Algorithms For Linkage Analysis Error Detection And Haplotyping In Pedigrees
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Algorithms For Linkage Analysis Error Detection And Haplotyping In Pedigrees
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Author : Jeffrey R. O'Connell
language : en
Publisher:
Release Date : 2000
Algorithms For Linkage Analysis Error Detection And Haplotyping In Pedigrees written by Jeffrey R. O'Connell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Linkage (Genetics) categories.
Genetic Mapping And Dna Sequencing
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Author : Terry Speed
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Genetic Mapping And Dna Sequencing written by Terry Speed and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
Genetics mapping, physical mapping and DNA sequencing are the three key components of the human and other genome projects. Statistics, mathematics and computing play important roles in all three, as well as in the uses to which the mapping and sequencing data are put. This volume edited by key researchers Mike Waterman and Terry Speed reviews recent progress in the area, with an emphasis on the theory and application of genetic mapping.
Algorithms In Bioinformatics
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Author : Raffaele Giancarlo
language : en
Publisher: Springer
Release Date : 2007-08-24
Algorithms In Bioinformatics written by Raffaele Giancarlo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-24 with Computers categories.
The refereed proceedings from the 7th International Workshop on Algorithms in Bioinformatics are provided in this volume. Papers address current issues in algorithms in bioinformatics, ranging from mathematical tools to experimental studies of approximation algorithms to significant computational analyses. Biological problems examined include genetic mapping, sequence alignment and analysis, phylogeny, comparative genomics, and protein structure.
Sequential Imputation And Linkage Analysis
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Author : Zachary Skrivanek
language : en
Publisher:
Release Date : 2002
Sequential Imputation And Linkage Analysis written by Zachary Skrivanek and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Linkage (Genetics) categories.
Abstract: Multilocus calculations using all available information on all pedigree members are important for linkage analysis. Exact calculation methods in linkage analysis are limited in either the number of loci or the number of pedigree members they can handle. In this thesis, we propose a Monte Carlo method for linkage analysis based on sequential imputation. Unlike exact methods, sequential imputation can handle both a moderate number of loci and a large number of pedigree members. Sequential imputation does not have the problem of slow mixing encountered by Markov chain Monte Carlo methods because of high correlation between samples from pedigree data. This Monte Carlo method is an application of importance sampling in which we sequentially impute ordered genotypes locus by locus and then impute inheritance vectors conditioned on these genotypes. The resulting inheritance vectors together with the importance sampling weights are used to derive a consistent estimator of any linkage statistic of interest. The linkage statistic can be parametric or nonparametric; we focus on nonparametric linkage statistics. We showed that sequential imputation can produce accurate estimates within reasonable computing time. Then we performed a simulation study to illustrate the potential gain in power using our method for multilocus linkage analysis with large pedigrees. We also showed how sequential imputation can be used in haplotype reconstruction, an important step in genetic mapping. In all of the applications of sequential imputation we can incorporate interference, which often is ignored in linkage analysis due to computational problems. We demonstrated the effect of interference on haplotyping and linkage analysis. We have implemented sequential imputation for multilocus linkage analysis in a user-friendly software package called SIMPLE (Sequential Imputation for Multi-Point Linkage Estimation). SIMPLE currently can estimate LOD scores, IBD sharing statistics and haplotype configuration probabilities for both simple and complex pedigrees with or without interference.
Genome Analysis
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Author : Eric D. Green
language : en
Publisher: CSHL Press
Release Date : 1997
Genome Analysis written by Eric D. Green and has been published by CSHL Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with DNA categories.
A complement to the bible of recombinant DNA, Molecular Cloning, these manuals are essential for every laboratory in which genes are being studied.
Statistical Genetics
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Author : Benjamin Neale
language : en
Publisher: Garland Science
Release Date : 2007-11-30
Statistical Genetics written by Benjamin Neale and has been published by Garland Science this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-11-30 with Science categories.
Statistical Genetics is an advanced textbook focusing on conducting genome-wide linkage and association analysis in order to identify the genes responsible for complex behaviors and diseases. Starting with an introductory section on statistics and quantitative genetics, it covers both established and new methodologies, providing the genetic and statistical theory on which they are based. Each chapter is written by leading researchers, who give the reader the benefit of their experience with worked examples, study design, and sources of error. The text can be used in conjunction with an associated website (www.genemapping.org) that provides supplementary material and links to downloadable software.
Multipoint Mapping And Linkage Based Upon Affected Pedigree Members
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Author : Robert C. Elston
language : en
Publisher: John Wiley & Sons
Release Date : 1989
Multipoint Mapping And Linkage Based Upon Affected Pedigree Members written by Robert C. Elston and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Science categories.
Using both empirical and simulated data, this study examines selected computational approaches and algorithms for analyzing the genetic etiology of a disease. It compares a wide variety of analytical methods and highlights areas of substantive interest to geneticists investigating human disease. Its methodologic emphasis provides useful guidance for the design of future studies to map disease susceptibility loci.
