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Examples

Here, we present a second example for data analysis provided by the metaP server. In this example, we mainly focus on functionality that has not been described in Example 1 yet.

Example 2: Human, mouse, and bovine plasma samples measured using AbsoluteIDQ Kit

For this example, we used MS/MS metabolomics data produced by applying AbsoluteIDQ Kits technology from Biocrates. Here, bovine, human, mouse pool plasma, and (human) reference blood samples have been measured spread over three kits. Based on MS/MS spectra, Biocrates' MetIQ software (provided with the kits) calculates the concentrations of about 160 metabolites. The data export file (.csv) can be directly put into the metaP server for further analysis. Additionaly, we uploaded a phenotype file in character (here: semicolon) separated format (csv). In this file, the plasma type of each sample is described and the reference samples, which can be used for comparing the measurements on different kits, are specified in a column named 'REPLICATES'.

Results

  • Metabolites: As described in Example 1, the metabolites page gives an overview over all metabolites measured in the example study. In addition to the functionality shown in Example 1, the metaP server provides more detailed information (physical/chemical features and cross-links to KEGG, HMDB, LipidMaps, PubChem, and CAS numbers) on each metabolite page. (Click here for an example.)
  • Samples: As described in Example 1, the samples page ('Samples' link in grey menu bar) lists all samples with the corresponding phenotypic information. For AbsoluteIDQ kit data, the KEGG IDs provided by Biocrates are used to map the metabolites measured onto KEGG metabolic maps (see also Example 1). Thus, no KEGG IDs have to be uploaded with the data.
  • Quality Check: The quality check page gives an overview over the data uploaded and the results for several data quality checks. The quality check functionality is the same for AbsoluteIDQ data as for other metabolomics data. However, compared to Example 1, we describe further quality check functionality here since the study used in Example 1 did not comprise different batches and did not incorporate data on reference or replicate samples.
    • Reproducibility of measurements: For AbsoluteIDQ data, all samples with the same name in the 'Sample Identification' column are assumed to be replicates and their coefficient of variation is determined for each metabolite. The result is visualized in the cv plot. If other replicate/reference samples should be used instead or in case of metabolomics data in other data formats, you can specifiy the replicates by adding a column called "REPLICATES" to the phenotype data file before upload. If the option 'drop references' has been chosen (as done in this example), these samples are ignored for further data analysis. If the option 'drop analytes with cv>0.25' is chosen (as done in this example), the corresponding noisy metabolites are ignored for further data analysis. This metabolites are listed in cv above 0.25.
    • Batch effects: For AbsoluteIDQ data, the information whether different kits have been used for the study is used automatically as batch information (plate bar code). If other batch information should be used instead or in case of metabolomics data in other data formats, you can specifiy the batch information by adding a column called "BATCHES" to the phenotype data file before upload. The metaP server performs a hypothesis test for the association of metabolite concentrations and batches (see boxplots and list of p-values). If the data contains replicates, the metaP server additionally provides batch-wise boxplots (ref/batch boxplots) for the replicates and the remaining data.
  • Principal Component Analysis: As described in Example 1, the metaP server performs PCA analyses based on the complete sample data (normalized using mean and standard deviation).
  • Kendall correlation tests: As described in Example 1, the metaP server determines the Kendall correlation between each phenotype with numeric values and each metabolite as well as the significance of the correlation. However, in this example, no numeric phenotype has been provided.




KEGG Data is provided by the Kanehisa Laboratories for academic use. Any commercial use of KEGG data requires a license agreement from Pathway Solutions Inc.
The Helmholtz Zentrum München imprint applies.

This page is maintained by Gabi Kastenmüller and Werner Römisch-Margl.
Last modification: 28 December 2009

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