Statistical methods for microarray data

Microarray analysis is particularly interesting from a statistical point of view since already a wide range of methods has been applied in the interpretation of the data and there is doubtless more to come. The purpose of this introduction is to collect analysis methods proposed in several papers, provide the details that are often missing, use a uniform notation, indicate in which direction results might be generalized or applied, and thus make the material more accessible to the non-statistician. Essentially this is a cleaned version of the notes I made when reading these papers. As a short glance at this review shows though, the reader is expected to be fairly familiar with mathematical concepts such differentiation and integration, manipulation of equations, some vector and matrix algebra, concepts from probability theory such as Bayes theorem or the mathematical properties of the Normal probability density function.