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Download or read book Statistical Methods to Map Quantitative Trait Loci for Binary Traits in Half-sib Populations written by and published by . This book was released on 1998 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Nicola J. Camp
Publisher : Springer Science & Business Media
ISBN 13 : 1592591760
Total Pages : 362 pages
Book Rating : 4.5/5 (925 download)
Download or read book Quantitative Trait Loci written by Nicola J. Camp and published by Springer Science & Business Media. This book was released on 2008-02-03 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Quantitative Trait Loci: Methods and Protocols, a panel of highly experienced statistical geneticists demonstrate in a step-by-step fashion how to successfully analyze quantitative trait data using a variety of methods and software for the detection and fine mapping of quantitative trait loci (QTL). Writing for the nonmathematician, these experts guide the investigator from the design stage of a project onwards, providing detailed explanations of how best to proceed with each specific analysis, to find and use appropriate software, and to interpret results. Worked examples, citations to key papers, and variations in method ease the way to understanding and successful studies. Among the cutting-edge techniques presented are QTDT methods, variance components methods, and the Markov Chain Monte Carlo method for joint linkage and segregation analysis.
Author : Rongling Wu
Publisher : Springer Science & Business Media
ISBN 13 : 038768154X
Total Pages : 371 pages
Book Rating : 4.3/5 (876 download)
Download or read book Statistical Genetics of Quantitative Traits written by Rongling Wu and published by Springer Science & Business Media. This book was released on 2007-07-17 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the basic concepts and methods that are useful in the statistical analysis and modeling of the DNA-based marker and phenotypic data that arise in agriculture, forestry, experimental biology, and other fields. It concentrates on the linkage analysis of markers, map construction and quantitative trait locus (QTL) mapping, and assumes a background in regression analysis and maximum likelihood approaches. The strength of this book lies in the construction of general models and algorithms for linkage analysis, as well as in QTL mapping in any kind of crossed pedigrees initiated with inbred lines of crops.
Author : Joel Ira Weller
Publisher : CABI
ISBN 13 : 1845937341
Total Pages : 288 pages
Book Rating : 4.8/5 (459 download)
Download or read book Quantitative Trait Loci Analysis in Animals written by Joel Ira Weller and published by CABI. This book was released on 2009 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative Trait Loci (QTL) is a topic of major agricultural significance for efficient livestock production. This book covers various statistical methods that have been used or proposed for detection and analysis of QTL and marker-and gene-assisted selection in animal genetics and breeding.
Download or read book Mapping Quantitative Trait Loci in Outbred Half-sib Populations written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative trait loci (QTL) mapping in outbred populations faces some challenges unique to the divergent genetic background and complex pedigree relationships. Motivated by a dairy cattle half-sib data set from a grand daughter design, we present in this dissertation a series of endeavors to address various challenges along the analysis flow of QTL mapping. A first step is to infer the haplotypes in sires based on the observed genotypes in sires and his offspring. Our method was shown to outperform peer methods with greater robustness and accuracy yet with fast speed performance. Then in light of adapting the multiple interval mapping method to within-family QTL analysis, we extended the modeling framework by allowing for heteroscedastic residual variances and upgraded the Windows QTL Cartographer accordingly. The advantageous post-analysis result parsing from Windows QTL Cartographer and more importantly, the improved analysis outputs due to more powerful maximum likelihood-based mixture modeling than the least squares regression manifest our efforts in delivering better methodology via practically user friendly software. We further developed a mixed model approach for the purpose of QTL mapping across multiple families that was aimed at modeling QTL effects as both the fixed effect across families and the random effect within families. Our mixed model was shown to encompass similar or higher statistical testing performance on QTL variation than the widely used variance component modeling approach, yet still allowing permutations for obtaining chromosome-wide or genome-wide significance threshold. What's more, the flexibility of our mixed model in constructing alternative hypotheses testing on either fixed or random QTL effects or both was shown to offer interesting insight into the varying sources of signal that would not be unveiled by least squares regression or variance component methods. In concluding our comprehensive approach to QTL linkage mapping in dair.
