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Bioinformatics. 2014 Oct;30(19):2802-7. doi: 10.1093/bioinformatics/btu396. Epub 2014 Jun 19.

PGS: a tool for association study of high-dimensional microRNA expression data with repeated measures.

Author information

1
Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, Institute of Human Genetics, University of Illinois at Chicago, Chicago, IL 60612, Division of Health and Biomedical Informatics, Departments of Preventive Medicine and Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, Department of Environmental Health, Harvard School of Public Health, Boston, MA 02115 and The Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
2
Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, Institute of Human Genetics, University of Illinois at Chicago, Chicago, IL 60612, Division of Health and Biomedical Informatics, Departments of Preventive Medicine and Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, Department of Environmental Health, Harvard School of Public Health, Boston, MA 02115 and The Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, Institute of Human Genetics, University of Illinois at Chicago, Chicago, IL 60612, Division of Health and Biomedical Informatics, Departments of Preventive Medicine and Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, Department of Environmental Health, Harvard School of Public Health, Boston, MA 02115 and The Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.

Abstract

MOTIVATION:

MicroRNAs (miRNAs) are short single-stranded non-coding molecules that usually function as negative regulators to silence or suppress gene expression. Owning to the dynamic nature of miRNA and reduced microarray and sequencing costs, a growing number of researchers are now measuring high-dimensional miRNA expression data using repeated or multiple measures in which each individual has more than one sample collected and measured over time. However, the commonly used univariate association testing or the site-by-site (SBS) testing may underutilize the longitudinal feature of the data, leading to underpowered results and less biologically meaningful results.

RESULTS:

We propose a penalized regression model incorporating grid search method (PGS), for analyzing associations of high-dimensional miRNA expression data with repeated measures. The development of this analytical framework was motivated by a real-world miRNA dataset. Comparisons between PGS and the SBS testing revealed that PGS provided smaller phenotype prediction errors and higher enrichment of phenotype-related biological pathways than the SBS testing. Our extensive simulations showed that PGS provided more accurate estimates and higher sensitivity than the SBS testing with comparable specificities.

AVAILABILITY AND IMPLEMENTATION:

R source code for PGS algorithm, implementation example and simulation study are available for download at https://github.com/feizhe/PGS.

PMID:
24947752
PMCID:
PMC4173025
DOI:
10.1093/bioinformatics/btu396
[Indexed for MEDLINE]
Free PMC Article

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