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Books on the topic 'Genome wide association studies'

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Published: 4 June 2021
Last updated: 11 January 2025

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1

Torkamaneh, Davoud, and François Belzile, eds. Genome-Wide Association Studies. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2237-7.

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2

Appasani, Krishnarao, ed. Genome-Wide Association Studies. Cambridge: Cambridge University Press, 2015. http://dx.doi.org/10.1017/cbo9781107337459.

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3

Tsunoda, Tatsuhiko, Toshihiro Tanaka, and Yusuke Nakamura, eds. Genome-Wide Association Studies. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8177-5.

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4

Gondro, Cedric, Julius van der Werf, and Ben Hayes, eds. Genome-Wide Association Studies and Genomic Prediction. Totowa, NJ: Humana Press, 2013. http://dx.doi.org/10.1007/978-1-62703-447-0.

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5

Guan, Weihua, ed. Epigenome-Wide Association Studies. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-1994-0.

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6

Stram, Daniel O. Design, Analysis, and Interpretation of Genome-Wide Association Scans. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-9443-0.

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7

Prabhu, Snehit. Computational Contributions Towards Scalable and Efficient Genome-wide Association Methodology. [New York, N.Y.?]: [publisher not identified], 2013.

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8

Zhang, Qiangfeng Cliff. Towards the integration of structural and systems biology: Structure-based studies of protein-protein interactions on a genome-wide scale. [New York, N.Y.?]: [publisher not identified], 2012.

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9

Gloyn, Anna L., and Mark I. McCarthy. Genetics in diabetes: Type 2 diabetes and related traits. Basel: Karger, 2014.

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10

International Association for Time Use Research. Conference. Time use studies world wide: A collection of papers presented at the 1989 Varna Conference of the International Association for Time Use Research. Edited by Gershuny Jonathan. Sofia, Bulgaria: Socioconsult Ltd., 1989.

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11

Genome-Wide Association Studies. Springer, 2023.

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12

Genome-Wide Association Studies. Springer Singapore Pte. Limited, 2020.

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13

Tanaka, Toshihiro, Yusuke Nakamura, and Tatsuhiko Tsunoda. Genome-Wide Association Studies. Springer, 2019.

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14

Tanaka, Toshihiro, Yusuke Nakamura, and Tatsuhiko Tsunoda. Genome-Wide Association Studies. Springer, 2019.

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15

Torkamaneh, Davoud, and François Belzile. Genome-Wide Association Studies. Springer, 2022.

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16

Gondro, Cedric, Julius van der Werf, and Ben Hayes. Genome-Wide Association Studies and Genomic Prediction. Humana Press, 2017.

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17

Hu, Ting, Ryan Urbanowicz, and Christian Darabos, eds. Machine Learning in Genome-Wide Association Studies. Frontiers Media SA, 2020. http://dx.doi.org/10.3389/978-2-88966-229-6.

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18

Media, Springer Science+Business, ed. Genome-wide association studies and genomic prediction. Humana Press, 2013.

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19

Fardo, David William. Statistical issues in genome-wide association studies. 2008.

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20

Appasani, Krishnarao, Stephen W. Scherer, and Peter M. Visscher. Genome-Wide Association Studies: From Polymorphism to Personalized Medicine. Cambridge University Press, 2016.

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21

Appasani, Krishnarao, Stephen W. Scherer, and Peter M. Visscher. Genome-Wide Association Studies: From Polymorphism to Personalized Medicine. Cambridge University Press, 2015.

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22

Cheng, Riyan, Lide Han, Hailan Liu, Min Zhang, and Guolian Kang, eds. Statistical Methods, Computing, and Resources for Genome-Wide Association Studies. Frontiers Media SA, 2021. http://dx.doi.org/10.3389/978-2-88971-212-0.

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23

Xihong, Lin, Lin Xihong, Kraft Peter, and Robins James, eds. SNP-set Tests for Sequencing and Genome-Wide Association Studies. 2014.

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24

Yang, Sheng, Shiquan Sun, Xiang Zhou, and Yang Zhao, eds. Integrative Analysis of Genome-Wide Association Studies and Single-Cell Sequencing Studies. Frontier Media SA, 2021. http://dx.doi.org/10.3389/978-2-88971-467-4.