Author : Scott A. Rifkin
Publisher : Humana Press
ISBN 13 : 9781617797842
Total Pages : 0 pages
Book Rating : 4.7/5 (978 download)
Download or read book Quantitative Trait Loci (QTL) written by Scott A. Rifkin and published by Humana Press. This book was released on 2012-05-09 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last two decades advances in genotyping technology, and the development of quantitative genetic analytical techniques have made it possible to dissect complex traits and link quantitative variation in traits to allelic variation on chromosomes or quantitative trait loci (QTLs). In Quantitative Trait Loci (QTLs):Methods and Protocols, expert researchers in the field detail methods and techniques that focus on specific components of the entire process of quantitative train loci experiments. These include methods and techniques for the mapping populations, identifying quantitative trait loci, extending the power of quantitative trait locus analysis, and case studies. Written in the highly successful Methods in Molecular BiologyTM series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory. Thorough and intuitive, Quantitative Trait Loci (QTLs):Methods and Protocols aids scientists in the further study of the links between phenotypic and genotypic variation in fields from medicine to agriculture, from molecular biology to evolution to ecology.
Author : Jie Xu
Publisher :
ISBN 13 :
Total Pages : 266 pages
Book Rating : 4.:/5 (319 download)
Download or read book Statistical Analysis for Mapping Linked Quantitative Trait Loci written by Jie Xu and published by . This book was released on 2005 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Meng Chen
Publisher :
ISBN 13 :
Total Pages : 164 pages
Book Rating : 4.:/5 (89 download)
Download or read book Statistical Methods for Expression Quantitative Trait Loci (EQTL) Mapping written by Meng Chen and published by . This book was released on 2006 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Xiaohua Gong
Publisher :
ISBN 13 :
Total Pages : 138 pages
Book Rating : 4.:/5 (341 download)
Download or read book Mapping Quantitative Trait Loci in Outbred Half-sib Populations written by Xiaohua Gong and published by . This book was released on 2009 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keywords: QTL, half-sib, variance component, mixed model, EM algorithm, haplotyping.
Author : Fengxing Du
Publisher :
ISBN 13 :
Total Pages : 340 pages
Book Rating : 4.:/5 (319 download)
Download or read book Designing Experiments for Mapping Quantitative Trait Loci in Segregating Animal Populations written by Fengxing Du and published by . This book was released on 1999 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Hongjuan Liu
Publisher :
ISBN 13 :
Total Pages : 218 pages
Book Rating : 4.3/5 (121 download)
Download or read book Quantitative Trait Loci Linkage Mapping for Dynamic Traits written by Hongjuan Liu and published by . This book was released on 2006 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Fei Zou
Publisher :
ISBN 13 :
Total Pages : 110 pages
Book Rating : 4.:/5 (89 download)
Download or read book Efficient and Robust Statistical Methodologies for Quantitative Trait Loci Analysis written by Fei Zou and published by . This book was released on 2001 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multiple-trait Multiple-interval Mapping of Quantitative-trait Loci written by and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: QTL (quantitative-trait locus) analysis aims to locate and estimate the effects of genes that are responsible for quantitative traits, such as grain protein content and yield, by means of statistical methods that evaluate the association of genetic variation with trait (phenotypic) variation. Quantitative traits are typically polygenic, i.e., controlled by multiple genes, with varying degrees of in uence on the phenotype. Several methods have been developed to increase the accuracy of QTL location and effect estimates. One of them, multiple interval mapping (MIM) (Kao et al. 1999), has been shown to be more accurate than conventional methods such as composite interval mapping (CIM) (Zeng 1994). Other QTL analysis methods have been developed to perform additional analyses that might be useful for breeders, such as of pleiotropy and QTL-by-environment (QxE) interaction. It has been shown (Jiang and Zeng 1995) that these analyses can be carried out with a multivariate extension of CIM (MT-CIM) that exploits the correlation structure in a set of traits. In doing so, this method also improves the accuracy of QTL location detection. This thesis describes the multivariate extension of MIM (MT-MIM) using ideas from MT-CIM. The development of additional multivariate tests, such as of pleiotropy and QxE interaction, and several methods pertinent to the development of MT-MIM are also described. A small simulation study shows that MT-MIM is more accurate than MT-CIM and univariate MIM. Results for real data show that MT-MIM is able to provide a more accurate and precise estimate of QTL location.
