A statistical framework for the design of microarray experiments and effective detection of differential gene expression


Autoria(s): Zhang, Shu-Dong; Gant, T.W.
Data(s)

01/11/2004

Resumo

Motivation: Microarray experiments generate a high data volume. However, often due to financial or experimental considerations, e.g. lack of sample, there is little or no replication of the experiments or hybridizations. These factors combined with the intrinsic variability associated with the measurement of gene expression can result in an unsatisfactory detection rate of differential gene expression (DGE). Our motivation was to provide an easy to use measure of the success rate of DGE detection that could find routine use in the design of microarray experiments or in post-experiment assessment.

Identificador

http://pure.qub.ac.uk/portal/en/publications/a-statistical-framework-for-the-design-of-microarray-experiments-and-effective-detection-of-differential-gene-expression(a7b39ef1-c3b3-4166-836a-d9b7f72d437b).html

http://dx.doi.org/10.1093/bioinformatics/bth336

http://www.scopus.com/inward/record.url?scp=8844224836&partnerID=8YFLogxK

Idioma(s)

eng

Direitos

info:eu-repo/semantics/restrictedAccess

Fonte

Zhang , S-D & Gant , T W 2004 , ' A statistical framework for the design of microarray experiments and effective detection of differential gene expression ' Bioinformatics , vol 20 , no. 16 , pp. 2821-2828 . DOI: 10.1093/bioinformatics/bth336

Palavras-Chave #/dk/atira/pure/subjectarea/asjc/1300/1308 #Clinical Biochemistry #/dk/atira/pure/subjectarea/asjc/1700/1703 #Computational Theory and Mathematics #/dk/atira/pure/subjectarea/asjc/1700/1706 #Computer Science Applications
Tipo

article