Algorithms For Human Genetics
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Author : BONNIE. KIRKPATRICK
language : en
Publisher:
Release Date : 2011
Algorithms For Human Genetics written by BONNIE. KIRKPATRICK and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Whereas Mendel used breeding experiments and painstakingly counted peas, modern biology increasingly requires computational tools. In the late 1800's probability and experimental genetics were the critical tools for discovering the gene. Today, the combined use of statistical and computational methods to make genetic and genomic discoveries has increased after the discovery of the DNA double-helix and the development of sequencing methods. By examining relationships among individuals using computational tools, geneticists have been able to understand the biological mechanisms that produce genetic diversity, map ancestral movements of populations, reconstruct ancestral genomes, and identify relatives. Furthermore, models in genetics have inspired advances in computer science, notably the model for inheritance in families is an early example of a graphical model and helped inspire the sum-product algorithm. The genetic data of interest is single-nucleotide polymorphism (SNP) data, which are positions in the genome known to have nucleotide variation across the population. Humans are diploid individuals having two copies of each chromosome. Data for an individual can come in two forms, either haplotypes or genotypes. The haplotypes are two strings, each giving the sequence of nucleotides that appear together on the same chromosome. The genotypes, for each position in the genome, give an unordered set of nucleotides that appear. In particular the genotype is said to be ùnphased' due to the lack of information about which nucleotide appears on which chromosome. In human genetics there are two main ways to model relatedness: evolutionary relationships between people and closer, family relationships. Evolutionary relationships, from the domain of population genetics, occur through a distant relative and leave small traces of the relationship in the genome. Family relationships are typically much closer and leave much larger traces in the genome. This thesis examines algorithms for both types of relationships. For evolutionarily related individuals, this thesis presents the perfect phylogeny and coalescent and then examines two related questions. The first is related to privacy of genetic data used for research purposes. In order to share data from studies while hopefully maintaining the privacy of study participants, geneticists have released the summary statistics of the data. A natural question, whether individuals can be detected in the summary data, is answered in the affirmative by using a perfect phylogeny model. The second question is how to construct perfect phylogenies from haplotypes where there is missing data. We introduce a polynomial-time algorithm for enumerating such phylogenies. This algorithm can be used to compute the probability of the data as an expectation over possible coalescent genealogies. Recent relationships are modeled using a family tree, or pedigree graph. Traditionally, geneticists construct these graphs from genealogical records in a very tedious process of examining birth, death, and marriage records. Invariably mistakes are made due to poor record keeping or incorrect paternity information. As an alternative to manual methods, this thesis addresses the problem of automatically constructing pedigree graphs from genetic data. The most obvious way to reconstruct pedigrees from genetic data is to use a structured machine learning approach, similar to phylogenetic reconstruction. That method would involve a search over the space of pedigree graphs where the objective is to find the pedigree graph with the highest likelihood of generating the observed data. Unfortunately, this is not a good way to proceed for two reasons: the space of pedigree graphs is exponential, and the likelihood calculation has exponential running time. The likelihood calculation given genotype data is known to be NP-hard. In an attempt to make use of the likelihood in complex pedigrees, the method PhyloPed uses a Gibbs sampler to infer haplotypes from genotype data. In a second attempt to use likelihood methods, this time for haplotype data, an NP-hardness result is presented. A third attempt to find an efficient algorithm for the likelihood problem results in a state-space reduction method for the pedigree hidden Markov model. Since likelihood-based approaches seem completely infeasible, a completely different approach is introduced. We focus on the problem of inferring relationships between a set of living individuals with available identity-by-descent data. For convenience, we assume that the inferred pedigree is monogamous without inter-generational mating. Two heuristic and practical pedigree reconstruction methods are introduced, one for inbred pedigrees and the other for outbred pedigrees. This work immediately reveals another important problem, that of evaluating the resulting inferred pedigree against a ground-truth pedigree. This can be done either by determining whether the two pedigrees are isomorphic or by finding the edit distance between the two pedigrees.
Biostatistical Genetics And Genetic Epidemiology
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Author : Robert C. Elston
language : en
Publisher: John Wiley & Sons
Release Date : 2002-04-22
Biostatistical Genetics And Genetic Epidemiology written by Robert C. Elston and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-04-22 with Medical categories.
"Human Genetics and Genetic Epidemiology" ist der 3. Band aus der sehr erfolgreichen Reihe 'Wiley Biostatistics Reference Series', die auf Artikeln der "Encyclopedia of Biostatistics" basiert. Dieser Band gibt einen topaktuellen und umfassenden Überblick über ein Forschungsgebiet, das insbesondere im Zuge des Human-Genomprojekts eine regelrechte Explosion an Forschungsaktivitäten erlebt hat. Enthalten sind komplett aktualisierte Artikel aus der "Encyclopedia of Biostatistics" sowie über 25% neue Artikel. Mit einem komplexen System an Querverweisen, die das Auffinden der gewünschten Information erheblich erleichtern. Eine interessante Lektüre für Genetiker, Epidemiologen, Biostatistiker und Forscher in diesen Bereichen.
Theoretical And Computational Methods In Genome Research
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Author : Sándor Suhai
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Theoretical And Computational Methods In Genome Research written by Sándor Suhai and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.
The application ofcomputational methods to solve scientific and practical problems in genome research created a new interdisciplinary area that transcends boundaries tradi tionally separating genetics, biology, mathematics, physics, and computer science. Com puters have, of course, been intensively used in the field of life sciences for many years, even before genome research started, to store and analyze DNA or protein sequences; to explore and model the three-dimensional structure, the dynamics, and the function of biopolymers; to compute genetic linkage or evolutionary processes; and more. The rapid development of new molecular and genetic technologies, combined with ambitious goals to explore the structure and function ofgenomes ofhigher organisms, has generated, how ever, not only a huge and exponentially increasing body of data but also a new class of scientific questions. The nature and complexity of these questions will also require, be yond establishing a new kind ofalliance between experimental and theoretical disciplines, the development of new generations both in computer software and hardware technolo gies. New theoretical procedures, combined with powerful computational facilities, will substantially extend the horizon of problems that genome research can attack with suc cess. Many of us still feel that computational models rationalizing experimental findings in genome research fulfill their promises more slowly than desired. There is also an uncer tainty concerning the real position of a "theoretical genome research" in the network of established disciplines integrating their efforts in this field.