Literature DB >> 23956254

Statistical genetics with application to population-based study design: a primer for clinicians.

Joseph Beyene1, Guillaume Pare.   

Abstract

With the completion of the entire human genome sequence and remarkable advances in genotyping technologies, there has been an increased interest in the application of genetics and genomics in biomedical research over the last decade. Large-scale population-based genetic association studies have now become routine and their application to several multifactorial diseases such as cardiovascular disorders has led to the identification of a number of novel susceptibility genes. However, to be able to interpret results from such studies, clinicians need to have a basic understanding of unique concepts and issues related to this fast-moving area of research. In this primer, we provide a broad overview of design, analysis, and methodological issues with a focus on population-based study design.

Entities:  

Keywords:  SNP; Statistical genetics; case-control study; genetic association; quality control

Mesh:

Year:  2013        PMID: 23956254     DOI: 10.1093/eurheartj/eht272

Source DB:  PubMed          Journal:  Eur Heart J        ISSN: 0195-668X            Impact factor:   29.983


  3 in total

Review 1.  Genetic Variation and Response to Neurocritical Illness: a Powerful Approach to Identify Novel Pathophysiological Mechanisms and Therapeutic Targets.

Authors:  Julián N Acosta; Stacy C Brown; Guido J Falcone
Journal:  Neurotherapeutics       Date:  2020-04       Impact factor: 7.620

Review 2.  Genetic underpinnings of cerebral edema in acute brain injury: an opportunity for pathway discovery.

Authors:  Elayna Kirsch; Natalia Szejko; Guido J Falcone
Journal:  Neurosci Lett       Date:  2020-05-26       Impact factor: 3.046

3.  Identification of Structural Variation from NGS-Based Non-Invasive Prenatal Testing.

Authors:  Ondrej Pös; Jaroslav Budis; Zuzana Kubiritova; Marcel Kucharik; Frantisek Duris; Jan Radvanszky; Tomas Szemes
Journal:  Int J Mol Sci       Date:  2019-09-07       Impact factor: 5.923

  3 in total

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