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DNA Research 2005 12(3):211-214; doi:10.1093/dnares/dsi007
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© The Author 2005. Kazusa DNA Research Institute

Short Communications

HTself: Self–Self Based Statistical Test for Low Replication Microarray Studies

Ricardo Z. N. Vêncio1,* and Tie Koide2

1BIOINFO-USP—Núcleo de Pesquisas em Bioinformática, Universidade de São Paulo Rua do Matão 1010, 05508-090 São Paulo, Brazil
2Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo Av. Prof. Lineu Prestes 748, 05508-090 São Paulo, Brazil

Different statistical methods have been used to classify a gene as differentially expressed in microarray experiments. They usually require a number of experimental observations to be adequately applied. However, many microarray experiments are constrained to low replication designs for different reasons, from financial restrictions to scarcely available RNA samples. Although performed in a high-throughput framework, there are few experimental replicas for each gene to allow the use of traditional or state-of-art statistical methods. In this work, we present a web-based bioinformatics tool that deals with real-life problems concerning low replication experiments. It uses an empirically derived criterion to classify a gene as differentially expressed by combining two widely accepted ideas in microarray analysis: self–self experiments to derive intensity-dependent cutoffs and non-parametric estimation techniques. To help laboratories without a bioinformatics infrastructure, we implemented the tool in a user-friendly website (http://blasto.iq.usp.br/~rvencio/HTself).

Key words: microarray; self–self; homotypical; web server; statistical test; low cost; differential gene expression

*To whom correspondence should be addressed. Tel. +55-11-3091-6210, Fax. +55-11-3814-4135, Email: rvencio{at}vision.ime.usp.br

Both these authors contributed equally to this work

Communicated by Michio Oishi


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