Dr. Su's Statistics, Department of Human Nutrition, Food, and Animal Sciences, University of Hawaii at Manoa, Honolulu, HI 96822, USA.
Hum Genomics. 2013 Jan 5;7(1):2. doi: 10.1186/1479-7364-7-2.
: A bivariate mixture model utilizing information across two species was proposed to solve the fundamental problem of identifying differentially expressed genes in microarray experiments. The model utility was illustrated using a dog and human lymphoma data set prepared by a group of scientists in the College of Veterinary Medicine at North Carolina State University. A small number of genes were identified as being differentially expressed in both species and the human genes in this cluster serve as a good predictor for classifying diffuse large-B-cell lymphoma (DLBCL) patients into two subgroups, the germinal center B-cell-like diffuse large B-cell lymphoma and the activated B-cell-like diffuse large B-cell lymphoma. The number of human genes that were observed to be significantly differentially expressed (21) from the two-species analysis was very small compared to the number of human genes (190) identified with only one-species analysis (human data). The genes may be clinically relevant/important, as this small set achieved low misclassification rates of DLBCL subtypes. Additionally, the two subgroups defined by this cluster of human genes had significantly different survival functions, indicating that the stratification based on gene-expression profiling using the proposed mixture model provided improved insight into the clinical differences between the two cancer subtypes.
提出了一种利用两种物种信息的双变量混合模型，以解决微阵列实验中鉴定差异表达基因的基本问题。该模型的实用性通过北卡罗来纳州立大学兽医学院的一组科学家准备的狗和人类淋巴瘤数据集进行了说明。确定了一小部分在两个物种中均差异表达的基因，并且该聚类中的人类基因可作为将弥漫性大 B 细胞淋巴瘤 (DLBCL) 患者分为两个亚组的良好预测因子，即生发中心 B 细胞样弥漫性大 B 细胞淋巴瘤和激活 B 细胞样弥漫性大 B 细胞淋巴瘤。与仅进行单物种分析（人类数据）所鉴定的人类基因数量（190）相比，从双物种分析中观察到的人类基因中显著差异表达的数量（21）非常少。这些基因可能具有临床相关性/重要性，因为这个小基因集实现了低的 DLBCL 亚型误分类率。此外，由该簇人类基因定义的两个亚组具有显著不同的生存功能，表明使用提出的混合模型基于基因表达谱进行分层提供了对两种癌症亚型之间临床差异的深入了解。
