Mathematical and statistical methods for genetic analysis / Kenneth Lange.

Author
Lange, Kenneth [Browse]
Format
Book
Language
English
Published/​Created
New York : Springer, 1997.
Description
xii, 265 pages : illustrations ; 24 cm.

Availability

Copies in the Library

Location Call Number Status Location Service Notes
Lewis Library - Stacks QH438.4.M33 L36 1997 Browse related items Request

    Details

    Subject(s)
    Series
    Statistics for biology and health [More in this series]
    Bibliographic references
    Includes bibliographical references and index.
    Contents
    • 1. Basic principles of population genetics : 1.1. Introduction ; 1.2. Genetics background ; 1.3. Hardy-Weinberg equilibrium ; 1.4. Linkage equilibrium ; 1.5. Selection ; 1.6. Balance between mutation and selection ; 1.7. Problems
    • 2. Counting methods and the EM algorithm : 2.1. Introduction ; 2.2. Gene counting ; 2.3. Description of the EM algorithm ; 2.4. Ascent property of the EM algorithm ; 2.5. Allele frequency estimation by the EM algorithm ; 2.6. Classical segregation analysis by the EM algorithm ; 2.7. Problems
    • 3. Newton's method and scoring : 3.1. Introduction ; 3.2. Newton's method ; 3.3. Scoring ; 3.4. Application to the design of linkage experiments ; 3.5. Quasi-Newton methods ; 3.6. The Dirichlet distribution ; 3.7. Empirical Bayes estimation of allele frequencies ; 3.8. Problems
    • 4. Hypothesis testing and categorical data : 4.1. Introduction ; 4.2. Hypotheses about genotype frequencies ; 4.3. Other multinomial problems in genetics ; 4.4. The Zmax test ; 4.5. The Wd statistic ; 4.6. Exact tests of independence ; 4.7. Problems
    • 5. Genetic identity coefficients : 5.1. Introduction ; 5.2. Kinship and inbreeding coefficients ; 5.3. Condensed identity coefficients ; 5.4. Generalized kinship coefficients ; 5.5. From kinship to identity coefficients ; 5.6. Calculation of generalized kinship coefficients ; 5.7. Problems.
    • 6. Applications of identity coefficients : 6.1. Introduction ; 6.2. Genotype prediction ; 6.3. Covariance for a quantitative trait ; 6.4. Risk ratios and genetic model discrimination ; 6.5. An affecteds-only method of linkage analysis ; 6.6. Problems
    • 7. Computation of Mendelian likelihoods : 7.1. Introduction ; 7.2. Mendelian models ; 7.3. Genotype elimination and allele consolidation ; 7.4. Array transformations and iterated sums ; 7.5. Array factoring ; 7.6. Examples of pedigree analysis ; 7.7. Problems
    • 8. The polygenic model : 8.1. Introduction ; 8.2. Maximum likelihood estimation by scoring ; 8.3. Application to Gc measured genotype data ; 8.4. Multivariate traits ; 8.5. Left and right-hand finger ridge counts ; 8.6. The hypergeometric polygenic model ; 8.7. Application to risk prediction ; 8.8. Problems
    • 9. Markov chain Monte Carlo methods : 9.1. Introduction ; 9.2. Review of discrete-time Makov chains ; 9.3. The Hastings-metropolis algorithm and simulated annealing ; 9.4. Descent states and descent graphs ; 9.5. Descent trees and the founder tree graph ; 9.6. The descent graph Markov chain ; 9.7. Computing location scores ; 9.8. Finding a legal descent graph ; 9.9. Haplotyping ; 9.10 Application to episodic ataxia ; 9.11. Problems
    • 10. Reconstruction of evolutionary trees : 10.1. Introduction ; 10.2. Evolutionary trees ; 10.3. Maximum parsimony ; 10.4. Review of continuous-time Markov chains ; 10.5. A nucleotide substitution model ; 10.6. Maximum likelihood reconstruction ; 10.7. Origin of the eukaryotes ; 10.8. Problems.
    • 11. Radiation hybrid mapping : 11.1. Introduction ; 11.2. Models ; 11.3. Minimum obligate breaks criterion ; 11.4. maximum likelihood methods ; 11.5. Application to haploid data ; 11.6. Polyploid radiation hybrids ; 11.7. Maximum likelihood under polyploidy ; 11.8. Obligate breaks under polyploidy ; 11.9. Bayesian methods ; 11.10. Applications to diploid data ; 11.11. Problems
    • 12. Models of recombination : 12.1. Introduction ; 12.2. Mather's formula and its generalization ; 12.3. Count-location model ; 12.4. Stationary renewal models ; 12.5. Poisson-skip model ; 12.6. Chiasma interference ; 12.7. Application to drosophila data ; 12.8. Problems
    • 13. Poisson approximation : 13.1. Introduction ; 13.2. Poisson approximation to the Wd statistic ; 13.3. Construction of somatic cell hybrid panels ; 13.4. Biggest marker gap ; 13.5 Randomness of restriction sites ; 13.6. DNA sequence matching ; 13.7. Problems.
    ISBN
    • 0387949097 ((hc ; : alk. paper))
    • 9780387949093 ((hc ; : alk. paper))
    LCCN
    96049533
    OCLC
    35928412
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