NDLI: Gene expression data: The technology and statistical analysis

Content Provider	Springer Nature Link
Author	Craig, B. A. Black, M. A. Doerge, R. W.
Copyright Year	2003
Abstract	The desire to view the simultaneous behavior of genes affected by a stimulus at the total genome level has brought the scientific world to a new place in history. It is now commonplace to have an experiment that investigates the expression of thousands of genes across treatments and time points. Biologists are quickly understanding that in order to make sense of these data and the variation that is inherent in the experimental process, statistical models need to be employed. This article presents important aspects of the two most common microarray technologies, the spotted array and the oligonucleotide array, for the purpose of identifying common and unique features of each technology and the data produced. Statistical models are suggested, and the statistical literature reviewed, in an attempt to bring some level of simplicity to the daunting task of analyzing these data. We include two examples, each based upon one of the different technologies, suggesta statistical model, and present the results of the analyses in hopes of providing both encouragement and guidance to readers wanting to become more involved in this exciting field known as genomics.
Starting Page	1
Ending Page	28
Page Count	28
File Format	PDF
ISSN	10857117
Journal	Journal of Agricultural, Biological, and Environmental Statistics
Volume Number	8
Issue Number	1
e-ISSN	15372693
Language	English
Publisher	Springer-Verlag
Publisher Date	2003-01-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Hypothesis testing Linear models Microarrays Multiple comparisons Statistical genetics Statistics for Life Sciences, Medicine, Health Sciences Agriculture Environmental Monitoring/Analysis Biostatistics
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Statistics and Probability Environmental Science Agricultural and Biological Sciences Statistics, Probability and Uncertainty

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