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