Ebook: Modeling Dose-Response Microarray Data in Early Drug Development Experiments Using R: Order-Restricted Analysis of Microarray Data
Author: Bijnens Luc, Shkedy Ziv, Lin Dan, Yekutieli Daniel, Amaratunga Dhammika
- Tags: Bio-informatique, Biologie--Informatique, Drugs--Dose-response relationship--Computer simulation, Drugs--Testing--Computer simulation, Statistique, Techniques pharmaceutiques, DNA microarrays, Livres électroniques, Livres numériques, Drugs -- Dose-response relationship -- Computer simulation, Drugs -- Testing -- Computer simulation, Biologie -- Informatique
- Series: Use R!
- Year: 2012
- Publisher: Imprint
- City: Berlin;Heidelberg
- Language: English
- pdf
This book focuses on the analysis of dose-response microarray data in pharmaceutical setting, the goal being to cover this important topic for early drug development and to provide user-friendly R packages that can be used to analyze dose-response microarray data. It is intended for biostatisticians and bioinformaticians in the pharmaceutical industry, biologists, and biostatistics/bioinformatics graduate students.
Part I of the book is an introduction, in which we discuss the dose-response setting and the problem of estimating normal means under order restrictions. In particular, we discuss the pooled-adjacent-violator (PAV) algorithm and isotonic regression, as well as the likelihood ratio test and non-linear parametric models, which are used in the second part of the book.
Part II is the core of the book. Methodological topics discussed include:
· Multiplicity adjustment
· Test statistics and testing procedures for the analysis of dose-response microarray data
· Resampling-based inference and use of the SAM method at the presence of small-variance genes in the data
· Identification and classification of dose-response curve shapes
· Clustering of order restricted (but not necessarily monotone) dose-response profiles
· Hierarchical Bayesian models and non-linear models for dose-response microarray data
· Multiple contrast tests
All methodological issues in the book are illustrated using four "real-world" examples of dose-response microarray datasets from early drug development experiments.