標(biāo)題: Titlebook: Genome-Wide Association Studies; Davoud Torkamaneh,Fran?ois Belzile Book 2022 The Editor(s) (if applicable) and The Author(s), under exclu [打印本頁(yè)] 作者: 我贊成 時(shí)間: 2025-3-21 18:38
書(shū)目名稱(chēng)Genome-Wide Association Studies影響因子(影響力)
書(shū)目名稱(chēng)Genome-Wide Association Studies影響因子(影響力)學(xué)科排名
書(shū)目名稱(chēng)Genome-Wide Association Studies網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱(chēng)Genome-Wide Association Studies網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱(chēng)Genome-Wide Association Studies被引頻次
書(shū)目名稱(chēng)Genome-Wide Association Studies被引頻次學(xué)科排名
書(shū)目名稱(chēng)Genome-Wide Association Studies年度引用
書(shū)目名稱(chēng)Genome-Wide Association Studies年度引用學(xué)科排名
書(shū)目名稱(chēng)Genome-Wide Association Studies讀者反饋
書(shū)目名稱(chēng)Genome-Wide Association Studies讀者反饋學(xué)科排名
作者: OTHER 時(shí)間: 2025-3-21 23:31
Interpretation of Manhattan Plots and Other Outputs of Genome-Wide Association Studiesgenome-wide significance threshold and the different appearance of Manhattan plots in single-locus and multiple-locus models; (3) exploration of population structure and kinship among individuals; (4) quantile–quantile (QQ) plot; (5) LD decay across the genome and LD between the associated markers a作者: 增強(qiáng) 時(shí)間: 2025-3-22 03:42
Development, Preparation, and Curation of High-Throughput Phenotypic Data for Genome-Wide Associatiove been done for phenotyping information. This chapter provides a guide for generating large-scale data related to the size and shape of fruits, leaves, seeds, and roots and for downstream analysis for curation and preparation of clean datasets, through removal of outliers and performing primary sta作者: acrobat 時(shí)間: 2025-3-22 05:24
Performing Genome-Wide Association Studies with Multiple Models Using GAPIT, and BLINK (Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway). Besides the availability of multiple models, GAPIT provides comprehensive functions for data quality control, data visualization, and publication-ready quality graphic outputs, such as Manhattan plots in rectang作者: 水汽 時(shí)間: 2025-3-22 12:16 作者: 少量 時(shí)間: 2025-3-22 13:58 作者: 少量 時(shí)間: 2025-3-22 17:09 作者: 生命 時(shí)間: 2025-3-22 21:16
https://doi.org/10.1007/978-3-658-31961-8genome-wide significance threshold and the different appearance of Manhattan plots in single-locus and multiple-locus models; (3) exploration of population structure and kinship among individuals; (4) quantile–quantile (QQ) plot; (5) LD decay across the genome and LD between the associated markers a作者: Panacea 時(shí)間: 2025-3-23 04:35 作者: 截?cái)?nbsp; 時(shí)間: 2025-3-23 07:14
Marc Joseph Saugey Restoration,, and BLINK (Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway). Besides the availability of multiple models, GAPIT provides comprehensive functions for data quality control, data visualization, and publication-ready quality graphic outputs, such as Manhattan plots in rectang作者: Licentious 時(shí)間: 2025-3-23 09:49 作者: 原告 時(shí)間: 2025-3-23 16:48 作者: 我說(shuō)不重要 時(shí)間: 2025-3-23 19:21
Klassifizierung der Quantenmechanik,undreds of plants in a cost-effective manner. Currently there are multiple commercial platforms available that are being effectively used across crops. These platforms include genotyping arrays such as the Illumina Infinium arrays and the Applied Biosystems Axiom Arrays along with a variety of reseq作者: Blemish 時(shí)間: 2025-3-24 00:08 作者: 暗諷 時(shí)間: 2025-3-24 03:36 作者: cartilage 時(shí)間: 2025-3-24 09:50
https://doi.org/10.1007/978-1-4842-3643-7s power is highly influenced by the accuracy of the phenotypic data. To obtain accurate phenotypic values, the phenotyping should be achieved through multienvironment trials (METs). In order to avoid any technical errors, the required time needs to be spent on exploring, understanding, curating and 作者: dialect 時(shí)間: 2025-3-24 14:16
