Integrated Genetic Epidemiology of Chagas Disease

Tibayrenc, Michel; Shaw, Marie‐Anne

doi:10.1016/b978-0-12-799942-5.00022-6

Cited by 2 publications

(1 citation statement)

References 113 publications

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“…It is important to point out that the selection of random mutations stands out as one of the main mechanisms of acquiring resistance and represents a relevant phenomenon in viruses that mutate at high frequencies. RNA viruses, for instance, have a mutation rate estimated at 10 −4 per nucleotide per replication [ 1 , 2 ]. In particular, the mutations were classified as variants of concern (VOCs), which included Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), and Delta (B.1.617.2); variants of interest (VOI), comprising Eta (B.1.525), Iota (B.1.126), Kappa (B.1.617.1), Lambda (C.37), Omicron (BA.1), Zeta (P.2 (484 K.V2), and Ihu (B.1.640.1); and variants of alert (VOA) ( , accessed on 1 October 2020) [ 3 , 4 ].…”

Section: Introductionmentioning

confidence: 99%

The Spike Mutants Website: A Worldwide Used Resource against SARS-CoV-2

Romeo

Prandi

Giombini

et al. 2022

IJMS

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A large number of SARS-CoV-2 mutations in a short period of time has driven scientific research related to vaccines, new drugs, and antibodies to combat the new variants of the virus. Herein, we present a web portal containing the structural information, the tridimensional coordinates, and the molecular dynamics trajectories of the SARS-CoV-2 spike protein and its main variants. The Spike Mutants website can serve as a rapid online tool for investigating the impact of novel mutations on virus fitness. Taking into account the high variability of SARS-CoV-2, this application can help the scientific community when prioritizing molecules for experimental assays, thus, accelerating the identification of promising drug candidates for COVID-19 treatment. Below we describe the main features of the platform and illustrate the possible applications for speeding up the drug discovery process and hypothesize new effective strategies to overcome the recurrent mutations in SARS-CoV-2 genome.

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Section: Introductionmentioning

confidence: 99%

The Spike Mutants Website: A Worldwide Used Resource against SARS-CoV-2

Romeo

Prandi

Giombini

et al. 2022

IJMS

View full text Add to dashboard Cite

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Penalized linear mixed models for structured genetic data

Reisetter

Breheny

2021

Genetic Epidemiology

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Many genetic studies that aim to identify genetic variants associated with complex phenotypes are subject to unobserved confounding factors arising from environmental heterogeneity. This poses a challenge to detecting associations of interest and is known to induce spurious associations when left unaccounted for. Penalized linear mixed models (LMMs) are an attractive method to correct for unobserved confounding. These methods correct for varying levels of relatedness and population structure by modeling it as a random effect with a covariance structure estimated from observed genetic data. Despite an extensive literature on penalized regression and LMMs separately, the two are rarely discussed together. The aim of this review is to do so while examining the statistical properties of penalized LMMs in the genetic association setting. Specifically, the ability of penalized LMMs to accurately estimate genetic effects in the presence of environmental confounding has not been well studied. To clarify the important yet subtle distinction between population structure and environmental heterogeneity, we present a detailed review of relevant concepts and methods. In addition, we evaluate the performance of penalized LMMs and competing methods in terms of estimation and selection accuracy in the presence of a number of confounding structures.

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Integrated Genetic Epidemiology of Chagas Disease

Cited by 2 publications

References 113 publications

The Spike Mutants Website: A Worldwide Used Resource against SARS-CoV-2

The Spike Mutants Website: A Worldwide Used Resource against SARS-CoV-2

Penalized linear mixed models for structured genetic data

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