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25

Cooley, Philip Chester. Methods in Statistical Genomics: In the Context of Genome-Wide Association Studies. RTI International, 2016. http://dx.doi.org/10.3768/rtipress.2016.bk.0016.1608.

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26

Cooley, Philip Chester. Methods in Statistical Genomics: In the Context of Genome-Wide Association Studies. RTI International / RTI Press, 2016.

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27

GWAS : the Rise of Hypothesis-Free Biomedical Science: Could Genome-Wide Association Studies Transform Modern Medicine? Elsevier Science & Technology Books, 2016.

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28

Hinks, Anne, and Wendy Thomson. Genetics of juvenile rheumatic diseases. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199642489.003.0043_update_002.

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Juvenile rheumatic diseases are heterogeneous, complex genetic diseases; to date only juvenile idiopathic arthritis (JIA) has been extensively studied in terms of identifying genetic risk factors. The MHC region is a well-established risk factor but in the last few years candidate gene and large-scale genome-wide association studies have been utilized in the search for non-HLA risk factors. There are now 17 JIA susceptibility loci which reach the genome-wide significance threshold for association and a further 7 regions with evidence for association in more than one study. In addition, some subtype-specific associations are emerging. These risk loci now need to be investigated further using fine-mapping strategies and then appropriate functional studies to show how the variant alters the gene function. This knowledge will not only lead to a better understanding of disease pathogenesis for juvenile rheumatic diseases but may also aid in the classification of these heterogeneous diseases. It may identify new pathways for potential therapeutic targets and help in the prediction of disease outcome and response to treatment.
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29

Hinks, Anne, and Wendy Thomson. Genetics of juvenile rheumatic diseases. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199642489.003.0043_update_003.

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Juvenile rheumatic diseases are heterogeneous, complex genetic diseases; to date only juvenile idiopathic arthritis (JIA) has been extensively studied in terms of identifying genetic risk factors. The MHC region is a well-established risk factor but in the last few years candidate gene and large-scale genome-wide association studies have been utilized in the search for non-HLA risk factors. There are now 17 JIA susceptibility loci which reach the genome-wide significance threshold for association and a further 7 regions with evidence for association in more than one study. In addition, some subtype-specific associations are emerging. These risk loci now need to be investigated further using fine-mapping strategies and then appropriate functional studies to show how the variant alters the gene function. This knowledge will not only lead to a better understanding of disease pathogenesis for juvenile rheumatic diseases but may also aid in the classification of these heterogeneous diseases. It may identify new pathways for potential therapeutic targets and help in the prediction of disease outcome and response to treatment.
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30

Siebert, Stefan, Sengupta Raj, and Alexander Tsoukas. The genetics of axial spondyloarthritis. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198755296.003.0004.

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Family and twin studies have long suggested a large genetic component in ankylosing spondylitis (AS). The genetic association with HLA-B27 remains one of the strongest single gene variant associations reported in any complex polygenic disease. The exact mechanism by which HLA-B27 contributes to AS remains unknown, with three main theories proposed: the arthritogenic peptide, endoplasmic reticulum stress with unfolded protein response, and homodimerization theories. Genome-wide association studies have identified a number of other important susceptibility genes for AS, several of which overlap with other spondyloarthritis conditions. Of these, ERAP1 and IL-23R, are covered in more detail, highlighting their functional importance.
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31

Hinks, Anne, and Wendy Thomson. Genetics of juvenile rheumatic diseases. Oxford University Press, 2013. http://dx.doi.org/10.1093/med/9780199642489.003.0043.

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Juvenile rheumatic diseases are heterogeneous, complex genetic diseases; to date only juvenile idiopathic arthritis (JIA) has been extensively studied in terms of identifying genetic risk factors. The MHC region is a well-established risk factor but in the last few years candidate gene and genome-wide association studies have been utilized in the search for non-HLA risk factors. There are now an additional 12 JIA susceptibility loci with evidence for association in more than one study. In addition, some subtype-specific associations are emerging. These risk loci now need to be investigated further using fine-mapping strategies and then appropriate functional studies to show how the variant alters the gene function. This knowledge will not only lead to a better understanding of disease pathogenesis for juvenile rheumatic diseases but may also aid in the classification of these heterogeneous diseases. It may identify new pathways for potential therapeutic targets and help in the prediction of disease outcome and response to treatment.
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32

Harold, Denise, and Julie Williams. Molecular genetics and biology of dementia. Oxford University Press, 2013. http://dx.doi.org/10.1093/med/9780199644957.003.0008.

