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The analysis of groups of adjacent apples below a given tree showed heterogeneity at this scale in the distribution of C. elegans and/or C. briggsae.
To test whether the distribution of apples was homogeneous among different groups of apples sampled below a given tree, we used a generalized linear model (GLM), assuming a Poisson response variable and a log link function.
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We need to show how to determine whether a given tree edge e= v, w) in a galled network N can represent a given cluster C. Let L e denote the set of all leaves below the node w that are reachable from w via a path of tree edges, and let R e denote the set of all reticulate nodes below w that are reachable from w via a path of tree edges, followed by a single reticulate edge.
The percentage of re-sampled trees supporting a given tree node are shown.
Each tree in each phylome was first compared with a given species tree.
The decision tree in Fig. 1 also recommends employing J48 for problems whose sparsity (measured by T2) is below a given threshold (the higher the value of T2, the denser the dataset).
Red numbers within the tree indicate number of trees corresponding to more than 80% of statistical support for a given group, whereas black indicates values below 80%.
Similarly, BindML [ 12] uses local MSAs, specialized substitution matrices, and phylogenetic tree construction to obtain the likelihood that a given patch MSA belongs to a PPIS (described below).
BI analyses were performed using four Monte Carlo Markov Chains (MCMC) running on a given number of generations (starting at 10,000 and increasing until standard deviation was below 0.01), with trees being sampled every 100 generations.
In the sections below, we give a few examples.
Below, we give an extension of (1.2).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com