Electronically subtracting expression patterns from a mixed cell population.
Bioinformatics
; 23(24): 3328-34, 2007 Dec 15.
Article
em En
| MEDLINE
| ID: mdl-17956877
ABSTRACT
MOTIVATION Biological samples frequently contain multiple cell-types that each can play a crucial role in the development and/or regulation of adjacent cells or tissues. The search for biomarkers, or expression patterns of, one cell-type in those samples can be a complex and time-consuming process. Ordinarily, extensive laboratory bench work must be performed to separate the mixed cell population into its subcomponents, such that each can be accurately characterized. RESULTS:
We have developed a methodology to electronically subtract gene expression in one or more components of a mixed cell population from a mixture, to reveal the expression patterns of other minor or difficult to isolate components. Examination of simulated data indicates that this procedure can reliably determine the expression patterns in cell-types that contribute as little as 5% of the total expression in a mixed cell population. We re-analyzed microarray expression data from the viral infection of macrophages and from the T-cells of wild type and Foxp3 deletion mice. Using our subtraction methodology, we were able to substantially improve the identification of genes involved in processes of subcomponent portions of these samples.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Reconhecimento Automatizado de Padrão
/
Inteligência Artificial
/
Fenômenos Fisiológicos Celulares
/
Técnicas de Cocultura
/
Análise de Sequência com Séries de Oligonucleotídeos
/
Proteoma
/
Perfilação da Expressão Gênica
Limite:
Animals
Idioma:
En
Ano de publicação:
2007
Tipo de documento:
Article