Searcharxiv⌕ Search

arXiv subjects

Mike Steel

Publications and source records attributed to Mike Steel.

At least 73 records · Page 4Linked to original sources

Reflections on the extinction-explosion dichotomy

A wide range of stochastic processes that model the growth and decline of populations exhibit a curious dichotomy: with certainty either the population goes extinct or its size tends to infinity. There is a elegant and classical theorem that explains why this dichotomy must hold under certain assumptions concerning the process. In this note, I explore how these assumptions might be relaxed further in order to obtain the same, or a similar conclusion, and obtain both positive and negative results.

q-bio.PE↗

Likelihood-based tree reconstruction on a concatenation of alignments can be positively misleading

The reconstruction of a species tree from genomic data faces a double hurdle. First, the (gene) tree describing the evolution of each gene may differ from the species tree, for instance, due to incomplete lineage sorting. Second, the aligned genetic sequences at the leaves of each gene tree provide merely an imperfect estimate of the topology of the gene tree. In this note, we demonstrate formally that a basic statistical problem arises if one tries to avoid accounting for these two processes and analyses the genetic data directly via a concatenation approach. More precisely, we show that, under the multi-species coalescent with a standard site substitution model, maximum likelihood estimation on sequence data that has been concatenated across genes and performed under the incorrect assumption that all sites have evolved independently and identically on a fixed tree is a statistically inconsistent estimator of the species tree. Our results provide a formal justification of simulation results described of Kubatko and Degnan (2007) and others, and complements recent theoretical results by DeGorgio and Degnan (2010) and Chifman and Kubtako (2014).

q-bio.PE↗

The most parsimonious tree for random data

Applying a method to reconstruct a phylogenetic tree from random data provides a way to detect whether that method has an inherent bias towards certain tree `shapes'. For maximum parsimony, applied to a sequence of random 2-state data, each possible binary phylogenetic tree has exactly the same distribution for its parsimony score. Despite this pleasing and slightly surprising symmetry, some binary phylogenetic trees are more likely than others to be a most parsimonious (MP) tree for a sequence of $k$ such characters, as we show. For $k=2$, and unrooted binary trees on six taxa, any tree with a caterpillar shape has a higher chance of being an MP tree than any tree with a symmetric shape. On the other hand, if we take any two binary trees, on any number of taxa, we prove that this bias between the two trees vanishes as the number of characters grows. However, again there is a twist: MP trees on six taxa are more likely to have certain shapes than a uniform distribution on binary phylogenetic trees predicts, and this difference does not appear to dissipate as $k$ grows.

q-bio.PE↗

Axiomatic opportunities and obstacles for inferring a species tree from gene trees

The reconstruction of a central tendency `species tree' from a large number of conflicting gene trees is a central problem in systematic biology. Moreover, it becomes particularly problematic when taxon coverage is patchy, so that not all taxa are present in every gene tree. Here, we list four apparently desirable properties that a method for estimating a species tree from gene trees could have (the strongest property states that building a species tree from input gene trees and then pruning leaves gives a tree that is the same as, or more resolved than, the tree obtained by first removing the taxa from the input trees and then building the species tree). We show that while it is technically possible to simultaneously satisfy these properties when taxon coverage is complete, they cannot all be satisfied in the more general supertree setting. In part two, we discuss a concordance-based consensus method based on Baum's `plurality clusters', and an extension to concordance supertrees.

q-bio.PE↗

Majority rule has transition ratio 4 on Yule trees under a 2-state symmetric model

Inferring the ancestral state at the root of a phylogenetic tree from states observed at the leaves is a problem arising in evolutionary biology. The simplest technique -- majority rule -- estimates the root state by the most frequently occurring state at the leaves. Alternative methods -- such as maximum parsimony - explicitly take the tree structure into account. Since either method can outperform the other on particular trees, it is useful to consider the accuracy of the methods on trees generated under some evolutionary null model, such as a Yule pure-birth model. In this short note, we answer a recently posed question concerning the performance of majority rule on Yule trees under a symmetric 2-state Markovian substitution model of character state change. We show that majority rule is accurate precisely when the ratio of the birth (speciation) rate of the Yule process to the substitution rate exceeds the value $4$. By contrast, maximum parsimony has been shown to be accurate only when this ratio is at least 6. Our proof relies on a second moment calculation, coupling, and a novel application of a reflection principle.

q-bio.PE↗

Tracing evolutionary links between species

The idea that all life on earth traces back to a common beginning dates back at least to Charles Darwin's {\em Origin of Species}. Ever since, biologists have tried to piece together parts of this `tree of life' based on what we can observe today: fossils, and the evolutionary signal that is present in the genomes and phenotypes of different organisms. Mathematics has played a key role in helping transform genetic data into phylogenetic (evolutionary) trees and networks. Here, I will explain some of the central concepts and basic results in phylogenetics, which benefit from several branches of mathematics, including combinatorics, probability and algebra.

