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3 edition of A comparison of non-parametric methods for detecting genetic linkage. found in the catalog.

A comparison of non-parametric methods for detecting genetic linkage.

Nicola Helen Chapman

A comparison of non-parametric methods for detecting genetic linkage.

by Nicola Helen Chapman

  • 81 Want to read
  • 34 Currently reading

Published by National Library of Canada in Ottawa .
Written in English


Edition Notes

Thesis (M.Sc.) -- University of Toronto, 1995.

SeriesCanadian theses = -- Thèses canadiennes
The Physical Object
Pagination2 microfiches : negative. --
ID Numbers
Open LibraryOL17882498M
ISBN 100612075303
OCLC/WorldCa46496037

• Linear model and Non-parametric tests don’t account for population structure • Initially proposed in Association mapping by Yu et al. () • Y typically consists of the phenotype values, or case-control status for N individuals. • X is the NxP genotype matrix, consisting of P genetic variants (e.g. SNPs). Thus, linkage methods alone may not be able to detect disease susceptibility genes for common, complex diseases. Similarly, potential caveats exist for association analysis methods for detecting interactions. First, with methods such as logistic regression, the interaction effects must be .

Chapter 13 covers the analysis of family data, including linkage and association studies. Both model-free and model-based linkage analyses are discussed. For the former, estimating marker identity by descent, interval mapping, the Haseman-Elston regression method for a quantitative trait, and the likehood variance component method are studied. 34 Non-parametric Linkage. P. Holmans. Introduction. Pros and Cons of Model-free Methods. Model-free Methods for Dichotomous Traits. Model-free Methods for Analysing Quantitative Traits. Conclusions. Related Chapters. References. 35 Population Admixture and Stratification in Genetic Epidemiology. P.M. McKeigue.

@article{osti_, title = {Linkage of the VNTR/insulin-gene and type I diabetes mellitus: Increased gene sharing in affected sibling pairs}, author = {Owerbach, D and Gabbay, K H}, abstractNote = {Ninety-six multiplex type I diabetic families were typed at the 5' flanking region of the insulin gene by using a PCR assay that better resolves the VNTR into multiple alleles. [] Bailey-Wilson JE, Sorant AJ, Malley JD, Presciuttini S, Redner RA, Severini TA, Badner JA, Pajevic S, et al."Comparison of novel and existing methods for detection of linkage disequilibrium using parent-child trios in the GAW12 genetic isolate simulated data." Genetic Epidemiology 21 .


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A comparison of non-parametric methods for detecting genetic linkage by Nicola Helen Chapman Download PDF EPUB FB2

Greenberg DA. Linkage analysis assuming a single-locus mode of inheritance for traits determined by two loci: inferring mode of inheritance and estimating penetrance. Genet Epidemiol. ; 7 (6)– Greenberg DA, Abreu P, Hodge SE.

The power to detect linkage in complex disease by means of simple LOD-score analyses. Am J Hum by: The purpose of our work is to compare the power of different methods to detect the effect of Locus B and its interaction with history of tobacco use.

We used the simulated data (Problem 3) of Genetic Analysis Workshop 15 (GAW15) with knowledge of the "answers" and compared four methods to test for genetic effect and/or G × E by: 3.

If the model specified for analysis is sufficiently close to the true mode of inheritance (MOI) that governs the trait, then parametric analysis has superior power to detect linkage when compared with nonparametric analysis.

Therefore, a key issue in linkage analysis is the specification of the correct genetic by:   Conventional methods for the detection of quantitative trait locus (QTL) are based on a comparison of single QTL models with a model assuming no QTL. For instance, in the SIM method the likelihood for a single putative QTL is assessed at each location on the genome.

However, QTLs located elsewhere on the genome can have an interfering by: 2. The method is applied to 28 published families analyzed for genetic linkage between hereditary motor and sensory neuropathy I and the A comparison of non-parametric methods for detecting genetic linkage.

book (FY) blood group locus and confirms heterogeneity of. Linkage analysis can be a powerful method for detecting the effect of genes for complex diseases [2,3]. Especially because of the enrichment of rare variants in families, linkage analysis has the advantage over association analysis that it is not prone to allelic heterogeneity.

Rita M. Cantor, in Emery and Rimoin's Principles and Practice of Medical Genetics and Genomics (Seventh Edition), Abstract. Linkage analysis is a well-established statistical method for mapping the genes for heritable traits to their chromosome locations.

Genome-wide markers are tested in pedigrees segregating a trait. The statistical method of linkage analysis combines these data to. To circumvent these problems, non-parametric methods of linkage analysis have been developed.

Instead of tracking the inheritance of a hypothesized (causative) disease gene, these non-parametric methods examine which parts of the genomes of a pair of affected relatives are identical by descent (IBD).

The most common paradigm uses affected. A general non-parametric genetic model with both main genetic effects and pairwise interactions assumes (1) where is the population mean, is an unknown function specifying the association between the phenotype and the j th SNP, is an unknown function specifying the association between the phenotype and the epistatic interaction between the j th.

Allele-sharing methods detect linkage by examining pedigrees for whether a particular genetic locus (chromosomal fragment) is more common among individuals in a pedigree than expected by random segregation. It is basically a non-parametric method. In book: eLS. Cite this publication in non-parametric methods some assumptions are made about the trait model, Robust Methods for the Detection of Genetic Linkage for Data from Extended.

Linear regression method, proposed by Haseman and Elston(), for detecting linkage to a quantitative trait of sib pairs is a linkage testing method for a single locus and a single trait.

The non-parametric methods achieved high power, but no non-parametric method outperformed all others under a variety of epistatic scenarios. PCS and ZSS, however, outperformed MDR.

PCS, ZSS and SSS displayed controlled type-I-errors. Confidence intervals were created using a non-parametric (resampling method) and parametric (resimulation method) bootstrap for a backcross population derived from inbred lines.

QTLs explaining 1%, 5 % and 10 % of the phenotypic variance were tested in populations of or individuals. Smith CAB () A non-parametric test for linkage with a quantitative character.

Ann Hum Genet – PubMed CrossRef Google Scholar Soller M, Brody T () On the power of experimental designs for the detection of linkage between marker loci. Abstract. Linkage analysis is used to map genetic loci using observations on relatives. It can be applied to both major gene disorders (parametric linkage) and complex diseases (model-free or non-parametric linkage), and it can be based on either a relatively small number of microsatellite markers or a denser map of single nucleotide polymorphisms (SNPs).

To detect QTLs, non-parametric or model free linkage analysis uses a similar linkage concept as described above, but unlike parametric linkage, no explicit model of the disease is required for this type of genomic search. Non-parametric methods were originally developed for sibling pairs but have been extended to general pedigrees.

Non-parametric methods based on combinatorial arguments have also been proposed for gene–gene interaction detection, for instance the combinatorial partitioning method (CPM), originally developed for quantitative outcomes, and the multivariate dimensionality reduction (MDR) method for discrete outcomes in balanced case-control studies.

The. Sex-specific maps and consequences for linkage mapping. Parametric vs. Non-parametric and Two-point vs. Multipoint: Controversies in Gene Mapping Methods for detecting horizontal transfer of genes Rickettsia Computational Methods for High Throughput Genetic Analysis - Expression profiling.

Affected sib pairs are widely used in human genetic linkage studies. Simple non-parametric tests, such as mean and proportion tests have been proposed for detecting linkage between the disease of.

@article{osti_, title = {Methods for detecting additional genes underlying Alzheimer disease}, author = {Locke, P A and Haines, J L and Ter-Minassian, M}, abstractNote = {Alzheimer`s disease (AD) is a complex inherited disorder with proven genetic heterogeneity.

To date, genes on chromosome 21 (APP) and 14 (not yet identified) are associated with early-onset familial AD, while the APOE.Explanation of Bio-states under guidance of Dr. Lokendra Sharma.Non-parametric MANOVA methods for detecting differentially expressed genes in real-time RT-PCR experiments.

Future research will focus on comparison of such methods with classical strategies for analysing RT-PCR data; moreover, work will also concentrate on extending such methods to doubly multivariate design.

Genetics. Systems biology.