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Books on the topic 'Genome-wide analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 March 2023

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1

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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Muley, Vijaykumar Yogesh, and Vishal Acharya. Genome-Wide Prediction and Analysis of Protein-Protein Functional Linkages in Bacteria. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-4705-4.

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3

Bioinformatics: The impact of accurate quantification on proteomic and genetic analysis and research. Toronto: Apple Academic Press, 2014.

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4

Kung, Johnny Tsun-Yi. Genome-wide Analysis of Ctcf-RNA Interactions. 2014.

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5

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

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6

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

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7

Ma, Jun. Genome-wide analysis of human peripheral leukocyte gene expression. 2003.

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8

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

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9

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

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10

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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11

Muley, Vijaykumar Yogesh, and Vishal Acharya. Genome-Wide Prediction and Analysis of Protein-Protein Functional Linkages in Bacteria. Springer, 2012.

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12

Muley, Vijaykumar Yogesh, and Vishal Acharya. Genome-Wide Prediction and Analysis of Protein-Protein Functional Linkages in Bacteria. Springer, 2012.

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13

Bear, Daniel. Genome-wide and single-cell analysis of neuronal activity-regulated gene expression. 2010.

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14

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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15

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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16

The Genetics of Sjogren's Syndrom: Candidate Gene Analyses and Genome-wide Linkage Studies. University of Bergen, 2002.

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17

Suffredini, Anthony F., and J. Perren Cobb. Genetic and molecular expression patterns in critical illness. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0031.

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Investigators who study RNA, proteins, or metabolites use analytic platforms that simultaneously measure changes in the relative abundance of thousands of molecules in a single biological sample. Over the last decade, the application of these high-throughput, genome-wide platforms to study critical illness and injury has generated huge quantities of data that require specialized computational skills for analysis. These investigations hold promise for improving our understanding of the host response, thereby transforming the practice of intensive care. This chapter summarizes recent technological and computational approaches used in genomics, proteomics, and metabolomics. While major advances have been made with these approaches when applied to chronic diseases, the acute nature of critical illness and injury has unique challenges. The rapidity of initiating events, the trajectory of inflammation that follows injury or infection and the interplay of host responses to a replicating infection, all have major effects on changes in gene and molecular expression. This complexity is further accentuated by measurement that may vary with the timing and type of tissue sampled after the critical event. In addition, the hunt for novel molecular markers holds promise for identifying patients at risk for severe illness and for enabling more individualized therapy.

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18

Lewis, Myles, and Tim Vyse. Genetics of connective tissue diseases. Oxford University Press, 2013. http://dx.doi.org/10.1093/med/9780199642489.003.0042.

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The advent of genome-wide association studies (GWAS) has been an exciting breakthrough in our understanding of the genetic aetiology of autoimmune diseases. Substantial overlap has been found in susceptibility genes across multiple diseases, from connective tissue diseases and rheumatoid arthritis (RA) to inflammatory bowel disease, coeliac disease, and psoriasis. Major technological advances now permit genotyping of millions of single nucleotide polymorphisms (SNPs). Group analysis of SNPs by haplotypes, aided by completion of the Hapmap project, has improved our ability to pinpoint causal genetic variants. International collaboration to pool large-scale cohorts of patients has enabled GWAS in systemic lupus erythematosus (SLE), systemic sclerosis and Behçet's disease, with studies in progress for ANCA-associated vasculitis. These 'hypothesis-free' studies have revealed many novel disease-associated genes. In both SLE and systemic sclerosis, identified genes map to known pathways including antigen presentation (MHC, TNFSF4), autoreactivity of B and T lymphocytes (BLK, BANK1), type I interferon production (STAT4, IRF5) and the NFκ‎B pathway (TNIP1). In SLE alone, additional genes appear to be involved in dysregulated apoptotic cell clearance (ITGAM, TREX1, C1q, C4) and recognition of immune complexes (FCGR2A, FCGR3B). Future developments include whole-genome sequencing to identify rare variants, and efforts to understand functional consequences of susceptibility genes. Putative environmental triggers for connective tissue diseases include infectious agents, especially Epstein-Barr virus; cigarette smoking; occupational exposure to toxins including silica; and low vitamin D, due to its immunomodulatory effects. Despite numerous studies looking at toxin exposure and connective tissue diseases, conclusive evidence is lacking, due to either rarity of exposure or rarity of disease.

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19

MacGregor, Alex, Ana Valdes, and Frances M. K. Williams. Genetics of osteoarthritis. Oxford University Press, 2013. http://dx.doi.org/10.1093/med/9780199642489.003.0044.

