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5 results for “Bayesian assignment”
◂Fig. 6 A molecular phylogeny of 56 systematically representative Peridiniaceae, including 42 accessions assignable to P. cinctum from various geographic regions. Maximum likelihood tree (– ln = 21,884.93), as inferred from a rRNA nucleotide alignment (1137 parsimony-informative sites) and with strain number information. Numbers on branches are ML bootstrap (above) and Bayesian support values (below) for the clusters (asterisks indicate maximal support values, values under 50 and 0.90, respectively, are not shown). Clades are indicated (CZE Czech Republic, E East, GER Germany, HET Heterocapsaceae, N North, PPE Protoperidiniaceae, POL Poland, rbn ribotype n, S South, SWE Sweden, UKR Ukraine, W West) in Bumps on the back: An unusual morphology in phylogenetically distinct Peridinium aff. cinctum (= Peridinium tuberosum; Peridiniales, Dinophyceae)
◂Fig. 6 A molecular phylogeny of 56 systematically representative Peridiniaceae, including 42 accessions assignable to P. cinctum from various geographic regions. Maximum likelihood tree (– ln = 21,884.93), as inferred from a rRNA nucleotide alignment (1137 parsimony-informative sites) and with strain number information. Numbers on branches are ML bootstrap (above) and Bayesian support values (below) for the clusters (asterisks indicate maximal support values, values under 50 and 0.90, respectively, are not shown). Clades are indicated (CZE Czech Republic, E East, GER Germany, HET Heterocapsaceae, N North, PPE Protoperidiniaceae, POL Poland, rbn ribotype n, S South, SWE Sweden, UKR Ukraine, W West)
◂Fig. 4 A molecular tree of 51 systematically representative Peridiniaceae, including all 28 accessions assignable to P. volzii. Maximum Likelihood tree (–ln = 22,017.62), as inferred from a rRNA nucleotide alignment (1,129 parsimony-informative sites) and with strain number information. Numbers on branches are ML bootstrap (above) and Bayesian support values (below) for the clusters (asterisks indicate maximal support values, values under 50 and 0.90, respectively, are not shown). Clades are indicated (abbreviations: HET, Heterocapsaceae; PPE, Protoperidiniaceae) in Morphological and molecular variability of Peridinium volzii Lemmerm. (Peridiniaceae, Dinophyceae) and its relevance for infraspecific taxonomy
◂Fig. 4 A molecular tree of 51 systematically representative Peridiniaceae, including all 28 accessions assignable to P. volzii. Maximum Likelihood tree (–ln = 22,017.62), as inferred from a rRNA nucleotide alignment (1,129 parsimony-informative sites) and with strain number information. Numbers on branches are ML bootstrap (above) and Bayesian support values (below) for the clusters (asterisks indicate maximal support values, values under 50 and 0.90, respectively, are not shown). Clades are indicated (abbreviations: HET, Heterocapsaceae; PPE, Protoperidiniaceae)
MCMC data for A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection
<p>These are unprocessed Markov-chain Monte-Carlo datasets accompanying the manuscript "A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection"</p>
Data from: Bayesian clustering analyses for genetic assignment and study of hybridization in oaks: effects of asymmetric phylogenies and asymmetric sampling schemes
Bayesian clustering methods have been widely used for studying species delimitation and genetic introgression. In order to test the effect of phylogenetic relationships and sampling scheme on the inferred clustering solution and on the performance of Bayesian clustering analysis, I simulated genotypes of the interfertile oak species Quercus robur, Quercus petraea, and Quercus pubescens and I run analyses using two popular software programs, STRUCTURE and BAPS. First, based on purebred simulations, I compared clustering solutions resulting from different sample size configurations. While clustering solution generally reflected the taxonomic relationships when equal samples of each species were included, spurious partition was inferred by STRUCTURE when some species were represented by larger and others by smaller samples. In very unbalanced configurations, STRUCTURE failed to identify the three species, even if three subpopulations were assumed. By contrast, BAPS could properly identify the three species under any sampling scheme. Second, based on simulations of purebreds and hybrids, I tested the performance of individual assignments with variable number of loci. This analysis showed that STRUCTURE can detect introgressed individuals more efficiently than BAPS. However, BAPS could assign purebreds more efficiently with a lower number of loci. Method performance also depended on phylogenetic relationships. In the case of Q. petraea, Q. pubescens, and their hybrids, method performance was lower due to their phylogenetic affinity. Inclusion of three instead of two species into the analysis led to reduction of performance, and to misclassification of hybrids, which often reflected the phylogenetic affinity between Q. petraea and Q. pubescens.
Data from: Bayesian clustering analyses for genetic assignment and study of hybridization in oaks: effects of asymmetric phylogenies and asymmetric sampling schemes
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