By Aidong Zhang
This booklet is particularly good written, in nice aspect and readability. The identify "Advanced" sounds formidable to a few intermediate or access point statisticians, however the math info within the ebook is especially comprehensible, offered as invaluable help with the intention to comprehend the defined statistical equipment.
I could hugely suggest this publication to statisticians with all statistical backgrounds who're new to the realm of microarray info research. This ebook is ideal as a textbook for a primary process microarray info research too.
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Additional info for Advanced analysis of gene expression microarray data
Image Processing The microarray image generated by the scanner forms the raw data of a microarray experiment. Prior to data analysis, the image must be converted from the TIFF format into the numerical information that quantifies gene expression. The manner in which this is accomplished will have a major impact on the quality of the resulting data and the success of further analysis. For in situ synthesized microarrays, both Affymetrix and Agilent have integrated tailored image-processing algorithms into their software packages, allowing end-users to directly generate quantified microarray data.
Missing d a t a may also occur systematically as a result of the robotic methods employed in generating the microarrays . Unfortunately, many algorithms for gene expression analysis require a complete d a t a set as input. Therefore, methods for estimating missing d a t a are 44 Advanced Analysis of Gene Expression Microarray Data needed before these algorithms can be applied. Suppose a micraorray data set is represented by a matrix where each row corresponds to one gene and each column represents an experimental condition.
1 Microarray D a t a Cleaning and Preprocessing Data Transformation It is common practice to transform DNA microarray d a t a from the raw intensities into log intensities before proceeding with analysis. There are several objectives of this transformation : • There should be a reasonable even spread of features across the intensity range. • Variability should be constant at all intensity levels. • T h e distribution of experimental errors should be approximately zero. • T h e distribution of intensities should be approximately bell-shaped.
Advanced analysis of gene expression microarray data by Aidong Zhang