Network-Based Meta-Analyses of Associations of Multiple Gene Expression Profiles with Bone Mineral Density Variations in Women

PloS One
Hao HeHong-Wen Deng

Abstract

Existing microarray studies of bone mineral density (BMD) have been critical for understanding the pathophysiology of osteoporosis, and have identified a number of candidate genes. However, these studies were limited by their relatively small sample sizes and were usually analyzed individually. Here, we propose a novel network-based meta-analysis approach that combines data across six microarray studies to identify functional modules from human protein-protein interaction (PPI) data, and highlight several differentially expressed genes (DEGs) and a functional module that may play an important role in BMD regulation in women. Expression profiling studies were identified by searching PubMed, Gene Expression Omnibus (GEO) and ArrayExpress. Two meta-analysis methods were applied across different gene expression profiling studies. The first, a nonparametric Fisher's method, combined p-values from individual experiments to identify genes with large effect sizes. The second method combined effect sizes from individual datasets into a meta-effect size to gain a higher precision of effect size estimation across all datasets. Genes with Q test's p-values < 0.05 or I(2) values > 50% were assessed by a random effects model and the remainde...Continue Reading

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Nov 23, 2016·Wiener klinische Wochenschrift·Klemen KodričJanja Marc
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Datasets Mentioned

BETA
GSE2208

Methods Mentioned

BETA
biopsies
two-hybrid
Chips
chip

Software Mentioned

Bioconductor BioNet package
hclust
ArrayExpress
R samr package
R Bioconductor affy package
Bioconductor
Affymetrix
WebGestalt
BioNet
SAM

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