34: Recovering Missing Correlations in Multi-Site Metabolomic Studies

Thomas M. Menino Convention & Exhibition Center 

Many NIH-sponsored laboratories carry out nontargeted metabolite studies, focusing only on a subset of the entire human metabolome and reporting summary data for the subset of metabolites. To form a complete picture of the entire metabolome or a substantial part of it, one must put the summary analysis on different subsets, obtained from the different laboratories, together in a consistent and efficient manner. We propose a methodology for integrating findings at various laboratories in a cooperative research partnership, in a scenario where only estimated Spearman rank correlation matrices, not raw data, can be shared between partner organizations. We assume the laboratories will study different, but intersecting sets of metabolites and consider how to impute missing values for the metabolite data not collected at a given lab.

meta-analysis

metabolomics

distributed research

correlation matrix 

ENAR