Similarities of ordered gene lists.
J Bioinform Comput Biol
; 4(3): 693-708, 2006 Jun.
Article
em En
| MEDLINE
| ID: mdl-16960970
ABSTRACT
MOTIVATION Many applications of microarray technology in clinical cancer studies aim at detecting molecular features for refined diagnosis. In this paper, we follow an opposite rationale we try to identify common molecular features shared by phenotypically distinct types of cancer using a meta-analysis of several microarray studies. We present a novel algorithm to uncover that two lists of differentially expressed genes are similar, even if these similarities are not apparent to the eye. The method is based on the ordering in the lists. RESULTS:
In a meta-analysis of five clinical microarray studies we were able to detect significant similarities in five of the ten possible comparisons of ordered gene lists. We included studies, where not a single gene can be significantly associated to outcome. The detection of significant similarities of gene lists from different microarray studies is a novel and promising approach. It has the potential to improve upon specialized cancer studies by exploring the power of several studies in one single analysis. Our method is complementary to previous methods in that it does not rely on strong effects of differential gene expression in a single study but on consistent ones across multiple studies.
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Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Regulação Neoplásica da Expressão Gênica
/
Análise de Sequência com Séries de Oligonucleotídeos
/
Perfilação da Expressão Gênica
/
Neoplasias
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
/
Systematic_reviews
Limite:
Humans
/
Male
Idioma:
En
Revista:
J Bioinform Comput Biol
Assunto da revista:
BIOLOGIA
/
INFORMATICA MEDICA
Ano de publicação:
2006
Tipo de documento:
Article
País de afiliação:
Alemanha