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Author: Eleftheria Zeggini Publisher: Springer ISBN: 1493928244 Category : Medical Languages : en Pages : 262
Book Description
This book is unique in covering a wide range of design and analysis issues in genetic studies of rare variants, taking advantage of collaboration of the editors with many experts in the field through large-scale international consortia including the UK10K Project, GO-T2D and T2D-GENES. Chapters provide details of state-of-the-art methodology for rare variant detection and calling, imputation and analysis in samples of unrelated individuals and families. The book also covers analytical issues associated with the study of rare variants, such as the impact of fine-scale population structure, and with combining information on rare variants across studies in a meta-analysis framework. Genetic association studies have in the last few years substantially enhanced our understanding of factors underlying traits of high medical importance, such as body mass index, lipid levels, blood pressure and many others. There is growing empirical evidence that low-frequency and rare variants play an important role in complex human phenotypes. This book covers multiple aspects of study design, analysis and interpretation for complex trait studies focusing on rare sequence variation. In many areas of genomic research, including complex trait association studies, technology is in danger of outstripping our capacity to analyse and interpret the vast amounts of data generated. The field of statistical genetics in the whole-genome sequencing era is still in its infancy, but powerful methods to analyse the aggregation of low-frequency and rare variants are now starting to emerge. The chapter Functional Annotation of Rare Genetic Variants is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Author: Eleftheria Zeggini Publisher: Springer ISBN: 1493928244 Category : Medical Languages : en Pages : 262
Book Description
This book is unique in covering a wide range of design and analysis issues in genetic studies of rare variants, taking advantage of collaboration of the editors with many experts in the field through large-scale international consortia including the UK10K Project, GO-T2D and T2D-GENES. Chapters provide details of state-of-the-art methodology for rare variant detection and calling, imputation and analysis in samples of unrelated individuals and families. The book also covers analytical issues associated with the study of rare variants, such as the impact of fine-scale population structure, and with combining information on rare variants across studies in a meta-analysis framework. Genetic association studies have in the last few years substantially enhanced our understanding of factors underlying traits of high medical importance, such as body mass index, lipid levels, blood pressure and many others. There is growing empirical evidence that low-frequency and rare variants play an important role in complex human phenotypes. This book covers multiple aspects of study design, analysis and interpretation for complex trait studies focusing on rare sequence variation. In many areas of genomic research, including complex trait association studies, technology is in danger of outstripping our capacity to analyse and interpret the vast amounts of data generated. The field of statistical genetics in the whole-genome sequencing era is still in its infancy, but powerful methods to analyse the aggregation of low-frequency and rare variants are now starting to emerge. The chapter Functional Annotation of Rare Genetic Variants is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Author: Evangelos Evangelou Publisher: Humana Press ISBN: 9781493978670 Category : Medical Languages : en Pages : 299
Book Description
This volume details fast-moving research while providing in-depth descriptions of methods and analytical approaches that are helping to understand the genome and how it is related to complex diseases. Chapters guide the reader through common and rare variation, gene-gene and gene-environment interactions and state-of-the-art approaches for the synthesis of genome-wide and gene expression data. Novel approaches for associations in the HLA region, family-based designs, Mendelian Randomization and Copy Number Variation are also presented. The volume concludes with the challenges researchers face while moving from identifying variants to their functional role and potential drug targets. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, a thorough presentation of methods and approaches and tips on troubleshooting and avoiding known pitfalls.
Author: Guhan Ram Venkataraman Publisher: ISBN: Category : Languages : en Pages :
Book Description
Complex diseases are a significant global burden, accounting for 70% of deaths in the U.S. annually. For example, 70,000 new cases of inflammatory bowel disease are diagnosed every year. Many such diseases have underlying genetic etiologies responsible for their pathology. Understanding their genetic basis could lead to more timely diagnosis and improved prognosis. Furthermore, human genetics presents an opportunity to identify new therapeutic targets. However, while much of the disease-causative common variation is well-documented, our understanding of rare, disease-contributory variation is sparse, largely due to the lack of power (limited sample size) and ascertainment to detect such variation with accuracy. While the above goal of understanding rare variation is not achievable with small cohort (n
Author: Tim Bernard Bigdeli Publisher: ISBN: Category : Languages : en Pages :
Book Description
Etiological models of complex disease are elusive[46, 33, 9], as are consistently replicable findings for major genetic susceptibility loci[54, 14, 15, 24]. Commonly-cited explanations invoke low-frequency genomic variation[41], allelic heterogeneity at susceptibility loci[33, 30], variable etiological trajectories[18, 17], and epistatic effects between multiple loci; these represent among the most methodologically-challenging issues in molecular genetic studies of complex traits. The response has been con- sistently reactionary -- hypotheses regarding the relative contributions of known functional elements, or emphasizing a greater role of rare variation[46, 33] have undergone periodic revision, driving increasingly collaborative efforts to ascertain greater numbers of participants and which assay a rapidly-expanding catalogue of human genetic variation. Major deep-sequencing initiatives, such as the 1,000 Genomes Project, are currently identifying human polymorphic sites at frequencies previously unassailable and, not ten years after publication of the first major genome-wide association findings, re-sequencing has already begun to displace GWAS as the standard for genetic analysis of complex traits. With studies of complex disease primed for an unprecedented survey of human genetic variation, it is essential that human geneticists address several prominent, problematic aspects of this research. Realizations regarding the boundaries of human traits previously considered to be effectively disparate in presentation[44, 39, 35, 27, 25, 12, 4, 13], as well as profound insight into the extent of human genetic diversity[23, 22] are not without consequence. Whereas the resolution of fine-mapping studies have undergone persistent refinement, recent polygenic findings suggest a less discriminant basis of genetic liability, raising the question of what a given, unitary association finding actually represents. Furthermore, realistic expectations regarding the pattern of findings for a particular genetic factor between or even within populations remain unclear. Of interest herein are methodologies which exploit the finite extent of genomic variability within human populations to distinguish single-point and cumulative group differences in liability to complex traits, the range of allele frequencies for which common association tests are appropriate, and the relevant dimensionality of common genetic variation within ethnically-concordant but differentially ascertained populations. Using high-density SNP genotype data, we consider both hypothesis-driven and agnostic (genome-wide) approaches to association analysis, and address specific issues pertaining to empirical significance and the statistical properties of commonly- applied tests. Lastly, we demonstrate a novel perspective of genome-wide genetic "background" through exhaustive evaluation of fundamental, stochastic genetic processes in a sample of matched affected and unaffected siblings selected from high- density schizophrenia families.
