Link test - A statistical method for finding prostate cancer biomarkers

被引：22

作者：

Deng, Xutao ^{[1
]}

Geng, Huimin

Bastola, Dhundy R.

Ali, Hesham H.

机构：

[1] Univ Nebraska, Coll Informat Sci & Technol, Omaha, NE 68182 USA

[2] Univ Nebraska, Med Ctr, Dept Pathol & Microbiol, Omaha, NE 68198 USA

[3] Univ Nebraska, Med Ctr, Dept Pediat, Omaha, NE 68198 USA

来源：

COMPUTATIONAL BIOLOGY AND CHEMISTRY | 2006年 / 30卷 / 06期

基金：

美国国家卫生研究院;

关键词：

microarray; mass spectrometry; biomarker; prostate cancer; text mining;

D O I：

10.1016/j.compbiolchem.2006.09.002

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

We present a new method, link-test, to select prostate cancer biomarkers from SELDI mass spectrometry and microarray data sets. Biomarkers selected by link-test are supported by data sets from both mRNA and protein levels, and therefore results in improved robustness. Link-test determines the level of significance of the association between a microarray marker and a specific mass spectrum marker by constructing background mass spectra distributions estimated by all human protein sequences in the SWISS-PROT database. The data set consist of both microarray and mass spectrometry data from prostate cancer patients and healthy controls. A list of statistically justified prostate cancer biomarkers is reported by link-test. Cross-validation results show high prediction accuracy using the identified biomarker panel. We also employ a text-mining approach with OMIM database to validate the cancer biomarkers. The study with link-test represents one of the first cross-platform studies of cancer biomarkers. (c) 2006 Elsevier Ltd. All rights reserved.

引用

页码：425 / 433

页数：9

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