© 2010

Handbook on Analyzing Human Genetic Data

Computational Approaches and Software


  • Focus on computational methods and associated software

  • Competing methods and software are compared and relative advantages and disadvantages highlighted

  • Helps to select the appropriate methods for a particular genetic problem


Table of contents

  1. Front Matter
    Pages 1-12
  2. Bruce Weir
    Pages 1-23
  3. Yu Zhang, Tianhua Niu
    Pages 25-79
  4. Mingyao Li, Gonçalo R. Abecasis
    Pages 81-118
  5. Christopher I. Amos, Bo Peng, Yaji Xu, Jianzhong Ma
    Pages 119-145
  6. Robert P. Igo, Yuqun Luo Jr., Shili Lin
    Pages 147-169
  7. Xiaofeng Zhu, ShuangLin Zhang
    Pages 171-190
  8. Kui Zhang, Hongyu Zhao
    Pages 191-240
  9. Michael P. Epstein, Lydia C. Kwee
    Pages 241-276
  10. Qingrun Zhang, Jurg Ott
    Pages 277-287
  11. Mitchell H. Gail, Nilanjan Chatterjee
    Pages 289-305
  12. Cliona Molony, Solveig K. Sieberts, Eric E. Schadt
    Pages 307-330
  13. Back Matter
    Pages 1-3

About this book


The discipline of statistical genetics is highly computational. Be it exact computational methods, simulation based, or a hybrid of the two, computational packages are indispensable tools and constant companions of researchers in the field. This handbook is intended to provide human geneticists and other biomedical researchers with guidance on selections of appropriate computational methods and software packages for their specific genetic problems. It may also be used by students and other learners as a reference in conjunction with a more theoretical and/or methodologically oriented text book. This book tries to strike a balance between methodological expositions and practical guidelines for software selections. Wherever possible, comparisons among competing methods and software are made to highlight the relative advantages and disadvantage of the approaches so that the readers can make informed choices to best match their specific needs.


DNA association studies gene expression genes genetics genome analysis linkage analysis statistical genetics

Authors and affiliations

  1. 1.Dept. StatisticsOhio State UniversityColumbusU.S.A.
  2. 2.School of MedicineYale UniversityNew HavenU.S.A.

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