| Main Title |
The Statistics of Gene Mapping [electronic resource] / |
| Type |
EBOOK |
| Author |
Siegmund, David.
|
| Other Authors |
|
| Publisher |
Springer New York, |
| Year Published |
2007 |
| Call Number |
QH431 |
| ISBN |
9780387496863 |
| Subjects |
Medicine ;
Human genetics ;
Computer simulation ;
Bioinformatics ;
Animal genetics ;
Genetics--Mathematics ;
Statistics
|
| Internet Access |
|
| Collation |
XIX, 331 p. online resource. |
| Notes |
Due to license restrictions, this resource is available to EPA employees and authorized contractors only |
| Contents Notes |
Background and Preparations -- Background in Statistics -- to Experimental Genetics -- Fundamentals of Genetics: Inbreeding, Recombination, Random Mating, and Identity by Descent -- Experimental Genetics -- Testing for Linkage with a Single Marker -- Whole Genome Scans: The Significance Level -- Statistical Power and Confidence Regions -- Missing Data and Interval Mapping -- Advanced Topics -- Human Genetics -- Mapping Qualitative Traits in Humans Using Affected Sib Pairs -- Admixture Mapping -- Mapping Complex and Quantitative Traits with Data from Human Pedigrees -- Association Studies -- Inferring Haplotypes from Genotypes and Testing Association. Gene mapping is used in experimental genetics to improve the hardiness or productivity of animals or plants of agricultural value, to explore basic mechanisms of inheritance, or to study animal models of human inheritance. In human populations it is used as a first step to identify genes associated with human health and disease. This book presents a unified discussion of the statistical concepts applied in gene mapping, first in the experimental context of crosses of inbred lines and then in outbred populations, primarily humans. The development involves elementary principles of probability and statistics, which are implemented by computational tools based on the R programming language to simulate genetic experiments and evaluate statistical analyses. The viewpoint reflects the modern approach of using anonymous DNA markers distributed throughout the genome to identify regions likely to contain genes of interest. The reader is assumed to have some familiarity with probability/statistics and with elementary genetics. Important topics are reviewed in the first three chapters. The R programming language is developed in the text. Each chapter contains exercises, both theoretical and computational, some routine and others that are more challenging. The book is suitable for upper level undergraduate students or graduate students of genetics or statistics. David Siegmund is the John D. and Sigrid Banks Professor in the Department of Statistics,Stanford University. He has been a visitor at The Hebrew University, the University of Zurich, the University of Heidelberg, the National University of Singapore, and the Free University of Amsterdam. He is a member of the National Academy of Sciences (USA) and the American Academy of Arts and Sciences. Benjamin Yakir is Associate Professor of Statistics at The Hebrew University of Jerusalem and has been a visiting professor at Stanford University, the University of Pennsylvania, and the National University of Singapore. |
| Place Published |
New York, NY |
| Corporate Au Added Ent |
SpringerLink (Online service) |
| Title Ser Add Ent |
Statistics for Biology and Health, |
| Host Item Entry |
Springer eBooks |
| PUB Date Free Form |
2007 |
| Series Title Untraced |
Statistics for Biology and Health, |
| BIB Level |
m |
| Medium |
computer |
| Content |
text |
| Carrier |
online resource |
| Cataloging Source |
OCLC/T |
| OCLC Time Stamp |
20131217192215 |
| Language |
eng |
| Origin |
SPRINGER |
| Type |
EBOOK |
| OCLC Rec Leader |
04516nam a22005775i 45 |
