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E-raamat: Statistical Methods in Molecular Biology

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Thisbookisintendedformolecularbiologistswhoperformquantitativeanalysesond ata emanatingfromtheir eldandforthestatisticianswhoworkwithmolecularbiologists andotherbiomedicalresearchers. Therearemanyexcellenttextbooksthatprovidefun- mentalcomponentsforstatisticaltrainingcurricula. Therearealsomany"byexpertsfor experts"booksinstatisticsandmolecularbiologywhichrequirein-depthknowledgein bothsubjectstobetakenfulladvantageof. Sofar,nobookinstatisticshasbeenpublished thatprovidesthebasicprinciplesofproperstatisticalanalysesandprogressestoamore advancedstatisticsinresponsetorapidlydevelopingtechnologiesandmethodologiesin the eldofmolecularbiology. Respondingtothissituation,ourbookaimsatbridgingthegapbetweenthesetwo extremes. Molecularbiologistswillbene tfromtheprogressivestyleofthebookwhere basicstatisticalmethodsareintroducedandgraduallyelevatedtoanintermediatelevel . Similarly,statisticianswillbene tfromlearningthevariousbiologicaldatagenerate dfrom the eldofmolecularbiology,thetypesofquestionsofinteresttomolecularbiologists, andthestatisticalapproachestoanalyzingthedata. Thestatisticalconceptsandmethods relevanttostudiesinmolecularbiologyarepresentedinasimpleandpracticalmanner. Speci cally,thebookcoversbasicandintermediatestatisticsthatareusefulforclassi cal and molecular biology settings and advanced statistical techniques that can be used to helpsolveproblemscommonlyencounteredinmodernmolecularbiologystudies,such assupervisedandunsupervisedlearning,hiddenMarkovmodels,manipulationandan- ysisofdatafromhigh-throughputmicroarrayandproteomicplatform,andsynthesisof these evidences. A tutorial-type format is used to maximize learning in some chapters. Advicefromjournaleditorsonpeer-reviewedpublicationandsomeusefulinformationon softwareimplementationarealsoprovided. Thisbookisrecommendedforuseassupplementarymaterialbothinsideandoutside classroomsorasaself-learningguideforstudents,scientists,andresearcherswhodeal with numericdatainmolecularbiologyandrelated elds. Thosewhostartasbeginners,but desiretobeatanintermediatelevel,will ndthisbookespeciallyusefulintheirlearnin g pathway. WewanttothankJohnWalker(serieseditor),PatrickMarton,DavidCasey,andAnne Meagher,(editorsatSpringerandHumana)andShanthyJaganathan(Integra-India). The followingpersonsprovidedusefuladviceandcommentsonselectionoftopics,referralto expertsineachtopic,and/orchapterreviewsthatwetrulyappreciate:StephenLooney(a former editor of this book), Stan Young, Dmitri Zaykin, Douglas Hawkins, Wei Pan, Alexandre Almeida, John Ho, Rebecca Doerge, Paula Trushin, Kevin Morgan, Jason Osborne,PeterWestfall,JennyXiang,Ya-linChiu,YolandaBarron,HuiboShao,Alvin Mushlin,andRonaldFanta. Drs. Bang,Zhou,andMazumdarwerepartiallysupported byClinicalTranslationalScienceCenter(CTSC)grant(UL1-RR024996). HeejungBang vii Contents Preface...vii Contributors...xi PARTIBASICSTATISTICS...1 1. ExperimentalStatisticsforBiologicalSciences...3 HeejungBangandMarieDavidian 2. NonparametricMethodsforMolecularBiology...105 KnutM. WittkowskiandTingtingSong 3. BasicsofBayesianMethods...155 SujitK. Ghosh 4. TheBayesiant-TestandBeyond ...179 MithatGonen PARTII DESIGNSANDMETHODSFORMOLECULARBIOLOGY...201 5. SampleSizeandPowerCalculationforMolecularBiologyStudies...203 Sin-HoJung 6. DesignsforLinkageAnalysisandAssociationStudiesofComplexDiseases...219 YuehuaCui,GengxinLi,ShaoyuLi,andRonglingWu 7. IntroductiontoEpigenomicsandEpigenome-WideAnalysis...243 MelissaJ. FazzariandJohnM. Greally 8. Exploration,Visualization,andPreprocessingofHigh-DimensionalData...267 ZhijinWuandZhiqiangWu PARTIII STATISTICALMETHODSFORMICROARRAYDATA ...285 9. IntroductiontotheStatisticalAnalysisofTwo-ColorMicroarrayData...287 MartinaBremer,EdwardHimelblau,andAndreasMadlung 10. BuildingNetworkswithMicroarrayData...315 BradleyM. Broom,WareeRinsurongkawong,LajosPusztai, andKim-AnhDo PARTIV ADVANCEDORSPECIALIZEDMETHODSFORMOLECULARBIOLOGY. . 345 11. SupportVectorMachinesforClassi cation:AStatisticalPortrait...347 YoonkyungLee 12. AnOverviewofClusteringAppliedtoMolecularBiology ...369 RebeccaNugentandMarinaMeila ix xContents 13. HiddenMarkovModelandItsApplicationsinMotifFindings...405 JingWuandJunXie 14. DimensionReductionforHigh-DimensionalData...417 LexinLi 15. IntroductiontotheDevelopmentandValidationofPredictiveBiomarker ModelsfromHigh-ThroughputDataSets ...435 XutaoDengandFabienCampagne 16. Multi-geneExpression-basedStatisticalApproachestoPredicting Patients'ClinicalOutcomesandResponses...471 FengCheng,Sang-HoonCho,andJaeK. Lee 17. Two-StageTestingStrategiesforGenome-WideAssociationStudies inFamily-BasedDesigns ...485 AmyMurphy,ScottT. Weiss,andChristophLange 18. StatisticalMethodsforProteomics ...497 KlausJung PARTVMETA-ANALYSISFORHIGH-DIMENSIONALDATA ...509 19. StatisticalMethodsforIntegratingMultipleTypesofHigh-ThroughputData. . 511 YangXieandChulAhn 20. ABayesianHierarchicalModelforHigh-DimensionalMeta-analysis...531 FeiLiu 21. MethodsforCombiningMultipleGenome-WideLinkageStudies...541 TreciaA. KippolaandStephanieA. Santorico PARTVI OTHERPRACTICALINFORMATION ...561 22. ImprovedReportingofStatisticalDesignandAnalysis:Guidelines, Education,andEditorialPolicies...5 63 MadhuMazumdar,SampritBanerjee,andHeatherL. VanEpps 23. StataCompanion...599 JenniferSousaBrennan SubjectIndex...627 Contributors CHULAHN* Division of Biostatistics, Department of Clinical Sciences, The Harold C.