Author: Lingyu Zhan Publisher: ISBN: Category : Languages : en Pages : 260
Book Description
For recent advancements in sequencing technologies, genetic information can be obtained from a large population at a relatively low cost. This provides an unprecedented opportunity to understand the role of genetic variability in association with complex human traits. One common strategy is to conduct genome-wide association studies to identify loci significantly associated with phenotypes of interest. However, the findings are usually limited to common variants with small effect sizes. Collectively, these identified loci can not fully explain the observed heritability, which is a problem commonly referred to as "the missing heritability." To uncover this problem, human genetic research has shifted more focus to other types of genetic variations, including rare variants, which is further capacitated and facilitated by the next-generation sequencing technique. These rare mutations are believed to harbor large effect sizes and, therefore to be one of the major contributors to complex traits.Here, we describe our effort in analyzing the effect of rare variants in two complex human traits, Alzheimer's Disease and Tourette Syndrome, followed by conducting a genome-wide association study on human blood lipids. Exploring large whole-genome sequencing datasets, we have first demonstrated that rare variants were strongly associated with Alzheimer's Disease, neurofibrillary tangles, and age-related phenotypes within the endocytic pathway using a gene-set burden analysis framework. Subsequent gene-based analyses identified one AD-associated gene, ANKRD13D, and two e-Genes, HLA-A and SLC26A7. Leveraging bulk and scRNA-Seq data, we observed significant differential expression patterns in all three implicated genes. Secondly, we have explored a specific type of rare variants, de novo mutations, within Tourette Syndrome patients using a whole-exome sequencing trio dataset and identified a recurrent mutation in one gene, FBN2, previously implicated in TS. Comparing to the expected mutation rate, we demonstrated that the protein-truncating variants were enriched in probands. In addition, gene-set analysis displayed differential expression patterns across different tissue types and brain developmental stages. Lastly, we have performed a multi-population meta-analysis on blood lipid levels using electronic health records and genotyping information from the UCLA ATLAS database. We have observed genetic effects both specific to and shared across five different populations. Compared to previous large-scale GWASes, our results demonstrated consistent effect estimates while identifying one novel locus, rs72552763.
Author: National Research Council Publisher: National Academies Press ISBN: 0309108675 Category : Social Science Languages : en Pages : 429
Book Description
Biosocial Surveys analyzes the latest research on the increasing number of multipurpose household surveys that collect biological data along with the more familiar interviewerâ€"respondent information. This book serves as a follow-up to the 2003 volume, Cells and Surveys: Should Biological Measures Be Included in Social Science Research? and asks these questions: What have the social sciences, especially demography, learned from those efforts and the greater interdisciplinary communication that has resulted from them? Which biological or genetic information has proven most useful to researchers? How can better models be developed to help integrate biological and social science information in ways that can broaden scientific understanding? This volume contains a collection of 17 papers by distinguished experts in demography, biology, economics, epidemiology, and survey methodology. It is an invaluable sourcebook for social and behavioral science researchers who are working with biosocial data.
Author: Gregory Connor Publisher: Cambridge Scholars Publishing ISBN: 1527575675 Category : Education Languages : en Pages : 360
Book Description
This book is an edited collection of recently published papers on the sources of average test score gaps when analysed through the lenses of race and ethnicity, socio-economic status, and biogeographic ancestries such as European, African, and East Asian ancestry. It brings together exciting recent findings that rely on powerful DNA-based methods developed in the last few decades. The book also considers the public policy question as to whether, and how, these findings should be disseminated to the general public audience.
Author: Diego A. Forero Publisher: CRC Press ISBN: 1000405672 Category : Science Languages : en Pages : 374
Book Description
Advances in high-throughput biological methods have led to the publication of a large number of genome-wide studies in human and animal models. In this context, recent tools from bioinformatics and computational biology have been fundamental for the analysis of these genomic studies. The book Bioinformatics and Human Genomics Research provides updated and comprehensive information about multiple approaches of the application of bioinformatic tools to research in human genomics. It covers strategies analysis of genome-wide association studies, genome-wide expression studies and genome-wide DNA methylation, among other topics. It provides interesting strategies for data mining in human genomics, network analysis, prediction of binding sites for miRNAs and transcription factors, among other themes. Experts from all around the world in bioinformatics and human genomics have contributed chapters in this book. Readers will find this book as quite useful for their in silico explorations, which would contribute to a better and deeper understanding of multiple biological processes and of pathophysiology of many human diseases.
Author: Eleftheria Zeggini
Author: Eleftheria Zeggini
Author: Evangelos Evangelou
Author: Guhan Ram Venkataraman
Author: International Conference on Quantitative Genetics
Author: Tim Bernard Bigdeli
Author: Lingyu Zhan
Author: National Research Council
Author: Gregory Connor
Author: 
Author: Diego A. Forero