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Considered highly exotic tools as recently as the late 1990s,
microarrays are now ubiquitous in biological research. Traditional
statistical approaches to design and analysis were not developed to
handle the high-dimensional, small sample problems posed by
microarrays. In just a few short years the number of statistical
papers providing approaches to analyzing microarray data has gone
from almost none to hundreds if not thousands. This overwhelming
deluge is quite daunting to either the applied investigator looking
for methodologies or the methodologist trying to keep up with the
field. DNA Microarrays and Related Genomics Techniques: Design,
Analysis, and Interpretation of Experiments consolidates
discussions of methodological advances into a single volume. The
book's structure parallels the steps an investigator or an analyst
takes when conducting and analyzing a microarray experiment from
conception to interpretation. It begins with foundational issues
such as ensuring the quality and integrity of the data and
assessing the validity of the statistical models employed, then
moves on to cover critical aspects of designing a microarray
experiment. The book includes discussions of power and sample size,
where only very recently have developments allowed such
calculations in a high dimensional context, followed by several
chapters covering the analysis of microarray data. The amount of
space devoted to this topic reflects both the variety of topics and
the effort investigators have devoted to developing new
methodologies. In closing, the book explores the intellectual
frontier - interpretation of microarray data. It discusses new
methods for facilitating and affecting formalization of the
interpretation process and the movement to make large high
dimensional datasets public for further analysis, and methods for
doing so. There is no question that this field will continue to
advance rapidly and some of the specific methodologies discussed in
this book wil
Considered highly exotic tools as recently as the late 1990s,
microarrays are now ubiquitous in biological research. Traditional
statistical approaches to design and analysis were not developed to
handle the high-dimensional, small sample problems posed by
microarrays. In just a few short years the number of statistical
papers providing approaches to analyzing microarray data has gone
from almost none to hundreds if not thousands. This overwhelming
deluge is quite daunting to either the applied investigator looking
for methodologies or the methodologist trying to keep up with the
field. DNA Microarrays and Related Genomics Techniques: Design,
Analysis, and Interpretation of Experiments consolidates
discussions of methodological advances into a single volume. The
book's structure parallels the steps an investigator or an analyst
takes when conducting and analyzing a microarray experiment from
conception to interpretation. It begins with foundational issues
such as ensuring the quality and integrity of the data and
assessing the validity of the statistical models employed, then
moves on to cover critical aspects of designing a microarray
experiment. The book includes discussions of power and sample size,
where only very recently have developments allowed such
calculations in a high dimensional context, followed by several
chapters covering the analysis of microarray data. The amount of
space devoted to this topic reflects both the variety of topics and
the effort investigators have devoted to developing new
methodologies. In closing, the book explores the intellectual
frontier - interpretation of microarray data. It discusses new
methods for facilitating and affecting formalization of the
interpretation process and the movement to make large high
dimensional datasets public for further analysis, and methods for
doing so. There is no question that this field will continue to
advance rapidly and some of the specific methodologies discussed in
this book wil
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