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Exploring Metabolomic data with recursive partitioning

Exploring Metabolomic data with recursive partitioning. Metabolomic Workshop NISS July 14-15, 2005. Why study metabolites?. Metabolomics – the global study of all small molecules produced in the human body

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Exploring Metabolomic data with recursive partitioning

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  1. Exploring Metabolomic data with recursive partitioning Metabolomic Workshop NISS July 14-15, 2005

  2. Why study metabolites? • Metabolomics – the global study of all small molecules produced in the human body • Biochemical consequences of environment, drugs, and mutations can be observed directly through metabolites • Understand how drugs work, interactions and possible side effects • ~2500 metabolites

  3. Challenges of metabolomic data • Nonnormal distributions • Outliers • Informative missing values • High correlation among metabolites • n < p problem (n - number of biological samples and p - number of metabolites)

  4. Why recursive partitioning? • Is fairly robust to non-normal data • Missing values is not an issue • Correlation among variables is not an issue • Useful for discovering outliers • Is efficient at handling large p, small n data sets

  5. How recursive partitioning works • Recursive partitioning efficiently searches through all of the variables and finds the one with the best split (most significant) • Once data is split or “partitioned” on this variable, the resulting daughter nodes are more homogeneous • Now each daughter node is explored to find the best split • This process is continued until no significant split remains

  6. Example

  7. Multiple Trees • All effects are not necessarily found in a single tree • In any node, there may be more than one significant variable • Creating multiple trees may reveal a number of possible effects • Gain an understanding of interactions/correlations among metabolites

  8. Software • Helix Tree (Partitionator) • www.goldenhelix.com • Uses Formal Inference-based Recursive Modeling (FIRM) developed by Douglas Hawkins • Anyone can download free 7 day trial (webinars to assist in using the software)

  9. Illustration of Software • Data • 317 metabolites • LC/MS and GC/MS • 63 biological samples • Want to discover which metabolites differentiate between the diseased group and the “healthy” individuals (within the diseased group there is a subset of individuals currently taking drugs)

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