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Abstract Details

Activity Number: 253
Type: Contributed
Date/Time: Monday, July 30, 2012 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #305926
Title: Accounting for Below Detection Limit Values in the Analysis of Metabolomic Data
Author(s): Philip Dixon*+
Companies: Iowa State University
Address: , Ames, IA, ,
Keywords: metabolomics ; detection limit ; distance measures

Metabolomics describes the types and concentrations of small molecular weight compounds in a sample. Measurements are usually made using some form of chromatography, e.g. HPLC or GC/MS. Considerable signal processing is required to identify a peak and measure its area, which is proportional to concentration. Hence, it is impossible to distinguish absence of a compound (a true 0) and presence at a concentration below some detection limit. Below detection limit values are usually treated abitrarily, and different arbitrary choices can have a substantial impact on results. I propose a method for down-weighting the contribution of below-detection limit values that reduces the impact of arbitrary choices. The key is using a variance-weighted distance to calculate the dissimilarity between pairs of samples. The resulting dissimilarity matrix can be used for clustering, hypothesis testing, and visualizing variation among the samples.

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