ProbeSelect: selecting differentially expressed probes in transcriptional profile data.
Bioinformatics
; 30(4): 574-5, 2014 Feb 15.
Article
em En
| MEDLINE
| ID: mdl-24336808
ABSTRACT
SUMMARY:
Transcriptional profiling still remains one of the most popular techniques for identifying relevant biomarkers in patient samples. However, heterogeneity in the population leads to poor statistical evidence for selection of most relevant biomarkers to pursue. In particular, human transcriptional differences can be subtle, making it difficult to tease out real differentially expressed biomarkers from the variability inherent in the population. To address this issue, we propose a simple statistical technique that identifies differentially expressed probes in heterogeneous populations as compared with controls. AVAILABILITY AND IMPLEMENTATION The algorithm has been implemented in Java and available at www.sourceforge.net/projects/probeselect.
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Software
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Análise de Sequência com Séries de Oligonucleotídeos
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Esclerose Múltipla Crônica Progressiva
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Perfilação da Expressão Gênica
Idioma:
En
Ano de publicação:
2014
Tipo de documento:
Article