TY - JOUR
T1 - Basic microarray analysis
T2 - Grouping and feature reduction
AU - Raychaudhuri, Soumya
AU - Sutphin, Patrick D.
AU - Chang, Jeffrey T.
AU - Altman, Russ B.
N1 - Funding Information:
This work is supported by NIH LM06244 and GM61374, as well as NSF DBI-9600637 and a grant from the Burroughs-Wellcome Foundation. SR is supported by NIH GM-07365. PDS is supported by NIH CA-88480 and JTC is supported by a Stanford Graduate Fellowship. The authors thank Amato Giaccia for very helpful discussions.
PY - 2001/5/1
Y1 - 2001/5/1
N2 - DNA microarray technologies are useful for addressing a broad range of biological problems - including the measurement of mRNA expression levels in target cells. These studies typically produce large data sets that contain measurements on thousands of genes under hundreds of conditions. There is a critical need to summarize this data and to pick out the important details. The most common activities, therefore, are to group together microarray data and to reduce the number of features. Both of these activities can be done using only the raw microarray data (unsupervised methods) or using external information that provides labels for the microarray data (supervised methods). We briefly review supervised and unsupervised methods for grouping and reducing data in the context of a publicly available suite of tools called CLEAVER, and illustrate their application on a representative data set collected to study lymphoma.
AB - DNA microarray technologies are useful for addressing a broad range of biological problems - including the measurement of mRNA expression levels in target cells. These studies typically produce large data sets that contain measurements on thousands of genes under hundreds of conditions. There is a critical need to summarize this data and to pick out the important details. The most common activities, therefore, are to group together microarray data and to reduce the number of features. Both of these activities can be done using only the raw microarray data (unsupervised methods) or using external information that provides labels for the microarray data (supervised methods). We briefly review supervised and unsupervised methods for grouping and reducing data in the context of a publicly available suite of tools called CLEAVER, and illustrate their application on a representative data set collected to study lymphoma.
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U2 - 10.1016/S0167-7799(01)01599-2
DO - 10.1016/S0167-7799(01)01599-2
M3 - Review article
C2 - 11301132
AN - SCOPUS:0035342091
SN - 0167-7799
VL - 19
SP - 189
EP - 193
JO - Trends in Biotechnology
JF - Trends in Biotechnology
IS - 5
ER -