Potentialities of multivariate approaches in genome-based cancer research:: identification of candidate genes for new diagnostics by PLS discriminant analysis
Potentialities of multivariate approaches in genome-based cancer research:: identification of candidate genes for new diagnostics by PLS discriminant analysis
复制标题
DOI：
10.1002/cem.846
复制
发表时间：
2004-03-01
影响因子：
2.4
通讯作者：
Scirè, S
中科院分区：
文献类型：
--
作者：
Musumarra, G;Barresi, V;Scirè, S
偏最小二乘判别分析（PLS-DA）提供了一个良好的统计基础的选择，从原来的9605-数据集，有限数量的基因转录最有效地区分不同的肿瘤组织型。PLS-DA方法的潜力指出，它能够识别基因，根据目前的知识，与癌症的发展。此外，PLS-DA能够鉴定MUC 13和S100 P蛋白作为开发新的结肠癌诊断的候选物。各种功能未知的基因和EST（表达序列标签），发现是重要的结肠癌，白血病，肾和中枢神经系统肿瘤细胞的基因的区别，值得在未来的分子研究的高度优先。版权所有（C）2004约翰威利父子有限公司。
Partial least squares discriminant analysis (PLS-DA) provides a sound statistical basis for the selection, from an original 9605-data set, of a limited number of gene transcripts most effective in discriminating different tumour histotypes. The potentialities of the PLS-DA approach are pointed out by its ability to identify genes which, according to current knowledge, are associated with cancer development. Moreover, PLS-DA was able to identify MUC 13 and S100P proteins as candidates for the development of new colon cancer diagnostics. Various genes with unknown function and ESTs (expressed sequence tags), found to be important in discriminating genes for colon, leukaemia, renal and central nervous system tumour cells, are indicated as deserving high priority in future molecular studies. Copyright (C) 2004 John Wiley Sons, Ltd.