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Quant Biol. 2017 Dec;5(4):291-301. Epub 2017 Nov 12.

The Ontology of Biological and Clinical Statistics (OBCS)-based statistical method standardization and meta-analysis of host responses to yellow fever vaccines.

Zheng J1, Li H2, Liu Q3, He Y4,5,6,7.

Author information

1
Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA.
2
Health Science Center, Shenzhen University, Shenzhen 518000, China.
3
Department of Mathematics, University of Maryland, College Park, MD 20742, USA.
4
Unit for Laboratory Animal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
5
Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
6
Center for Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
7
Comprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, MI 48109, USA.

Abstract

Background:

The community-based Ontology of Biological and Clinical Statistics (OBCS) represents and standardizes biological and clinical data and statistical methods.

Methods:

Both OBCS and the Vaccine Ontology (VO) were used to ontologically model various components and relations in a typical host response to vaccination study. Such a model was then applied to represent and compare three microarray studies of host responses to the yellow fever vaccine YF-17D. A literature meta-analysis was then conducted to survey yellow fever vaccine response papers and summarize statistical methods, using OBCS.

Results:

A general ontological model was developed to identify major components in a typical host response to vaccination. Our ontology modeling of three similar studies identified common and different components which may contribute to varying conclusions. Although these three studies all used the same vaccine, human blood samples, similar sample collection time post vaccination, and microarray assays, statistically differentially expressed genes and associated gene functions differed, likely due to the differences in specific variables (e.g., microarray type and human variations). Our manual annotation of 95 papers in human responses to yellow fever vaccines identified 38 data analysis methods. These statistical methods were consistently represented and classified with OBCS. Eight statistical methods not available in existing ontologies were added to OBCS.

Conclusions:

The study represents the first single use case of applying OBCS ontology to standardize, integrate, and use biomedical data and statistical methods. Our ontology-based meta-analysis showed that different experimental results might be due to different experimental assays and conditions, sample variations, and data analysis methods.

KEYWORDS:

OBCS; host response to vaccination; ontology; statistical data analysis; vaccine

PMID:
30034908
PMCID:
PMC6054478

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