Arvustused

"Here is a comprehensive book that systematically covers both basic and advanced statistical topics in molecular biology, including parametric and nonparametric, and frequentist and Bayesian methods. I am highly impressed by the breadth and depth of the applications. I strongly recommend this book for both statisticians and biologists who need to communicate with each other in this exciting field of research." (Robert C. Elston, PhD., Director, Division of Genetic and Molecular Epidemiology, Case Western Reserve University)



"An extraordinary exposition of the central topics of modern molecular biology, presented by practicing experts who weave together rigorous theory with practical techniques and illustrative examples." (George C. Newman, MD, PhD, Chairman, Neurosensory Sciences, Albert Einstein Medical Center)



"I cannot think of anything we need now in translation research field more than more efficient cross talk between molecular biology and statistics. This book is just on target. It fills the gap." (Iman Osman, MB, BCh, MD, Director, Interdisciplinary Melanoma Cooperative Program, New York University Langone Medical Center)

Preface vii
Contributors xi
PART I BASIC STATISTICS
1(200)
Experimental Statistics for Biological Sciences
3(102)
Heejung Bang
Marie Davidian
Nonparametric Methods for Molecular Biology
105(50)
Knut M. Wittkowski
Tingting Song
Basics of Bayesian Methods
155(24)
Sujit K. Ghosh
The Bayesian t-Test and Beyond
179(22)
Mithat Gonen
PART II DESIGNS AND METHODS FOR MOLECULAR BIOLGY
201(84)
Sample Size and Power Calculation for Molecular Biology Studies
203(16)
Sin-Ho Jung
Designs for Linkage Analysis and Association Studies of Complex Diseases
219(24)
Yuehua Cui
Gengxin Li
Shaoyu Li
Rongling Wu
Introduction to Epigenomics and Epigenome-Wide Analysis
243(24)
Melissa J. Fazzari
John M. Greally
Exploration, Visualization, and Preprocessing of High-Dimensional Data
267(18)
Zhijin Wu
Zhiqiang Wu
PART III STATISTICAL METHODS FOR MICROARRAY DATA
285(60)
Introduction to the Statistical Analysis of Two-Color Microarray Data
287(28)
Martina Bremer
Edward Himelblau
Andreas Madlung
Building Networks with Microarray Data
315(30)
Bradley M. Broom
Waree Rinsurongkawong
Lajos Pusstai
Kim-Anh Do
PART IV ADVANCED OR SPECIALIZED METHODS FOR MOLECULAR BIOLOGY
345(164)
Support Vector Machines for Classification: A Statistical Portrait
347(22)
Yoonkyung Lee
An Overview of Clustering Applied to Molecular Biology
369(36)
Rebecca Nugent
Marina Meila
Hidden Markov Model and its Applications in Motif Findings
405(12)
Jing Wu
Jun Xie
Dimension Reduction for High-Dimensional Data
417(18)
Lexin Li
Introduction to the Development and Validation of Predictive Biomarker Models from High-Throughput Data Sets
435(36)
Xutao Deng
Fabien Campagne
Multi-gene Expression-based Statistical Approaches to Predicting Patients' Clinical Outcomes and Responses
471(14)
Feng Cheng
Sang-Hoon Cho
Jae K. Lee
Two-Stage Testing Strategies for Genome-Wide Association Studies in Family-Based Designs
485(12)
Amy Murphy
Scott T. Weiss
Christoph Lange
Statistical Methods for Proteomics
497(12)
Klaus Jung
PART V META-ANALYSIS FOR HIGH-DIMENSIONAL DATA
509(52)
Statistical Methods for Integrating Multiple Types of High-Throughput Data
511(20)
Yang Xie
Chul Ahn
A Bayesian Hierarchical Model for High-Dimensional Meta-analysis
531(10)
Fei Liu
Methods for Combining Multiple Genome-Wide Linkage Studies
541(20)
Trecia A. Kippola
Stephanie A. Santorico
PART VI OTHER PRACTICAL INFORMATION
561(66)
Improved Reporting of Statistical Design and Analysis: Guidelines, Education, and Editorial Policies
563(36)
Madhu Mazumdar
Samprit Banerjee
Heather L. Van Epps
Stata Companion
599(28)
Jennifer Sousa Brennan
Subject Index 627
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