title: Cross-platform comparability of microarray technology: intra-platform consistency and appropriate data analysis procedures are essential.
abstract: 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.
authors: National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR Road, Jefferson, Arkansas 72079, USA. leming.shi@fda.hhs.gov
authors: Leming
authors: L
authors: Shi
authors: Weida
authors: W
authors: Tong
authors: Hong
authors: H
authors: Fang
authors: Uwe
authors: U
authors: Scherf
authors: Jing
authors: J
authors: Han
authors: Raj K
authors: RK
authors: Puri
authors: Felix W
authors: FW
authors: Frueh
authors: Federico M
authors: FM
authors: Goodsaid
authors: Lei
authors: L
authors: Guo
authors: Zhenqiang
authors: Z
authors: Su
authors: Tao
authors: T
authors: Han
authors: James C
authors: JC
authors: Fuscoe
authors: Z Alex
authors: ZA
authors: Xu
authors: Tucker A
authors: TA
authors: Patterson
authors: Huixiao
authors: H
authors: Hong
authors: Qian
authors: Q
authors: Xie
authors: Roger G
authors: RG
authors: Perkins
authors: James J
authors: JJ
authors: Chen
authors: Daniel A
authors: DA
authors: Casciano
mesh_terms: D030541:Databases, Genetic / Q000592:standards*; D040081:Protein Array Analysis / Q000592:standards*