https://doi.org/10.1007/978-1-4302-4570-4ging genotype to phenotype, several genes have been associated with traits of agricultural interest. Despite this, there is still a gap between genotyping and phenotyping due to the large difference in throughput between the two disciplines. Although cutting-edge phenomics technologies are available作者: 不能逃避 時(shí)間: 2025-3-24 14:57 作者: 松雞 時(shí)間: 2025-3-24 21:00 作者: 挑剔小責(zé) 時(shí)間: 2025-3-25 00:10 作者: FER 時(shí)間: 2025-3-25 05:30 作者: Interlocking 時(shí)間: 2025-3-25 10:26 作者: rheumatology 時(shí)間: 2025-3-25 11:46
Marc Joseph Saugey Restoration,ides the genetic linkage between the genetic markers and the causal mutations, many other factors contribute to the LD, including selection and nonrandom mating formatting population structure. Many methods have been developed with accompany of corresponding software such as multiple loci mixed mode作者: senile-dementia 時(shí)間: 2025-3-25 19:12
Finding Answers in a Text Document, provided unprecedented insights into the genetic basis of quantitative variation for complex traits. Along with the development of high-throughput sequencing technology, both sample sizes and marker sizes are increasing rapidly, which make computations more challenging than ever. Therefore, to effi作者: BUMP 時(shí)間: 2025-3-25 20:55 作者: CHART 時(shí)間: 2025-3-26 03:53 作者: 災(zāi)禍 時(shí)間: 2025-3-26 05:23 作者: 預(yù)防注射 時(shí)間: 2025-3-26 12:24
Genome-Wide Association Studies978-1-0716-2237-7Series ISSN 1064-3745 Series E-ISSN 1940-6029 作者: 使激動(dòng) 時(shí)間: 2025-3-26 14:35
Designing a Genome-Wide Association Study: Main Steps and Critical DecisionsAS) in the context of crop plants. After introducing some general concepts regarding GWAS, we divide the contents of this overview into four main sections that reflect the key components of a GWAS: assembly and phenotyping of an association panel, genotyping, association analysis and candidate gene 作者: Jogging 時(shí)間: 2025-3-26 17:52 作者: Carcinogenesis 時(shí)間: 2025-3-26 23:23
Genotyping Platforms for Genome-Wide Association Studies: Options and Practical Considerationsundreds of plants in a cost-effective manner. Currently there are multiple commercial platforms available that are being effectively used across crops. These platforms include genotyping arrays such as the Illumina Infinium arrays and the Applied Biosystems Axiom Arrays along with a variety of reseq作者: Indigence 時(shí)間: 2025-3-27 01:50 作者: 感情 時(shí)間: 2025-3-27 05:42 作者: Parabola 時(shí)間: 2025-3-27 10:02
Preparation and Curation of Multiyear, Multilocation, Multitrait Datasetss power is highly influenced by the accuracy of the phenotypic data. To obtain accurate phenotypic values, the phenotyping should be achieved through multienvironment trials (METs). In order to avoid any technical errors, the required time needs to be spent on exploring, understanding, curating and 作者: 負(fù)擔(dān) 時(shí)間: 2025-3-27 15:11 作者: 連鎖 時(shí)間: 2025-3-27 20:49
Preparation and Curation of Omics Data for Genome-Wide Association Studieso the analysis of classical agronomic traits, such as yield or flowering time, but also embracing the dissection of the genetic basis of molecular traits. Data generated by omics platforms, however, pose some technical and statistical challenges to the classical methodology and assumptions of an ass作者: Scintigraphy 時(shí)間: 2025-3-28 01:01
Producing High-Quality Single Nucleotide Polymorphism Data for Genome-Wide Association Studies. SNPs can be used to identify genomic regions linked to traits such as disease in genome-wide association studies, to understand population structure and diversity, or to understand mechanisms of genome evolution. One of the first steps of any SNP-based workflow, following SNP discovery, is quality作者: 牛的細(xì)微差別 時(shí)間: 2025-3-28 03:28 作者: 打折 時(shí)間: 2025-3-28 07:19
Data Integration, Imputation , and Meta-analysis for Genome-Wide Association Studieseir benefit and increase reference population sizes for genomic prediction and genome-wide association studies (GWAS). However, different studies use different genotyping techniques which requires a synchronizing step for the genotyped variants called “imputation” before combining them. Optimally, d作者: 注視 時(shí)間: 2025-3-28 14:22
