A non-transformation method for identifying differentially expressed genes from cDNA microarrays.
cDNA microarray data are subject to many sources of variation that have to be removed before statistical tests can be applied for identifying genes that are expressed differentially. Background correction, log-ratio transformation, and normalization, referred as the log-ratio approach, have been widely used for this purpose. However, there are some problems associated with this procedure. In this study, we proposed an alternative approach that obviates the log-ratio transformation step and goes directly to normalization after background correction. The method can estimate the "noise" effect by utilizing the information more effectively. Simulation studies were carried out to compare the feasibility and efficiency of this approach for detecting the specifically and differentially expressed genes under various conditions with the log-ratio approach. The results showed that our approach worked well and was more robust and powerful than the log-ratio approach.
Zhang
Ji-Gang
JG
State Key Laboratory for Agrobiotechnology, Key Laboratory for Animal Genetics and breeding of the Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100094, China.
Yin
Zong-Jun
ZJ
Zhang
Qin
Q
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D020869:Gene Expression Profiling / Q000379:methods*; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*