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Considerable progress has been made in our understanding of the genetics and molecular biology of dementia. In this chapter we focus predominantly on the most common form of dementia, Alzheimer’s disease (AD), but also discuss vascular dementia and frontotemporal dementia. Genetic mutations have been identified that cause Mendelian subtypes of each disorder, and in recent years genome-wide association studies have greatly aided the identification of risk genes for more common forms of disease. For example, 9 susceptibility genes have been identified in AD in the past 3 years as a result of genome-wide association studies, the first robust risk loci to be identified since APOE in 1993. This progress in genetic research is having a dramatic effect on our understanding of disease pathogenesis, by refining previous ideas and defining new primary disease mechanisms.
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33

Xiang, Ruidong, Hao Cheng, Lingzhao Fang, Zhe Zhang, and Marie-Pierre Sanchez, eds. Multi-Layered Genome-Wide Association/Prediction in Animals. Frontiers Media SA, 2022. http://dx.doi.org/10.3389/978-2-88976-047-3.

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34

Purcell, Shaun M. Genetic Methodologies and Applications. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0001.

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Mental illness is highly heritable, yet it has been difficult historically to identify the specific genes that comprise that risk. This difficulty resides in the fact that the genetic risk for all common mental disorders is polygenic, with perhaps hundreds of genetic variations, each of small effect, contributing to the overall risk. Despite these challenges, the field has made dramatic advances over the past decade in beginning to understand the genetic basis of mental illness. This chapter provides an overview of the experimental approaches used, beginning with epidemiology and population genetics to define the heritability of an illness, to classic studies of large families and linkage disequilibrium analysis, to genome-wide investigations including genome-wide association studies (GWAS), exome sequencing, and whole genome sequencing. Increasingly, these genetic advances are being understood within the biological context of disease pathophysiology.
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35

Otowa, Takeshi, Roxann Roberson-Nay, Mandakh Bekhbat, Gretchen N. Neigh, and John M. Hettema. Genetics of Anxiety Disorders. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0033.

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This chapter provides a broad overview of the state of research in the genetics of the major anxiety disorders (ADs). They exhibit moderate familial aggregation and heritability due to genetic risk factors that are shared between them as well as those that are disorder-specific. Many candidate gene association studies have been published, with a small set of genes that have been consisted validated for their role in one or more anxiety phenotypes. Genome-wide association studies of ADs are in their infancy, with a handful of published studies for each disorder so far and more to come conducted by large consortia. Animal studies provide a promising complimentary approach that demonstrate concurring evidence across species supporting the involvement of particular biological systems in anxiety-related behaviors.
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36

Ismail, Khalida, Calum D. Moulton, Andrea Danese, and Brenda W. Penninx. A life course approach to understanding the association between depression and type 2 diabetes. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198789284.003.0002.

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The relationship between depression and type 2 diabetes is bidirectional and poorly explained by behavioural factors alone. Chronic activation of the innate immune system provides a promising mechanism by which both conditions could develop concurrently across the life course. Genetically, overlap between depression and type 2 diabetes has been reported by twin studies, although not yet at the genome-wide significance level. In utero, activation of inflammatory processes may impact on neurodevelopment of appetite and mood regulation. In early childhood, prolonged adversity is associated with subsequent elevated inflammation, depression, and obesity, which may be amplified by unhealthy lifestyle choices in adolescence. Finally, prolonged low socioeconomic status into adulthood is associated with chronically elevated inflammation and incident type 2 diabetes. In sum, a lifespan approach to the comorbidity of depression and type 2 diabetes offers novel opportunities for timely intervention and even for the primary prevention of type 2 diabetes.
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37

Levinson, Douglas F., and Walter E. Nichols. Genetics of Depression. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0024.

