Browsing by Subject "Recombination"

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Estimating recombination rates from genomic data using topological data analysis
(2018-08-01) Humphreys, Devon Paul; Hillis, David M., 1958-
Accurate estimation of recombination rates from genomic data is critical in studying the origins of evolutionary diversity. Because the inference of recombination rates under a full evolutionary model is computationally expensive, an alternative approach using topological data analysis (TDA) has been proposed. Previous TDA methods used information contained solely in the topological feature known as the first Betti number (β1) of a sample of genome sequences, and this quantity is thought to relate to the number of loops that can be detected within a genealogy with recombination. These methods are considerably less computationally intensive than current model-based methods. However, the use of topological features has proven difficult to connect to the theory of the underlying biological process of recombination, and consequently, β1 has unpredictable behavior under various evolutionary scenarios involving recombination. We introduce a new topological feature which has a natural connection to coalescent models, which we call [symbol]. We show that [symbol] and β1 are differentially affected by different evolutionary and empirical scenarios in a given dataset, therefore we use them in conjunction to provide a more efficient, robust, and accurate estimator of recombination rates in a topological model implemented in new software we call TREE. Compared to previous TDA methods, TREE better approximates the results of model-based methods on an empirical dataset, and additionally outperforms previous TDA-based methods on simulated and empirical data. These characteristics make TREE well suited as a first-pass estimator of recombination rate heterogeneity and hotspots throughout the genome. Our work justifies the use of topological statistics as summaries of distributions of genome sequences and describes an unintuitive relationship between topological summaries of genetic distances and the impact of recombination on sequences
Jet characterization in Au + Au collisions at STAR
(2013-05) Dávila Leyva, Alán; Markert, Christina
The present study combines modern jet reconstruction algorithms and particle identification (PID) techniques in order to study the enhancement of proton/pion ratio at mid transverse momentum ([mathematical symbols] 1.5 - 4.0 GeV/c) observed in central Au + Au collisions at [mathematical symbols] = 200 GeV. The ratio enhancement is thought to be caused by recombination processes and/or parton fragmentation modification of jets in relativistic heavy ion collisions. The fragmentation modification hypothesis is tested in this analysis by reconstructing and selecting energetic jets presumably biased to fragment outside of the medium created in Au + Au collisions and comparing their particle composition to the recoiling (medium-traversing) jets. The bias assumption is confirmed by comparing jets in central collisions, where the effect of proton/pion enhancement is present, with peripheral ones where no medium effects are expected. The selected jets are reconstructed by using the anti-k[subscript T] algorithm from the modern FASTJET package. The PID in the p[subscript T] region of interest is possible by combining measurements of the particles' energy deposition and velocity from the Time Projection Chamber and the recently installed (2009-2010) Time of Flight detectors at STAR. The acceptance of these detectors, [eta] < 1.0 and full azimuth, make them extraordinary tools for correlation studies. These features allow for the measurement of relative azimuth ([phi] [subscript jet] - [phi] [subscript pion,proton]) distributions by using the selected jet axis in order to disentangle the uncorrelated background present in the high multiplicity heavy ion collisions. The proton/pion ratios in two different centrality bins and p[subscript T] = 1.2 - 3.0 GeV/c are presented for biased (vacuum fragmenting) jets and their recoiling counterparts
Report on estimating prokaryotic recombination landscapes from genomic data
(2023-08) Golightly, Peter; Baker, Brett J.
Recombination plays a crucial role in the evolution of prokaryotic life. As genomic sequencing data become more widely available, many methods to estimate the rate of recombination have been developed to meet the increasingly high computation demand. Methods for estimating recombination rely on a number of signals resulting from recombination, including differentiation in linkage, phylogeny, and substitution rate. Here, I discuss different signals used to detect recombination, how they are incorporated into current recombination estimation software, and the potential limitations of that software or algorithm. I also discuss which of these methods can be applied to different types of sequencing data. Finally, I provide a detailed description of four commonly used programs for estimating recombination from genomic data in prokaryotes.