標(biāo)題: Titlebook: Genetic Epidemiology; Methods and Protocol Evangelos Evangelou Book 2018 Springer Science+Business Media, LLC, part of Springer Nature 2018 [打印本頁] 作者: cerebral 時(shí)間: 2025-3-21 17:01
書目名稱Genetic Epidemiology影響因子(影響力)
書目名稱Genetic Epidemiology影響因子(影響力)學(xué)科排名
書目名稱Genetic Epidemiology網(wǎng)絡(luò)公開度
書目名稱Genetic Epidemiology網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Genetic Epidemiology被引頻次
書目名稱Genetic Epidemiology被引頻次學(xué)科排名
書目名稱Genetic Epidemiology年度引用
書目名稱Genetic Epidemiology年度引用學(xué)科排名
書目名稱Genetic Epidemiology讀者反饋
書目名稱Genetic Epidemiology讀者反饋學(xué)科排名
作者: 銀版照相 時(shí)間: 2025-3-21 22:07 作者: 為現(xiàn)場 時(shí)間: 2025-3-22 02:29
https://doi.org/10.1007/978-1-4939-7868-7Genome variation; Multivariate; genetic epidemiology; polygenic traits; Mendelian Randomization作者: enterprise 時(shí)間: 2025-3-22 04:57
Medienkonzentration und Medienkonzerneion by determining both exposures and outcomes at one time point. Cohort studies identify the study groups based on the exposure and, then, the researchers follow up study participants to measure outcomes. Case-control studies identify the study groups based on the outcome, and the researchers retro作者: 平常 時(shí)間: 2025-3-22 12:25
Nationale und internationale Filmproduktiont emerged in the mid-1980s bringing together approaches and techniques developed in mathematical and quantitative genetics, medical and population genetics, statistics and epidemiology. The purpose of this chapter is to familiarize the reader with key concepts in genetic epidemiology as applied at p作者: Needlework 時(shí)間: 2025-3-22 13:36
https://doi.org/10.1007/978-3-642-86069-0a and thresholds have been established for data QC at the sample and variant level. Sample QC is aimed at the identification and removal (when appropriate) of individuals with (1) low call rate, (2) discrepant sex or other identity-related information, (3) excess genome-wide heterozygosity and homoz作者: Needlework 時(shí)間: 2025-3-22 18:01
Michael Fischer M.Sc., Dipl.-Krim.nome-wide association studies (GWAS). In this chapter, we review the key concepts that underlie the GWAS approach. We will describe the “common disease, common variant” theory, and will review how we finally afforded to capture the common variance in genome to make GWAS possible. Finally, we will go作者: 廢止 時(shí)間: 2025-3-23 00:12
Problemstellung und Untersuchungskonzeption, rarer frequency spectrum of the genome has not yet been comprehensively explored. Technological developments increasingly lift restrictions to access rare genetic variation. Dense reference panels enable improved genotype imputation for rarer variants in studies using DNA microarrays. Moreover, the作者: PRO 時(shí)間: 2025-3-23 01:31
https://doi.org/10.1007/978-3-642-92786-7dies, and is extensively used in the genomic analyses of complex traits. Estimates from different studies are combined and the results effectively provide the power of a much larger study. Meta-analysis also has the potential of discovering heterogeneity in the effects among the different studies. T作者: RAG 時(shí)間: 2025-3-23 06:01
https://doi.org/10.1007/978-3-211-76520-3e been made in identifying genetic variants associated with complex traits through more dense panels of genetic variants and larger sample sizes, genome-wide interaction analyses are still limited in power to detect interactions with small effect sizes, rare frequencies, and higher order interaction作者: Conjuction 時(shí)間: 2025-3-23 11:34
https://doi.org/10.1007/978-3-662-26053-1forts to pinpoint drivers of this commonly encountered association peak at the short arm of chromosome 6, however, have been challenging, owing to the high density of genes and the long and extended linkage disequilibrium that are characteristic of this region..The development of methods to impute c作者: floaters 時(shí)間: 2025-3-23 16:43
