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Detecting individual sites subject to episodic diversifying selection.

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TLDR
It is found that episodic selection is widespread and it is concluded that the number of sites experiencing positive selection may have been vastly underestimated.
Abstract
The imprint of natural selection on protein coding genes is often difficult to identify because selection is frequently transient or episodic, i.e. it affects only a subset of lineages. Existing computational techniques, which are designed to identify sites subject to pervasive selection, may fail to recognize sites where selection is episodic: a large proportion of positively selected sites. We present a mixed effects model of evolution (MEME) that is capable of identifying instances of both episodic and pervasive positive selection at the level of an individual site. Using empirical and simulated data, we demonstrate the superior performance of MEME over older models under a broad range of scenarios. We find that episodic selection is widespread and conclude that the number of sites experiencing positive selection may have been vastly underestimated.

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Detection of a SARS-CoV-2 variant of concern in South Africa.

TL;DR: A newly arisen lineage of SARS-CoV-2 (designated 501Y.V2) was identified in South Africa after the first wave of the epidemic in a severely affected metropolitan area (Nelson Mandela Bay) that is located on the coast of the Eastern Cape province.
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Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil.

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Emergence and rapid spread of a new severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) lineage with multiple spike mutations in South Africa

Houriiyah Tegally, +60 more
- 22 Dec 2020 - 
TL;DR: In this paper, the authors describe a new SARS-CoV-2 lineage (501Y.V2) characterised by eight lineage-defining mutations in the spike protein, including three at important residues in the receptor-binding domain (K417N, E484K and N501Y).
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Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa

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FUBAR : A Fast, Unconstrained Bayesian AppRoximation for inferring selection

TL;DR: This work presents an approximate hierarchical Bayesian method using a Markov chain Monte Carlo (MCMC) routine that ensures robustness against model misspecification by averaging over a large number of predefined site classes, and leaves the distribution of selection parameters essentially unconstrained.
References
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Journal ArticleDOI

Controlling the false discovery rate: a practical and powerful approach to multiple testing

TL;DR: In this paper, a different approach to problems of multiple significance testing is presented, which calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate, which is equivalent to the FWER when all hypotheses are true but is smaller otherwise.
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Evolutionary trees from DNA sequences: A maximum likelihood approach

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Evolutionary Rate at the Molecular Level

TL;DR: Calculating the rate of evolution in terms of nucleotide substitutions seems to give a value so high that many of the mutations involved must be neutral ones.
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Adaptive protein evolution at the Adh locus in Drosophila

TL;DR: A simple statistical test of the neutral protein evolution hypothesis is proposed based on a comparison of the number of amino-acid replacement substitutions to synonymous substitutions in the coding region of a locus, finding that there are more fixed replacement differences between species than expected.
Journal ArticleDOI

Asymptotic Properties of Maximum Likelihood Estimators and Likelihood Ratio Tests under Nonstandard Conditions

TL;DR: In this article, the authors derived the asymptotic distribution of maximum likelihood estimators and likelihood ratio statistics, which is the same as the distribution of the projection of the Gaussian random variable.
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