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Major depressive disorder (MDD) is a common and heterogeneous complex trait. Twin heritability is 35%–40%, perhaps higher in severe/recurrent cases. Adverse life events (particularly during childhood) increase risk. Current evidence suggests some overlap in genetic factors among MDD, bipolar disorder, and schizophrenia. Large genome-wide association studies (GWAS) are now proving successful. Polygenic effects of common SNPs are substantial. Findings implicate genes with effects on synaptic development and function, including two obesity-associated genes (NEGR1 and OLFM4), but not previous “candidate genes.” It can now be expected that larger GWAS samples will produce additional associations that shed new light on MDD genetics.
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38

Siebert, Stefan, Sengupta Raj, and Alexander Tsoukas. A brief history of ankylosing spondylitis. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198755296.003.0002.

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The history of ankylosing spondylitis (AS) dates back to the discovery of skeletons with characteristic spinal changes. The disease was further defined by correlating pathological and clinical features, and the development of clinical radiology. Subsequent epidemiology and familial studies highlighted the association with other related conditions as part of the spondyloarthritides. The discovery of HLA-B27 confirmed this association. Over the past two decades, genome-wide association studies, and advances in imaging and immunology have yielded dramatic insights into the disease and the development of highly effective therapies.
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39

Stram, Daniel O. Design, Analysis, and Interpretation of Genome-Wide Association Scans. Springer, 2016.

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40

Stram, Daniel O. Design, Analysis, and Interpretation of Genome-Wide Association Scans. Springer, 2013.

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41

Stram, Daniel O. Design, Analysis, and Interpretation of Genome-Wide Association Scans. Springer London, Limited, 2013.

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42

Stram, Daniel O. Design, Analysis, and Interpretation of Genome-Wide Association Scans. Springer, 2013.

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43

Kan, Carol, and Ma-Li Wong. Genetics. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198789284.003.0004.

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An association between type 2 diabetes mellitus (T2DM) and depression has been reported in epidemiological studies. Finding a genetic overlap between T2DM and depression will provide evidence to support a common biological pathway to both disorders. Genetic correlations observed from twin studies indicate that a small magnitude of the variance in liability can be attributed to genetic factors. However, no genetic overlap has been observed between T2DM and depression in genome-wide association studies using both the polygenic score and the linkage disequilibrium score regression approaches. Clarifying the shared heritability between these two complex traits is an important next step towards better therapy and treatment. Another area that needs to be explored is gene–environment interaction, since genotypes can affect an individual’s responses to the environment and environment can differentially affect genotypes expression.
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44

Dalbeth, Nicola. Clinical features of gout. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198748311.003.0005.

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About 60% of the variance in serum urate levels can be explained by inherited genetic factors, but the extent of the contribution of genetic factors to gout in the presence of hyperuricaemia is not known. Genome-wide association studies in Europeans have identified 28 loci controlling serum urate levels, although the molecular basis of the majority of these genetic associations is currently unknown. The SLC2A9 and ABCG2 renal and gut uric acid transporters have very strong effects on urate levels and the risk of gout. Other uric acid transporters (e.g. SLC22A11/OAT478, SLC22A12/URAT1) and a glycolysis gene (GCKR) are associated with urate levels. Environmental exposures such as sugar-sweetened beverages and alcohol interact with urate-associated genetic variants in an unpredictable fashion. Very little is known about the genetic control of gout in the presence of hyperuricaemia, formation of monosodium urate crystals, and the immune response.
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45

Distel, Marijn A., and Marleen H. M. de Moor. Genetic Influences on Borderline Personality Disorder. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199997510.003.0007.

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Borderline personality disorder (BPD) tends to “run in families.” Twin and twin family studies show that BPD is moderately heritable, with some evidence for nonadditive gene action. BPD co-occurs with Axis I and other Axis II disorders, as well as with a certain profile of normal personality traits. Multivariate twin (family) studies have shown that these phenotypic associations are partly due to genetic associations, and this is observed most strongly for BPD and neuroticism. Candidate gene-finding studies for BPD suggest the possible role of genes in the serotonergic and dopaminergic system, but this needs to be confirmed in larger genome-wide studies. Future studies will complement the knowledge described in this chapter to enable us to move toward a comprehensive model of the development of BPD in which biological and environmental influences on BPD are integrated.
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46

Sumner, Jennifer A., Angela C. Bustamante, Karestan C. Koenen, and Monica Uddin. Genetics of PTSD. Edited by Israel Liberzon and Kerry J. Ressler. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780190215422.003.0011.

