Methods of Analysis and Meta-Analysis for Identifying Differentially Expressed Genes.

Kontou P. I., Pavlopoulou A., Bagos P. G.

Methods in molecular biology (Clifton, N.J.), cilt.1793, ss.183-210, 2018 (Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 1793
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1007/978-1-4939-7868-7_12
  • Dergi Adı: Methods in molecular biology (Clifton, N.J.)
  • Derginin Tarandığı İndeksler: Scopus
  • Sayfa Sayıları: ss.183-210
  • Anahtar Kelimeler: Gene expression, Microarrays, Differentially expressed genes, Meta-analysis, Statistical tests, Multiple comparisons, FALSE DISCOVERY RATE, COMBINING PROBABILITY VALUES, MICROARRAY DATA-ANALYSIS, P-VALUES, FEATURE-SELECTION, CLASS PREDICTION, STATISTICAL INFERENCES, QUALITY-CONTROL, T-TEST, CLASSIFICATION
  • Dokuz Eylül Üniversitesi Adresli: Hayır

Özet

Microarray approaches are widely used high-throughput techniques to assess simultaneously the expression of thousands of genes under certain conditions and study the effects of certain treatments, diseases, and developmental stages. The traditional way to perform such experiments is to design oligonucleotide hybridization probes that correspond to specific genes and then measure the expression of the genes in order to determine which of them are up-or down-regulated compared to a condition that is used as a control. Hitherto, individual experiments cannot capture the bigger picture of how a biological system works and, therefore, data integration from multiple experimental studies and external data repositories is necessary to understand the function of genes and their expression patterns under certain conditions. Therefore, the development of methods for handling, integrating, comparing, interpreting and visualizing microarray data is necessary. The selection of an appropriate method for analysing microarray datasets is not an easy task. In this chapter, we provide an overview of the various methods developed for microarray data analysis, as well as suggestions for choosing the appropriate method for microarray meta-analysis.