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In this chapter we outline the approaches which have been adopted to identify genetic variants predisposing to osteoarthritis (OA), a condition long recognized as having a heritable component. Such routes to their identification include examining mendelian traits in which OA is a feature, candidate gene studies based on knowledge of OA pathobiology, linkage analysis in related individuals, and, more recently, genome-wide association studies in large samples of unrelated individuals. It is increasingly evident that the main symptom deriving from OA—notably joint pain—also has a genetic basis but this is differs from that underlying OA. Variants convincingly shown to predispose to OA lie in the GDF5 and MCF2L genes and in the chr7 cluster mapping to the COG5 gene, in addition to the ASPN gene in Asian populations. Those associated with pain in OA include TRPV1 and PACE4. Epigenetic influences are also being explored in both the pathogenesis of OA and the variation of pain processing.

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20

Cutter, Asher D. A Primer of Molecular Population Genetics. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198838944.001.0001.

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The study of molecular population genetics seeks to understand the micro-evolutionary principles underlying DNA sequence variation and change. It addresses such questions as: Why do individuals differ as much as they do in their DNA sequences? What are the genomic signatures of adaptations? How often does natural selection dictate changes to DNA and accumulate as differences between species? How does the ebb and flow in the abundance of individuals over time get marked onto chromosomes to record genetic history? The concepts used to answer such questions also apply to analysis of personal genomics, genome-wide association studies, phylogenetics, landscape and conservation genetics, forensics, molecular anthropology, and selection scans. This Primer of Molecular Population Genetics introduces the bare essentials of the theory and practice of evolutionary analysis through the lens of DNA sequence change in populations. Intended as an introductory text for upper-level undergraduates and junior graduate students, this Primer also provides an accessible entryway for scientists from other areas of biology to appreciate the ideas and practice of molecular population genetics. With the revolutionary advances in genomic data acquisition, understanding molecular population genetics is now a fundamental requirement for today’s life scientists.

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21

Langley, Kate. ADHD genetics. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198739258.003.0003.

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This chapter reviews the evidence suggesting that there is a strong genetic component to ADHD and the efforts to identify the specific genetic factors that might be involved. It discusses the different types of genetic contributions, from common to rare variants, and the evidence that these are involved in the aetiology of the disorder. An overview of the methodological strategies employed, including genome-wide association studies (GWAS), polygenic risk score, and copy number variant (CNV) analyses, is undertaken, as well as discussion of the strengths and pitfalls of such work. The contradictory findings in the field and controversies that arise as a result are also explored. Finally, this chapter considers how the heritability of ADHD and specific genetic factors involved need to be examined in the context of clinical factors such as comorbidity and how these factors affect investigations into the genetics of ADHD.

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22

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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23

Richiardi, Lorenzo, Giovenale Moirano, and Pagona Lagiou. Testicular Cancer. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190676827.003.0021.

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Testicular cancer is highly curable and, though relatively rare, it is the most common cancer among young men. Incidence of testicular cancer has been increasing constantly around the world since the beginning of the twentieth century, but factors responsible for the rise in incidence remain enigmatic. Only few risk factors for testicular cancer are established, including age, ethnic group, cryptorchidism and hypospadias, contralateral testicular cancer, family history, and height. While analytic epidemiologic research has provided numerous etiologic clues, many of them remain tentative. Overwhelming evidence indicates the fundamental importance of environmental factors in the etiology of this enigmatic cancer. Prenatal exposures seem to be instrumental in shaping the risk of testicular cancer, but postnatal exposures acting in childhood, adolescence, and very early adulthood are also important. Testicular cancer has also a strong genetic component that is studied through international collaborations and genome-wide association studies.

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24

Pezzini, Alessandro. Genetics. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198722366.003.0011.

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Ischaemic stroke is a heterogeneous multifactorial disorder. Although epidemiological data from twin and family studies provide substantial evidence for a genetic basis for stroke, the contribution of genetic factors identified so far is small. Large progress has been made in single-gene disorders associated with ischaemic stroke, particularly at young age. By contrast, little is known about the genes associated with multifactorial stroke. The reported genome-wide association studies of ischaemic stroke have shown that no single common genetic variant imparts major risk, but data on early-onset disease are scarce in this regard. Larger studies with samples numbering in the thousands are ongoing to identify common variants with smaller effects on risk. This approach, in addition with new analytic techniques, will likely contribute to the identification of additional genes, novel pathways, and eventually novel therapeutic approaches to cerebrovascular disorders in the near future. The aims of this review are to summarize data on clinical, genetic, and epidemiologic aspects of monogenic conditions associated with juvenile ischaemic stroke, to discuss recent findings and methodological limitations regarding the genetics of sporadic ischaemic stroke in this age category, and to provide a brief overview of the potential future approaches to stroke genetics.

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