Das Methoden-Repertoire von Lehrerntion studies (GWAS) have successfully identified many genetic markers related to human diseases, the traditional statistical methods are not powerful to detect rare genetic markers. The rare genetic markers are usually grouped together and tested at the set level. One of such methods is the sequence作者: CULP 時(shí)間: 2025-3-23 20:11
https://doi.org/10.1007/978-3-531-91774-0ntive strategies will eventually decrease burden of diseases and thus precise prediction plays a crucial role in public health. Many investigators put efforts into finding models that improve prediction using known risk factors of diseases. Recently with the overwhelming load of genetic loci discove作者: 吵鬧 時(shí)間: 2025-3-24 02:03 作者: leniency 時(shí)間: 2025-3-24 03:02
Das Mikroskop und Seine Anwendung,s and study the effects of certain treatments, diseases, and developmental stages. The traditional way to perform such experiments is to design oligonucleotide hybridization probes that correspond to specific genes and then measure the expression of the genes in order to determine which of them are 作者: Generic-Drug 時(shí)間: 2025-3-24 10:15
Das zusammengesetzte Mikroskop,vational epidemiology. The advent of genome-wide association studies and the increasing accumulation of summarized data from large genetic consortia make MR a powerful technique. In this review, we give a primer in MR methodology, describe efficient MR designs and analytical strategies, and focus on作者: conscribe 時(shí)間: 2025-3-24 12:08 作者: 異端邪說2 時(shí)間: 2025-3-24 17:53 作者: 生意行為 時(shí)間: 2025-3-24 21:54 作者: aplomb 時(shí)間: 2025-3-25 01:27 作者: Mammal 時(shí)間: 2025-3-25 05:18 作者: Watemelon 時(shí)間: 2025-3-25 09:34 作者: insular 時(shí)間: 2025-3-25 13:09 作者: EVADE 時(shí)間: 2025-3-25 19:07 作者: 友好關(guān)系 時(shí)間: 2025-3-25 22:23
https://doi.org/10.1007/978-3-642-86069-0uilibrium (HWE), (4) bad genotype intensity plots, (5) batch effects, (6) differences in allele frequencies with published data sets, (7) very low minor allele counts?(MAC), (8) low imputation quality score, (9) low variant quality score log-odds, and (10) few or low quality reads.作者: Axon895 時(shí)間: 2025-3-26 01:12 作者: 恩惠 時(shí)間: 2025-3-26 04:36 作者: Airtight 時(shí)間: 2025-3-26 10:42
Quality Control of Common and Rare Variants,uilibrium (HWE), (4) bad genotype intensity plots, (5) batch effects, (6) differences in allele frequencies with published data sets, (7) very low minor allele counts?(MAC), (8) low imputation quality score, (9) low variant quality score log-odds, and (10) few or low quality reads.作者: 協(xié)奏曲 時(shí)間: 2025-3-26 13:09 作者: 伸展 時(shí)間: 2025-3-26 18:55
Methods for Polygenic Traits, effect of as many genetic loci as possible. Such new parameters aim to better distinguish individuals who will develop a disease from those who will not. In this chapter, various polygenic methods that use multiple genetic loci to directly or indirectly improve precision of genetic prediction are discussed.作者: 棲息地 時(shí)間: 2025-3-27 01:02 作者: Cleave 時(shí)間: 2025-3-27 02:55
https://doi.org/10.1007/978-3-642-92786-7his chapter provides an overview of the methods used for meta-analysis of common and rare single variants and also for gene/region-based analyses; common variants are mainly identified via genome-wide association studies (GWAS) and rare variants through various types of sequencing experiments.作者: 他姓手中拿著 時(shí)間: 2025-3-27 06:46 作者: 死貓他燒焦 時(shí)間: 2025-3-27 13:10
Die mechanische Einrichtung des Mikroskopss challenges that are usually overlooked in traditional gene mapping. This chapter describes some of the most common challenges and opportunities to use human genetics to identify and validate novel drug targets.作者: Kaleidoscope 時(shí)間: 2025-3-27 17:24 作者: 大氣層 時(shí)間: 2025-3-27 21:35
Meta-Analysis of Common and Rare Variants,his chapter provides an overview of the methods used for meta-analysis of common and rare single variants and also for gene/region-based analyses; common variants are mainly identified via genome-wide association studies (GWAS) and rare variants through various types of sequencing experiments.作者: CESS 時(shí)間: 2025-3-27 22:20
