This book presents the statistical aspects of designing,
analyzing and interpreting the results of genome-wide association
scans (GWAS studies) for genetic causes of disease using unrelated
subjects. Particular detail is given to the practical aspects of
employing the bioinformatics and data handling methods necessary to
prepare data for statistical analysis. The goal in writing this
book is to give statisticians, epidemiologists, and students in
these fields the tools to design a powerful genome-wide study based
on current technology. The other part of this is showing readers
how to conduct analysis of the created study.
Design and Analysis of Genome-Wide Association Studies provides
a compendium of well-established statistical methods based upon
single SNP associations. It also provides an introduction to more
advanced statistical methods and issues. Knowing that technology,
for instance large scale SNP arrays, is quickly changing, this text
has significant lessons for future use with sequencing data.
Emphasis on statistical concepts that apply to the problem of
finding disease associations irrespective of the technology ensures
its future applications. The author includes current bioinformatics
tools while outlining the tools that will be required for use with
extensive databases from future large scale sequencing projects.
The author includes current bioinformatics tools while outlining
additional issues and needs arising from the extensive databases
from future large scale sequencing projects.
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