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Microarray-Based MicroRNA Expression Data Analysis with Bioconductor.
Mastriani, Emilio; Zhai, Rihong; Zhu, Songling.
Afiliação
  • Mastriani E; Systemomics Center, College of Pharmacy, Harbin Medical University, Harbin, China.
  • Zhai R; Genomics Research Center (State-Province Key Laboratories of Biomedicine-Pharmaceutics of China), Harbin Medical University, Harbin, China.
  • Zhu S; School of Public Health, Shenzhen University Health Science Center, Shenzhen, China.
Methods Mol Biol ; 1751: 127-138, 2018.
Article em En | MEDLINE | ID: mdl-29508294
ABSTRACT
MicroRNAs (miRNAs) are small, noncoding RNAs that are able to regulate the expression of targeted mRNAs. Thousands of miRNAs have been identified; however, only a few of them have been functionally annotated. Microarray-based expression analysis represents a cost-effective way to identify candidate miRNAs that correlate with specific biological pathways, and to detect disease-associated molecular signatures. Generally, microarray-based miRNA data analysis contains four major

steps:

(1) quality control and normalization, (2) differential expression analysis, (3) target gene prediction, and (4) functional annotation. For each step, a large couple of software tools or packages have been developed. In this chapter, we present a standard analysis pipeline for miRNA microarray data, assembled by packages mainly developed with R and hosted in Bioconductor project.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: RNA Mensageiro / Análise de Sequência de RNA / Perfilação da Expressão Gênica / MicroRNAs / Sequenciamento de Nucleotídeos em Larga Escala Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: RNA Mensageiro / Análise de Sequência de RNA / Perfilação da Expressão Gênica / MicroRNAs / Sequenciamento de Nucleotídeos em Larga Escala Idioma: En Ano de publicação: 2018 Tipo de documento: Article