q-bio.PE↗

Autocatalytic sets in a partitioned biochemical network

In previous work, RAF theory has been developed as a tool for making theoretical progress on the origin of life question, providing insight into the structure and occurrence of self-sustaining and collectively autocatalytic sets within catalytic polymer networks. We present here an extension in which there are two "independent" polymer sets, where catalysis occurs within and between the sets, but there are no reactions combining polymers from both sets. Such an extension reflects the interaction between nucleic acids and peptides observed in modern cells and proposed forms of early life.

q-bio.MN↗

Tree split probabilities determine the branch lengths

The evolution of aligned DNA sequence sites is generally modeled by a Markov process operating along the edges of a phylogenetic tree. It is well known that the probability distribution on the site patterns at the tips of the tree determines the tree and its branch lengths. However, the number of patterns is typically much larger than the number of edges, suggesting considerable redundancy in the branch length estimation. In this paper we ask whether the probabilities of just the `edge-specific' patterns (the ones that correspond to a change of state on a single edge) suffice to recover the branch lengths of the tree, under a symmetric 2-state Markov process. We first show that this holds provided the branch lengths are sufficiently short, by applying the inverse function theorem. We then consider whether this restriction to short branch lengths is necessary, and show that for trees with up to four leaves it can be lifted. This leaves open the interesting question of whether this holds in general.

q-bio.PE↗

Predicting the ancestral character changes in a tree is typically easier than predicting the root state

Predicting the ancestral sequences of a group of homologous sequences related by a phylogenetic tree has been the subject of many studies, and numerous methods have been proposed to this purpose. Theoretical results are available that show that when the mutation rate become too large, reconstructing the ancestral state at the tree root is no longer feasible. Here, we also study the reconstruction of the ancestral changes that occurred along the tree edges. We show that, depending on the tree and branch length distribution, reconstructing these changes (i.e. reconstructing the ancestral state of all internal nodes in the tree) may be easier or harder than reconstructing the ancestral root state. However, results from information theory indicate that for the standard Yule tree, the task of reconstructing internal node states remains feasible, even for very high substitution rates. Moreover, computer simulations demonstrate that for more complex trees and scenarios, this result still holds. For a large variety of counting, parsimony-based and likelihood-based methods, the predictive accuracy of a randomly selected internal node in the tree is indeed much higher than the accuracy of the same method when applied to the tree root. Moreover, parsimony- and likelihood-based methods appear to be remarkably robust to sampling bias and model mis-specification.

q-bio.PE↗

A matroid associated with a phylogenetic tree

A (pseudo-)metric $D$ on a finite set $X$ is said to be a `tree metric' if there is a finite tree with leaf set $X$ and non-negative edge weights so that, for all $x,y \in X$, $D(x,y)$ is the path distance in the tree between $x$ and $y$. It is well known that not every metric is a tree metric. However, when some such tree exists, one can always find one whose interior edges have strictly positive edge weights and that has no vertices of degree 2, any such tree is -- up to canonical isomorphism -- uniquely determined by $D$, and one does not even need all of the distances in order to fully (re-)construct the tree's edge weights in this case. Thus, it seems of some interest to investigate which subsets of $\binom{X}{2}$ suffice to determine (`lasso') these edge weights. In this paper, we use the results of a previous paper to discuss the structure of a matroid that can be associated with an (unweighted) $X-$tree $T$ defined by the requirement that its bases are exactly the `tight edge-weight lassos' for $T$, i.e, the minimal subsets $\cl$ of $\ch$ that lasso the edge weights of $T$.

math.CO↗

An Arrow-type result for inferring a species tree from gene trees

The reconstruction of a central tendency `species tree' from a large number of conflicting gene trees is a central problem in systematic biology. Moreover, it becomes particularly problematic when taxon coverage is patchy, so that not all taxa are present in every gene tree. Here, we list four desirable properties that a method for estimating a species tree from gene trees should have. We show that while these can be achieved when taxon coverage is complete (by the Adams consensus method), they cannot all be satisfied in the more general setting of partial taxon coverage.

q-bio.PE↗

Consistency of Bayesian inference of resolved phylogenetic trees

Bayesian inference is now a leading technique for reconstructing phylogenetic trees from aligned sequence data. In this short note, we formally show that the maximum posterior tree topology provides a statistically consistent estimate of a fully-resolved evolutionary tree under a wide variety of conditions. This includes the inference of gene trees from aligned sequence data across the entire parameter range of branch lengths, and under general conditions on priors in models where the usual `identifiability' conditions hold. We extend this to the inference of species trees from sequence data, where the gene trees constitute `nuisance parameters', as in the program *BEAST. This note also addresses earlier concerns raised in the literature questioning the extent to which statistical consistency for Bayesian methods might hold in general.

q-bio.PE↗

Autocatalytic Sets and Biological Specificity

A universal feature of the biochemistry of any living system is that all the molecules and catalysts that are required for reactions of the system can be built up from an available food source by repeated application of reactions from within that system. RAF (reflexively autocatalytic and food-generated) theory provides a formal way to study such processes. Beginning with Kauffman's notion of "collectively autocatalytic sets", this theory has been further developed over the last decade with the discovery of efficient algorithms and new mathematical analysis. In this paper, we study how the behaviour of a simple binary polymer model can be extended to models where the pattern of catalysis more precisely reflects the ligation and cleavage reactions involved. We find that certain properties of these models are similar to, and can be accurately predicted from, the simple binary polymer model; however, other properties lead to slightly different estimates. We also establish a number of new results concerning the structure of RAFs in these systems.

q-bio.MN↗

The Structure of N-Player Games when Influence and Independence Collide

We study the mathematical properties of probabilistic processes in which the independent actions of $n$ players (`causes') can influence the outcome of each player (`effects'). In such a setting, each pair of outcomes will generally be statistically correlated, even if the actions of all the players provide a complete causal description of the players' outcomes, and even if we condition on the outcome of any one player's action. This correlation always holds when $n=2$, but when $n=3$ there exists a highly symmetric process, recently studied, in which each cause can influence each effect, and yet each pair of effects is probabilistically independent (even upon conditioning on any one cause). We study such symmetric processes in more detail, obtaining a complete classification for all $n \geq 3$. Using a variety of mathematical techniques, we describe the geometry and topology of the underlying probability space that allows independence and influence to coexist.

math.PR↗

Predicting the loss of phylogenetic diversity under non-stationary diversification models

For many taxa, the current high rates of extinction are likely to result in a significant loss of biodiversity. The evolutionary heritage of biodiversity is frequently quantified by a measure called phylogenetic diversity (PD). We predict the loss of PD under a wide class of phylogenetic tree models, where speciation rates and extinction rates may be time-dependent, and assuming independent random species extinctions at the present. We study the loss of PD when $K$ contemporary species are selected uniformly at random from the $N$ extant species as the surviving taxa, while the remaining $N-K$ become extinct. We consider two models of species sampling, the so-called field of bullets model, where each species independently survives the extinction event at the present with probability $p$, and a model for which the number of surviving species is fixed. We provide explicit formulae for the expected remaining PD in both models, conditional on $N=n$, conditional on $K=k$, or conditional on both events. When $N=n$ is fixed, we show the convergence to an explicit deterministic limit of the ratio of new to initial PD, as $n\to\infty$, both under the field of bullets model, and when $K=k_n$ is fixed and depends on $n$ in such a way that $k_n/n$ converges to $p$. We also prove the convergence of this ratio as $T\to\infty$ in the supercritical, time-homogeneous case, where $N$ simultaneously goes to $\infty$, thereby strengthening previous results of Mooers et al. (2012).

q-bio.PE↗

Hide and seek: placing and finding an optimal tree for thousands of homoplasy-rich sequences

Finding optimal evolutionary trees from sequence data is typically an intractable problem, and there is usually no way of knowing how close to optimal the best tree from some search truly is. The problem would seem to be particularly acute when we have many taxa and when that data has high levels of homoplasy, in which the individual characters require many changes to fit on the best tree. However, a recent mathematical result has provided a precise tool to generate a short number of high-homoplasy characters for any given tree, so that this tree is provably the optimal tree under the maximum parsimony criterion. This provides, for the first time, a rigorous way to test tree search algorithms on homoplasy-rich data, where we know in advance what the `best' tree is. In this short note we consider just one search program (TNT) but show that it is able to locate the globally optimal tree correctly for 32,768 taxa, even though the characters in the dataset requires, on average, 1148 state-changes each to fit on this tree, and the number of characters is only 57.

q-bio.PE↗

The standard lateral gene transfer model is statistically consistent for pectinate four-taxon trees

Evolutionary events such as incomplete lineage sorting and lateral gene transfer constitute major problems for inferring species trees from gene trees, as they can sometimes lead to gene trees which conflict with the underlying species tree. One particularly simple and efficient way to infer species trees from gene trees under such conditions is to combine three-taxon analyses for several genes using a majority vote approach. For incomplete lineage sorting this method is known to be statistically consistent, however, in the case of lateral gene transfer it is known that a zone of inconsistency does exist for a specific four-taxon tree topology. In this paper we analyze all remaining four-taxon topologies and show that no other inconsistencies exist.

q-bio.PE↗

Time and Knowability in Evolutionary Processes

Historical sciences like evolutionary biology reconstruct past events by using the traces that the past has bequeathed to the present. The Markov Chain Convergence Theorem and the Data Processing Inequality describe how the mutual information between present and past is affected by how much time there is in between. These two results are very general; they pertain to any process, not just to the biological processes that occur in evolution. To study the specifically biological question of how the present state of a lineage provides information about its evolutionary past, we use a Moran process framework and consider how the kind of evolutionary process (drift, and selection of various kinds) at work in a lineage affects the epistemological relation of present to past.

q-bio.PE↗