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Trauma exposure and PTSD are heritable. However, the mechanisms of risk and resilience following trauma exposure are not yet well understood, suggesting that investigations into the genetic architecture of PTSD have much to contribute. This chapter reviews the rapidly growing literature on molecular genetic risk factors for PTSD, including findings from candidate gene and genome-wide association studies. Given the critical role of trauma exposure in the onset of PTSD, it also discusses gene-environment interplay, and highlights some recent findings from epigenetic studies. The chapter concludes by summarizing considerations for the field as it continues to move forward, and discusses exciting new developments in the search for genetic markers for PTSD.
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47

Goldman, David, Zhifeng Zhou, and Colin Hodgkinson. The Genetic Basis of Addictive Disorders. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0042.

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Addictive disorders are moderately to highly heritable, indicating that alleles transmitted from parents are protective, or enhance risk by whatever mechanisms. However, the inheritance of addictive disorders is complex, involving hundreds of genes and variants that are both common and rare, and that vary in effect size and context of action. Genes altering risk for addictions have been identified by pathway and candidate gene studies in humans and model organisms, and genomic approaches including genome-wide association, meiotic linkage, and sequencing. Genes responsible for shared liability to different addictive disorders have been identified, as well as genes that are relatively specific in altering risk of addiction to one agent. An impediment to overarching conclusions is that most of the heritability of addictions is unexplained at the level of gene or functional locus. However, new analytic approaches and tools have created new potentials for resolution of the “missing heritability.”
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48

Beaver, Kevin M., Eric J. Connolly, Joseph L. Nedelec, and Joseph A. Schwartz. On the Genetic and Genomic Basis of Aggression, Violence, and Antisocial Behavior. Edited by Rosemary L. Hopcroft. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190299323.013.15.

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There is a great deal of interest in examining the genetic and environmental architecture to aggression, violence, and antisocial behaviors. This interest has resulted in hundreds of studies being published that estimate genetic and environmental effects on antisocial phenotypes. The results generated from these studies have been remarkably consistent and have contributed greatly to the knowledge base on the etiology of antisocial behavior. This chapter reviews the research on the genetic basis to antisocial phenotypes by presenting the results related to the heritability of antisocial phenotypes. It also discusses some of the molecular genetic association studies as well as genome-wide association studies that focus on the development of antisocial behaviors. In doing so, it also reviews findings related to gene–environment interactions. The chapter concludes by discussing some of the ways in which these findings could be used for intervention and prevention programs.
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49

Haiman, Christopher, and David J. Hunter. Genetic Epidemiology of Cancer. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190676827.003.0004.

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This chapter explores the genetic epidemiology of cancer: the identification and quantification of inherited genetic factors, and their potential interaction with the environment, in the etiology of cancer in human populations. It also describes the techniques used to identify genetic variants that contribute to cancer susceptibility. It describes the older research methods for identifying the chromosomal localization of high-risk predisposing genes, such as linkage analysis within pedigrees and allele-sharing methods, as it is important to understand the foundations of the field. It also reviews the epidemiologic study designs that can be helpful in identifying low-risk alleles in candidate gene and genome-wide association studies, as well as gene–environment interactions. Finally, it describes some of the genotyping and sequencing platforms commonly employed for high-throughput genome analysis, and the concept of Mendelian randomization and how it may be useful in the study of biomarkers and environmental causes of cancer.
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50

Guffanti, Guia, Milissa L. Kaufman, Lauren A. M. Lebois, and Kerry J. Ressler. Genetic Approaches to Post-Traumatic Stress Disorder. Edited by Charles B. Nemeroff and Charles R. Marmar. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190259440.003.0026.

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Post-traumatic stress disorder (PTSD) is a debilitating psychiatric disorder with an estimated genetic component accounting for 30%–40% of the variance contributing to risk for the disease. This chapter starts with a review of the biological hypotheses and related genetic mechanisms currently proposed to be associated with PTSD and trauma-related disorders. It will follow with a description of the state-of-the-art on the methodologies and their application to map genetic loci and identify biomarkers associated with PTSD. Finally, we will review the latest results from genome-wide association studies of genetic variants as well as those derived from the emerging fields of epigenetics and gene expression.
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