最近看到一个韩国人的TCGA数据挖掘文章，标题是：《Classification of Genes Based on Age-Related Differential Expression in Breast Cancer》，发表于2017年，研究者根据年龄对病人进行分组，使用TCGA数据库里面的乳腺癌患者数据，病人分成 3 组：

• Young patients were defined as ≤45 years of age
• elderly patients were defined as those ≥60 years of age
• The rest of the patients were defined as “intermediate.”

全部的分析流程如下所示：

• A total of 5,962 genes in class A were defined as significant DEGs in breast cancer, and 13,684 in class B were nonsignificant.
• Ones who want to find biomarkers or driver genes are likely to investigate only genes in class A.
• However, we classified the genes of each class once again into eight groups, based on the pattern of p-values, which were calculated separately for every age group (secondary classification in Fig. 2).
• After a second round of classification, the genes were eventually divided into 16 classes (A1–B8) (Supplementary Table 1).

差异分析把基因分成了两类，差异分析相信大家都不陌生了，基本上看我六年前的表达芯片的公共数据库挖掘系列推文即可；

• 解读GEO数据存放规律及下载，一文就够
• 解读SRA数据库规律一文就够
• 从GEO数据库下载得到表达矩阵 一文就够
• GSEA分析一文就够（单机版+R语言版）
• 根据分组信息做差异分析- 这个一文不够的
• 差异分析得到的结果注释一文就够

然后居然对基因的p值进行趋势分类，我勒个去，让人尴尬的脑阔疼！

作者的研究结果居然是把基因分成了16组，然后每个组有自己的生物学功能数据库注释结果，其中几个组可以把癌症样品和正常对照区分开来！

说他是灌水，都是侮辱了灌水这两个字！