Statistical inference methods for gene expression arrays

被引：10

作者：

Nadon, R ^{[1
]}

Shi, PD ^{[1
]}

Skandalis, A ^{[1
]}

Woody, E ^{[1
]}

Hubschle, H ^{[1
]}

Susko, E ^{[1
]}

Rghei, N ^{[1
]}

机构：

[1] Imaging Res Inc, St Catharines, ON, Canada

来源：

MICROARRAYS: OPTICAL TECHNOLOGIES AND INFORMATICS | 2001年 / 4266卷

关键词：

cDNA microarray; cDNA macroarray; random error; statistical test; differential expression;

D O I：

10.1117/12.427999

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Gene expression arrays present unique challenges for statistical inference. The typically small number of replicated expression values in array studies make the use of standard parametric statistical tests problematic. Such tests have low sensitivity and return potentially inaccurate probability values. This paper describes novel alternative statistical modeling procedures which circumvent these difficulties by pooling random error estimates obtained from replicate expression values. The procedures, which can be used with both micro- and macro-arrays, include outlier detection, confidence intervals, statistical tests of differences between conditions, and statistical power analysis for determining, number of replicates needed to detect between-condition differences of specified magnitude. The methods are illustrated with experimental data.

引用

页码：46 / 55

页数：10

共 10 条

[1]

Barnett V., 1998, WILEY SERIES PROBABI

[2] Gene expression informatics - it's all in your mine [J].