Audic S, Claverie J M
Laboratory of Structural and Genetic Information, Centre National de la Recherche Scientifique-E.P.91, Marseille 13402, France.
Genome Res. 1997 Oct;7(10):986-95. doi: 10.1101/gr.7.10.986.
Genes differentially expressed in different tissues, during development, or during specific pathologies are of foremost interest to both basic and pharmaceutical research. "Transcript profiles" or "digital Northerns" are generated routinely by partially sequencing thousands of randomly selected clones from relevant cDNA libraries. Differentially expressed genes can then be detected from variations in the counts of their cognate sequence tags. Here we present the first systematic study on the influence of random fluctuations and sampling size on the reliability of this kind of data. We establish a rigorous significance test and demonstrate its use on publicly available transcript profiles. The theory links the threshold of selection of putatively regulated genes (e.g., the number of pharmaceutical leads) to the fraction of false positive clones one is willing to risk. Our results delineate more precisely and extend the limits within which digital Northern data can be used.
在不同组织、发育过程或特定病理状态下差异表达的基因，是基础研究和药物研究最为关注的对象。“转录本谱”或“数字Northern印迹”通常是通过对来自相关cDNA文库的数千个随机选择的克隆进行部分测序而生成的。然后可以从其同源序列标签计数的变化中检测出差异表达的基因。在此，我们首次对随机波动和样本量对这类数据可靠性的影响进行了系统研究。我们建立了一个严格的显著性检验，并展示了其在公开可用的转录本谱上的应用。该理论将推定受调控基因的选择阈值（例如药物先导物的数量）与愿意承担的假阳性克隆比例联系起来。我们的结果更精确地划定并扩展了数字Northern印迹数据可使用的范围。
