POWER_SAGE: comparing statistical tests for SAGE experiments | Zendy

Michael Man | Zendy; Xuning Wang | Zendy; Yixin Wang | Zendy

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POWER_SAGE: comparing statistical tests for SAGE experiments

Author(s) -

Michael Man,

Xuning Wang,

Yixin Wang

Publication year - 2000

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/16.11.953

Subject(s) - sage , statistical power , robustness (evolution) , computer science , statistical hypothesis testing , sample size determination , serial analysis of gene expression , monte carlo method , power (physics) , statistical analysis , statistics , expression (computer science) , data mining , gene expression , mathematics , gene , biology , gene expression profiling , genetics , physics , quantum mechanics , nuclear physics , programming language

The Serial Analysis of Gene Expression (SAGE) technology determines the expression level of a gene by measuring the frequency of a sequence tag derived from the corresponding mRNA transcript. Several statistical tests have been developed to detect significant differences in tag frequency between two samples. However, which one of these tests has the greatest power to detect real changes remains undetermined.

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