A Primer in Mendelian Randomization Methodology with a Focus on Utilizing Published Summary Associa methods and practical guidance for conducting an MR study using summary association data. We show that the analysis is straightforward utilizing either the MR-base platform or available packages in R. However, further research is required for the development of specialized methodology to assess MR assumptions.作者: tenuous 時(shí)間: 2025-3-28 03:01 作者: allude 時(shí)間: 2025-3-28 07:35 作者: hereditary 時(shí)間: 2025-3-28 11:24 作者: Pcos971 時(shí)間: 2025-3-28 16:57
Genome-Wide Association Studies,e, common variant” theory, and will review how we finally afforded to capture the common variance in genome to make GWAS possible. Finally, we will go over technical aspects of GWAS such as genotype imputation, epidemiologic designs, analysis methods, and considerations such as genomic inflation, multiple testing, and replication.作者: prodrome 時(shí)間: 2025-3-28 20:45
Das Methoden-Repertoire von Lehrerne applicable for family-based rare variant analysis. Here, I present three published statistical approaches for family-based rare variant analysis for: 1. continuous traits, 2. binary traits, and 3. multiple correlated traits.作者: 匍匐 時(shí)間: 2025-3-29 01:47 作者: 大猩猩 時(shí)間: 2025-3-29 05:16
Novel Methods for Family-Based Genetic Studies,e applicable for family-based rare variant analysis. Here, I present three published statistical approaches for family-based rare variant analysis for: 1. continuous traits, 2. binary traits, and 3. multiple correlated traits.作者: Junction 時(shí)間: 2025-3-29 08:19
From Identification to Function: Current Strategies to Prioritise and Follow-Up GWAS Results,evelop better preventive and curative strategies? Current efforts are shifting to focus on these questions as we move from identifying variants to understanding their effects. Here I provide a broad overview of the main technical concerns and current bottlenecks as we approach this new phase.作者: 油氈 時(shí)間: 2025-3-29 15:09 作者: 百靈鳥 時(shí)間: 2025-3-29 16:43 作者: 絕緣 時(shí)間: 2025-3-29 20:58 作者: Negligible 時(shí)間: 2025-3-30 00:47
Genome-Wide Association Studies,nome-wide association studies (GWAS). In this chapter, we review the key concepts that underlie the GWAS approach. We will describe the “common disease, common variant” theory, and will review how we finally afforded to capture the common variance in genome to make GWAS possible. Finally, we will go作者: 我們的面粉 時(shí)間: 2025-3-30 05:39 作者: PRISE 時(shí)間: 2025-3-30 08:57
Meta-Analysis of Common and Rare Variants,dies, and is extensively used in the genomic analyses of complex traits. Estimates from different studies are combined and the results effectively provide the power of a much larger study. Meta-analysis also has the potential of discovering heterogeneity in the effects among the different studies. T作者: 起波瀾 時(shí)間: 2025-3-30 16:07
Gene-Gene and Gene-Environment Interactions,e been made in identifying genetic variants associated with complex traits through more dense panels of genetic variants and larger sample sizes, genome-wide interaction analyses are still limited in power to detect interactions with small effect sizes, rare frequencies, and higher order interaction作者: ingenue 時(shí)間: 2025-3-30 16:42
Genetic Association in the HLA Region,forts to pinpoint drivers of this commonly encountered association peak at the short arm of chromosome 6, however, have been challenging, owing to the high density of genes and the long and extended linkage disequilibrium that are characteristic of this region..The development of methods to impute c作者: 娘娘腔 時(shí)間: 2025-3-30 21:57 作者: 贊美者 時(shí)間: 2025-3-31 03:31 作者: 艱苦地移動(dòng) 時(shí)間: 2025-3-31 07:08
Multivariate Methods for Meta-Analysis of Genetic Association Studies,recision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in作者: 內(nèi)行 時(shí)間: 2025-3-31 10:43 作者: ORE 時(shí)間: 2025-3-31 15:50
