Analyzing Illumina Gene Expression Microarray Data Obtained From Human Whole Blood Cell and Blood Monocyte Samples

• Published in: Methods in molecular biology (Clifton, N.J.) Vol. 1368; p. 85
• Main Authors: Teumer, Alexander, Schurmann, Claudia, Schillert, Arne, Schramm, Katharina, Ziegler, Andreas, Prokisch, Holger
• Format: Journal Article
• Language: English
• Published: United States 01.01.2016
• Subjects: Analysis of Variance; Female; Gene Expression Profiling - methods; Humans; Male; Monocytes - metabolism; Nucleic Acid Amplification Techniques; Nucleic Acid Hybridization; Oligonucleotide Array Sequence Analysis - methods; Phenotype; Quality Control; RNA, Messenger - genetics; RNA, Messenger - isolation & purification; Staining and Labeling; ILLUMINA HumanHT-12; Gene expression analysis; Human whole blood cells; Transcriptomics; BeadChip; Microarray; Human monocytes
• ISSN: 1940-6029
• DOI: 10.1007/978-1-4939-3136-1_7

Microarray profiling of gene expression is widely applied to studies in molecular biology and functional genomics. Experimental and technical variations make not only the statistical analysis of single studies but also meta-analyses of different studies very challenging. Here, we describe the analytical steps required to substantially reduce the variations of gene expression data without affecting true effect sizes. A software pipeline has been established using gene expression data from a total of 3358 whole blood cell and blood monocyte samples, all from three German population-based cohorts, measured on the Illumina HumanHT-12 v3 BeadChip array. In summary, adjustment for a few selected technical factors greatly improved reliability of gene expression analyses. Such adjustments are particularly required for meta-analyses of different studies.