Detecting and profiling tissue-selective genes
Detecting and profiling tissue-selective genes
复制标题
DOI：
10.1152/physiolgenomics.00313.2005
复制
发表时间：
2006-07-12
影响因子：
4.6
通讯作者：
Liu, Wei
中科院分区：
文献类型：
--
作者：
Liang, Shuang;Li, Yizheng;Liu, Wei
DNA微阵列技术的广泛使用已经从各种组织和/或细胞类型产生了大量数据。这些数据为全面回答人类转录组的组织特异性问题奠定了基础。我们的重点是通过识别在少数组织类型中优先表达的基因来揭示组织-基因关系。组织选择性将揭示这些基因的潜在生理功能，并提供了一个不可或缺的参考，以比较疾病的病理生理学，并确定或验证组织特异性药物靶点。在这里，我们描述了一个系统的计算和统计方法来分析基因表达数据，以确定组织选择性基因与使用更广泛的数据集和一个完善的多重比较程序与错误率控制。分析了97种正常人类组织类型中35，152个探针组的表达数据，并鉴定了3，919个基因对一种或几种组织类型具有选择性。我们介绍了这些组织选择性基因的结果，并将其与其他研究确定的结果进行了比较。
The widespread use of DNA microarray technologies has generated large amounts of data from various tissue and/or cell types. These data set the stage to answer the question of tissue specificity of human transcriptome in a comprehensive manner. Our focus is to uncover the tissue-gene relationship by identifying genes that are preferentially expressed in a small number of tissue types. The tissue selectivity would shed light on the potential physiological functions of these genes and provides an indispensable reference to compare against disease pathophysiology and to identify or validate tissue-specific drug targets. Here we describe a systematic computational and statistical approach to profile gene expression data to identify tissue-selective genes with the use of a more extensive data set and a well-established multiple-comparison procedure with error rate control. Expression data of 35,152 probe sets in 97 normal human tissue types were analyzed, and 3,919 genes were identified to be selective to one or a few tissue types. We presented results of these tissue-selective genes and compared them to those identified by other studies.