Population Structure and Relatedness for Genome-Wide Association Studies of core collections for the conservation of genetic resources, uncovering the demographic history of the population under study, as well as for association studies. With the recent development of high-throughput genotyping technologies, several algorithms and methods have been developed and impleme作者: TSH582 時(shí)間: 2025-3-28 17:30 作者: FRAX-tool 時(shí)間: 2025-3-28 22:12 作者: Eclampsia 時(shí)間: 2025-3-29 02:51
1064-3745 expertsThis detailed collection explores genome-wide association studies (GWAS), which have revolutionized the investigation of complex traits over the past decade and have unveiled numerous useful genotype–phenotype associations in plants. The book describes the key concepts and methods underlying作者: Assemble 時(shí)間: 2025-3-29 04:36 作者: 壓倒 時(shí)間: 2025-3-29 10:53
https://doi.org/10.1007/978-1-4842-4433-3 in formatting of genotype data for use with popular GWAS programs. This protocol describes how typical SV genotype data can be formatted for input to three GWAS programs commonly used by the plant genetics community: TASSEL, GAPIT, and mrMLM.作者: 天空 時(shí)間: 2025-3-29 13:44
Book 2022decade and have unveiled numerous useful genotype–phenotype associations in plants. The book describes the key concepts and methods underlying GWAS, including the genetic architecture underlying variation for phenotypic traits, the structure of genetic variation in plants, technologies for capturing作者: monologue 時(shí)間: 2025-3-29 16:12 作者: 小步走路 時(shí)間: 2025-3-29 23:16
A Practical Guide to Using Structural Variants for Genome-Wide Association Studies in formatting of genotype data for use with popular GWAS programs. This protocol describes how typical SV genotype data can be formatted for input to three GWAS programs commonly used by the plant genetics community: TASSEL, GAPIT, and mrMLM.作者: 正式演說(shuō) 時(shí)間: 2025-3-30 03:52
Klassifizierung der Quantenmechanik,n crops with simple genomes to crops with very complex, large, polyploid genomes. Depending on the crop and the goal of the GWAS, there are several options and practical considerations to take into account when selecting a genotyping technology to ensure that the right coverage, accuracy, and cost for the study is achieved.作者: Celiac-Plexus 時(shí)間: 2025-3-30 07:35
https://doi.org/10.1007/978-1-4842-3643-7 as possible any effect that can lead to misestimation of the phenotypic values. The purpose of this chapter is to explain a series of important steps to explore and analyze data from METs used to characterize an association panel. Two datasets are used to illustrate two different scenarios.作者: 演繹 時(shí)間: 2025-3-30 08:44
https://doi.org/10.1007/978-1-4842-2208-9ulation structure and relatedness in a step-by-step fashion. To exemplify the process, two pruned datasets (14K and 243K SNP markers) were used to investigate population structure and relatedness among a soybean GWAS panel using different approaches and methods.作者: irradicable 時(shí)間: 2025-3-30 16:00
Finding Answers in a Text Document, and false negative rates have always been hot topics in the domain of GWAS. In this chapter, we describe how to perform GWAS using an R package, rMVP, which includes data preparation, evaluation of population structure, association tests by different models, and high-quality visualization of GWAS results.作者: CHIDE 時(shí)間: 2025-3-30 17:30 作者: 輕信 時(shí)間: 2025-3-31 00:10 作者: 多產(chǎn)子 時(shí)間: 2025-3-31 02:01
Population Structure and Relatedness for Genome-Wide Association Studiesulation structure and relatedness in a step-by-step fashion. To exemplify the process, two pruned datasets (14K and 243K SNP markers) were used to investigate population structure and relatedness among a soybean GWAS panel using different approaches and methods.作者: mediocrity 時(shí)間: 2025-3-31 06:06
Performing Genome-Wide Association Studies Using rMVP and false negative rates have always been hot topics in the domain of GWAS. In this chapter, we describe how to perform GWAS using an R package, rMVP, which includes data preparation, evaluation of population structure, association tests by different models, and high-quality visualization of GWAS results.
