1st Edition
Gene Expression Studies Using Affymetrix Microarrays
The Affymetrix GeneChip® system is one of the most widely adapted microarray platforms. However, due to the overwhelming amount of information available, many Affymetrix users tend to stick to the default analysis settings and may end up drawing sub-optimal conclusions. Written by a molecular biologist and a biostatistician with a combined decade of experience in practical expression profiling experiments and data analyses, Gene Expression Studies Using Affymetrix Microarrays tears down the omnipresent language barriers among molecular biology, bioinformatics, and biostatistics by explaining the entire process of a gene expression study from conception to conclusion.
Truly Multidisciplinary: Merges Molecular Biology, Bioinformatics, and Biostatistics
This authoritative resource covers important technical and statistical pitfalls and problems, helping not only to explain concepts outside the domain of researchers, but to provide additional guidance in their field of expertise. The book also describes technical and statistical methods conceptually with illustrative, full-color examples, enabling those inexperienced with gene expression studies to grasp the basic principles.
Gene Expression Studies Using Affymetrix Microarrays provides novices with a detailed, yet focused introductory course and practical user guide. Specialized experts will also find it useful as a translation dictionary to understand other involved disciplines or to get a broader picture of microarray gene expression studies in general. Although focusing on Affymetrix gene expression, this globally relevant guide covers topics that are equally useful for other microarray platforms and other Affymetrix applications.
Biological question
Why gene expression?
Biotechnological advancements
Research Question
Main types of research questions
Affymetrix microarrays
Probes
Probe sets
Array types
Standard lab processes
Affymetrix data quality
Running the experiment
Biological experiment
Microarray experiment
Data analysis preparation
Data preprocessing
Quality control
Data analysis
Why do we need statistics?
The curse of high-dimensionality
Gene filtering
Unsupervised data exploration
Detecting differential expression
Supervised prediction
Pathway analysis
Other analysis approaches
Presentation of results
Data visualization
Biological Interpretation
Data publishing
Reproducible research
Pharmaceutical R&D
The need for early indications
Critical Path Initiative
Drug Discovery
Drug Development
Clinical Trials
Using R and Bioconductor
R and Bioconductor
R and Sweave
R and Eclipse
Automated array analysis
Other software for microarray analysis
Future Perspectives
Co-analyzing different data types
The microarrays of the future
Next-gen sequencing: The end for microarrays?
Bibliography
Biography
Hinrich Göhlmann and Willem Talloen work at Johnson & Johnson Pharmaceutical R&D as Principal Scientist and Senior Biostatistician, respectively.
… useful for practitioners working in gene expression studies … a valuable self-contained introductory material presenting all aspects of gene expression studies using Affymetrix microarrays. The book is well-arranged. The inserted boxes explaining biological or statistical concepts help to make the book very readable. … a well-written overview over a broad range of problems and solutions with the interpretation. …
—ISCB News, No. 51, June 2011…The book is very well organized and well written, and covers many of the major topics of microarrays experiments … A nice feature of this book, and one which makes it very pleasant to read, is the use of full-color illustrations and plots, as well as boxes with some highlighted information, such as biological and statistical concepts. …
—Guilherme J.M. Rosa, Biometrics, December 2010The target audience of this book is practicing biologists making use of microarray technology, but it may be of great interest to their statistician collaborators or statisticians new to the field. … When I began investigating bioinformatics as a statistics graduate student several years ago, it would have saved me a great deal of time to have a single resource such as this to help me understand this aspect of the field. … Chapter 5 … essentially serves as a catalog of commonly applied statistical methods for gene expression (or more generally, high-dimensional) data. The breadth of this catalog is impressive. …
—Journal of the American Statistical Association, Sept. 2010, Vol. 105, No. 491"Written by a molecular biologist and a biostatistician with a combined decade of experience in practical expression profling experiments and data analyses, this text tears down the omnipresent language barriers among molecular biology, bioinformatics,and biostatistics by explaining the entire process of a gene expression study from conception to conclusion."
—Zentralblatt MATH