Author : Stanford University. Department of Statistics
Publisher :
ISBN 13 :
Total Pages : 36 pages
Book Rating : 4.:/5 (123 download)
Download or read book Statistical Methods for Mapping Quantitative Trait Loci from a Dense Set of Markers written by Stanford University. Department of Statistics and published by . This book was released on 1997 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher :
ISBN 13 :
Total Pages : 82 pages
Book Rating : 4.:/5 (887 download)
Download or read book Regression-based Methods to Map Quantitative Trait Loci Underlying Function-valued Phenotypes written by and published by . This book was released on 2014 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most statistical methods for QTL mapping focus on a single phenotype. However, multiple phenotypes are commonly measured, and recent technological advances have greatly simplified the automated acquisition of numerous phenotypes, including function-valued phenotypes, such as growth measured over time. While there exist methods for QTL mapping with function-valued phenotypes, they are generally computationally intensive and focus on single-QTL models. This thesis is composed of two main parts. In the first part, I propose some simple approaches for QTL mapping with function-valued traits, including multiple-QTL models using a penalized likelihood approach. The methods are fast and maintain high power and precision. After identifying multiple QTL by these approaches, we can view the function-valued QTL effects to provide a deeper understanding of the underlying processes. However there are two weaknesses. First, the methods do not work well when the curves are not smooth. Second, they do not take account of the correlation structure among time points. In the second part, I suggest a method to overcome those weaknesses, by smoothing the data set to reduce measurement error, and with functional Principal Component Analysis (PCA). We reduce the functional data into a small number of principal components without much loss of information. We can then proceed with QTL mapping on these dimension-reduced data. We consider four subsequent methods for analysis. First, we simply treat these multiple traits as independent. Second, we use multivariate QTL mapping method proposed by \citet{knott2000}, assuming that the transformed multivariate trait data follow a multivariate normal distribution. The third and fourth ideas are to take the average and maximum of LOD scores for each trait, as considered in the first part. I have implemented these methods in an R package, funqtl (github.com/ikwak2/funqtl ).
Author : Chunfang Jin
Publisher :
ISBN 13 :
Total Pages : 136 pages
Book Rating : 4.:/5 (89 download)
Download or read book Contributions to the Design and Analysis of Quantitative Trait Loci Experiments written by Chunfang Jin and published by . This book was released on 2004 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Heather J. Zhou
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (139 download)
Download or read book Statistical Methods for Molecular Quantitative Trait Locus Analysis written by Heather J. Zhou and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Molecular quantitative trait locus (molecular QTL, henceforth "QTL") analysis investigates the relationship between genetic variants and molecular traits, helping explain findings in genome-wide association studies. This dissertation addresses two major problems in QTL analysis: hidden variable inference problem and eGene identification problem. Estimating and accounting for hidden variables is widely practiced as an important step in QTL analysis for improving the power of QTL identification. However, few benchmark studies have been performed to evaluate the efficacy of the various methods developed for this purpose. In my first project, I benchmark popular hidden variable inference methods including surrogate variable analysis (SVA), probabilistic estimation of expression residuals (PEER), and hidden covariates with prior (HCP) against principal component analysis (PCA)-a well-established dimension reduction and factor discovery method-via 362 synthetic and 110 real data sets. I show that PCA not only underlies the statistical methodology behind the popular methods but is also orders of magnitude faster, better performing, and much easier to interpret and use. To help researchers use PCA in their QTL analysis, I provide an R package PCAForQTL along with a detailed guide, both of which are available at httpss://github.com/heatherjzhou/PCAForQTL. I believe that using PCA rather than SVA, PEER, or HCP will substantially improve and simplify hidden variable inference in QTL mapping as well as increase the transparency and reproducibility of QTL research. A central task in expression quantitative trait locus (eQTL) analysis is to identify cis-eGenes (henceforth "eGenes"), i.e., genes whose expression levels are regulated by at least one local genetic variant. Among the existing eGene identification methods, FastQTL is considered the gold standard but is computationally expensive as it requires thousands of permutations for each gene. Alternative methods such as eigenMT and TreeQTL have lower power than FastQTL. In my second project, I propose ClipperQTL, which reduces the number of permutations needed from thousands to 20 for data sets with large sample sizes (>450) by using the contrastive strategy developed in Clipper; for data sets with smaller sample sizes, it uses the same permutation-based approach as FastQTL. I show that ClipperQTL performs as well as FastQTL and runs about 500 times faster if the contrastive strategy is used and 50 times faster if the conventional permutation-based approach is used. The R package ClipperQTL is available at httpss://github.com/heatherjzhou/ClipperQTL. This project demonstrates the potential of the contrastive strategy developed in Clipper and provides a simpler and more efficient way of identifying eGenes.
