Understanding SAGE data.
Serial analysis of gene expression (SAGE) is a method for identifying and quantifying transcripts from eukaryotic genomes. Since its invention, SAGE has been widely applied to analyzing gene expression in many biological and medical studies. Vast amounts of SAGE data have been collected and more than a thousand SAGE-related studies have been published since the mid-1990s. The principle of SAGE has been developed to address specific issues such as determination of normal gene structure and identification of abnormal genome structural changes. This review focuses on the general features of SAGE data, including the specificity of SAGE tags with respect to their original transcripts, the quantitative nature of SAGE data for differentially expressed genes, the reproducibility, the comparability of SAGE with microarray and the future potential of SAGE. Understanding these basic features should aid the proper interpretation of SAGE data to address biological and medical questions.
Wang
San Ming
SM
Center for Functional Genomics, ENH Research Institute, Robert H. Lurie Comprehensive Cancer Center, Northwestern University, 1001 University Place, Evanston, IL 60201, USA. swang1@northwestern.edu
D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling / Q000379:methods*; D015723:Gene Library; D016678:Genome / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity