. Species Tree Inference brings together many of today’s leading scholars in the field to provide an incisive guide to the latest practices for analyzing multilocus sequence data.This wide-ranging and authoritative book gives detailed explanations of emerging new approaches and assesses their strengths and challenges, offering an invaluable context for gauging which procedure to apply given the types of genomic data and processes that contribute to differences in the patterns of inheritance across loci. It demonstrates how to apply these approaches using empirical studies that span a range of taxa, timeframes of diversification, and processes that cause the evolutionary history of genes across genomes to differ.By fully embracing this genomic heterogeneity, Species Tree Inference illustrates how to address questions beyond the goal of estimating phylogenetic relationships of organisms, enabling students and researchers to pursue their own research in statistically sophisticated ways while charting new directions of scientific discovery.

Phylogeny. --- Biology --- Accuracy and precision. --- Addition. --- Akaike information criterion. --- Algebraic geometry. --- Algorithm. --- Allele. --- Ammunition. --- Amplicon. --- Analysis. --- Approximation. --- Bayesian inference. --- Biological process. --- CPU time. --- Chromosome. --- Coalescent theory. --- Common descent. --- Computation. --- Computational phylogenetics. --- Conditional expectation. --- Conditional probability distribution. --- Confidence interval. --- Consideration. --- Data set. --- Detection. --- Determinant. --- East Asia. --- Effective population size. --- Empiricism. --- Error term. --- Error. --- Estimation. --- Evolution. --- F1 hybrid. --- Gene duplication. --- Gene flow. --- Gene. --- Genre. --- Graphics processing unit. --- Horizontal gene transfer. --- Hybrid (biology). --- Identifiability. --- Implementation. --- Inference. --- Introgression. --- Likelihood function. --- Linear regression. --- Lycopersicon. --- Markov chain Monte Carlo. --- Molecular evolution. --- Molecular marker. --- Monocotyledon. --- Monte Carlo method. --- NP-hardness. --- Narration. --- Network topology. --- Normal distribution. --- Nucleic acid sequence. --- Nucleic acid structure. --- Nucleotide. --- Null hypothesis. --- Order of magnitude. --- Outgroup (cladistics). --- Parameter (computer programming). --- Parameter. --- Phylogenetic network. --- Phylogenetic tree. --- Phylogenetics. --- Phylogenomics. --- Polyploid. --- Posterior probability. --- Prediction. --- Probability distribution. --- Probability. --- Pseudolikelihood. --- Quantity. --- Rational number. --- Requirement. --- Result. --- Reticulation (single-access key). --- Sample Size. --- Scalability. --- Selection bias. --- Sequence alignment. --- Shading. --- Singular value decomposition. --- Solanum. --- Speciation (genetic algorithm). --- Speciation. --- Species. --- Statistical model. --- Statistical significance. --- Statistics. --- Subset. --- Substitution model. --- Suggestion. --- Tax. --- Taxon. --- Test statistic. --- Trade-off. --- Uncertainty.