【佳学基因检测】肿瘤纯度采用新型配对特征选择方法改善差异基因表达分析基因检测

病原微生物基因检测多少钱要点

体会癌的基因检测基因解码如何创新治疗认识到《Math Biosci》在 2019 May;311:39-48发表了一篇题目为《肿瘤纯度采用新型配对特征选择方法改善差异基因表达分析基因检测》肿瘤靶向药物治疗基因检测临床研究文章。该研究由Sen Liang, Sen Yang, Dayang Liang, Jiechao Ma, Yuan Tian, Jing Zhao, Xu Zhang, Ying Xu, Yan Wang 等完成。促进了肿瘤的正确治疗与个性化用药的发展，进一步强调了基因信息检测与分析的重要性。

肿瘤靶向药物及正确治疗临床研究内容关键词：

特征选择,基因表达分析,匹配病例,对照设计,检验统计,肿瘤纯度

肿瘤靶向治疗基因检测临床应用结果

基于组织的基因表达数据分析虽然贼强大，但是与基于细胞的基因表达数据分析相比，它代表了一个更具挑战性的问题，即使对于贼简单的差异基因表达分析也是如此。确定基因在肿瘤与非肿瘤对照组织中是否差异表达的结果不仅取决于两个表达值，还取决于组织细胞为肿瘤细胞的百分比，即肿瘤纯度。我们开发了一种新的匹配对特征选择方法，该方法在确定基因是否在肿瘤与对照实验中差异表达时充分考虑了肿瘤纯度，该方法简单、有效且正确。为了评估该方法的有效性和性能，我们将其与使用模拟数据集和实际癌症组织数据集的四种已发表方法进行了比较，发现我们的方法比其他方法具有更高的灵敏度和特异性，具有更好的性能。我们的方法是匹配病例对照设计下基因表达分析的配对特征选择方法，该方法考虑了肿瘤纯度信息，可为进一步发展其他基因表达分析需求奠定基础。

肿瘤发生与反复转移国际数据库描述：

Tissue-based gene expression data analyses, while most powerful, represent a significantly more challenging problem compared to cell-based gene expression data analyses, even for the simplest differential gene expression analyses. The result in determining if a gene is differentially expressed in tumor vs. non-tumorous control tissues does not only depend on the two expression values but also on the percentage of the tissue cells being tumor cells, i.e., the tumor purity. We developed a novel matched-pairs feature selection method, which takes into full consideration of the tumor purity when deciding if a gene is differentially expressed in tumor vs. control experiments, which is simple, effective, and accurate. To evaluate the validity and performance of the method, we have compared it with four published methods using both simulated datasets and actual cancer tissue datasets and found that our method achieved better performance with higher sensitivity and specificity than the other methods. Our method was the a matched-pairs feature selection method on gene expression analysis under matched case-control design which takes into consideration the tumor purity information, which can set a foundation for further development of other gene expression analysis needs.