Effects of threshold choice on biological conclusions reached during analysis of gene expression by DNA microarrays.
Global analysis of gene expression by using DNA microarrays is employed increasingly to search for differences in biological properties between normal and diseased tissue. In such studies, expression that deviates from defined thresholds commonly is used for creating genetic signatures that characterize disease vs. normality. Although it is axiomatic that the threshold parameters applied to microarray analysis will alter the contents of such genetic signatures, the extent to which threshold choice can affect the fundamental conclusions made from microarray-based studies has not been elucidated. We used GABRIEL (Genetic Analysis By Rules Incorporating Expert Logic), a platform of knowledge-based algorithms for the global analysis of gene expression, together with conventional statistical approaches, to examine the sensitivity of conclusions to threshold choice in recently published microarray-based studies. An analysis of the effects of threshold decisions in one of these studies [Ramaswamy, S., Ross, K. N., Lander, E. S. & Golub, T. R. (2003) Nat. Genet. 33, 49-54], which arrived at the important conclusion that the metastatic potential of primary tumors is encoded by the bulk of cells in the tumor, is the focus of this article. We discovered that support for this conclusion highly depends on the threshold used to create gene expression signatures. We also found that threshold choice dramatically affected the gene function categories represented nonrandomly in signatures. Our results suggest that the robustness of biological conclusions made by using microarray analysis should be routinely assessed by examining the validity of the conclusions by using a range of threshold parameters.
Pan
Kuang-Hung
KH
Department of Genetics and Program in Biomedical Informatics, Stanford University School of Medicine, Stanford University, Stanford, CA 94305-5120, USA.
Lih
Chih-Jian
CJ
Cohen
Stanley N
SN
D000230:Adenocarcinoma / Q000235:genetics / Q000401:mortality; D000465:Algorithms; D002528:Cerebellar Neoplasms / Q000235:genetics; D015870:Gene Expression; D006801:Humans; D008175:Lung Neoplasms / Q000235:genetics / Q000401:mortality; D016393:Lymphoma, B-Cell / Q000235:genetics; D008297:Male; D008527:Medulloblastoma / Q000235:genetics; D009362:Neoplasm Metastasis / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011471:Prostatic Neoplasms / Q000235:genetics; D016019:Survival Analysis