Cross-platform comparability of microarray technology: intra-platform consistency and appropriate data analysis procedures are essential.
BACKGROUND
The acceptance of microarray technology in regulatory decision-making is being challenged by the existence of various platforms and data analysis methods. A recent report (E. Marshall, Science, 306, 630-631, 2004), by extensively citing the study of Tan et al. (Nucleic Acids Res., 31, 5676-5684, 2003), portrays a disturbingly negative picture of the cross-platform comparability, and, hence, the reliability of microarray technology.


RESULTS
We reanalyzed Tan's dataset and found that the intra-platform consistency was low, indicating a problem in experimental procedures from which the dataset was generated. Furthermore, by using three gene selection methods (i.e., p-value ranking, fold-change ranking, and Significance Analysis of Microarrays (SAM)) on the same dataset we found that p-value ranking (the method emphasized by Tan et al.) results in much lower cross-platform concordance compared to fold-change ranking or SAM. Therefore, the low cross-platform concordance reported in Tan's study appears to be mainly due to a combination of low intra-platform consistency and a poor choice of data analysis procedures, instead of inherent technical differences among different platforms, as suggested by Tan et al. and Marshall.


CONCLUSIONS
Our results illustrate the importance of establishing calibrated RNA samples and reference datasets to objectively assess the performance of different microarray platforms and the proficiency of individual laboratories as well as the merits of various data analysis procedures. Thus, we are progressively coordinating the MAQC project, a community-wide effort for microarray quality control.
Shi
Leming
L
National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR Road, Jefferson, Arkansas 72079, USA. leming.shi@fda.hhs.gov
Tong
Weida
W
Fang
Hong
H
Scherf
Uwe
U
Han
Jing
J
Puri
Raj K
RK
Frueh
Felix W
FW
Goodsaid
Federico M
FM
Guo
Lei
L
Su
Zhenqiang
Z
Han
Tao
T
Fuscoe
James C
JC
Xu
Z Alex
ZA
Patterson
Tucker A
TA
Hong
Huixiao
H
Xie
Qian
Q
Perkins
Roger G
RG
Chen
James J
JJ
Casciano
Daniel A
DA
D030541:Databases, Genetic / Q000592:standards*; D040081:Protein Array Analysis / Q000592:standards*