Format

Send to

Choose Destination
See comment in PubMed Commons below
PLoS One. 2012;7(12):e50938. doi: 10.1371/journal.pone.0050938. Epub 2012 Dec 7.

Analyzing illumina gene expression microarray data from different tissues: methodological aspects of data analysis in the metaxpress consortium.

Author information

1
Interfaculty Institute for Genetics and Functional Genomics, Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany.

Abstract

Microarray profiling of gene expression is widely applied in molecular biology and functional genomics. Experimental and technical variations make meta-analysis of different studies challenging. In a total of 3358 samples, all from German population-based cohorts, we investigated the effect of data preprocessing and the variability due to sample processing in whole blood cell and blood monocyte gene expression data, measured on the Illumina HumanHT-12 v3 BeadChip array.Gene expression signal intensities were similar after applying the log(2) or the variance-stabilizing transformation. In all cohorts, the first principal component (PC) explained more than 95% of the total variation. Technical factors substantially influenced signal intensity values, especially the Illumina chip assignment (33-48% of the variance), the RNA amplification batch (12-24%), the RNA isolation batch (16%), and the sample storage time, in particular the time between blood donation and RNA isolation for the whole blood cell samples (2-3%), and the time between RNA isolation and amplification for the monocyte samples (2%). White blood cell composition parameters were the strongest biological factors influencing the expression signal intensities in the whole blood cell samples (3%), followed by sex (1-2%) in both sample types. Known single nucleotide polymorphisms (SNPs) were located in 38% of the analyzed probe sequences and 4% of them included common SNPs (minor allele frequency >5%). Out of the tested SNPs, 1.4% significantly modified the probe-specific expression signals (Bonferroni corrected p-value<0.05), but in almost half of these events the signal intensities were even increased despite the occurrence of the mismatch. Thus, the vast majority of SNPs within probes had no significant effect on hybridization efficiency.In summary, adjustment for a few selected technical factors greatly improved reliability of gene expression analyses. Such adjustments are particularly required for meta-analyses.

PMID:
23236413
PMCID:
PMC3517598
DOI:
10.1371/journal.pone.0050938
[Indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Public Library of Science Icon for PubMed Central
    Loading ...
    Support Center