Introduction to omu

Omu is an R package that enables rapid analysis of Metabolomics data sets, and the creation of intuitive graphs. Omu can assign metabolite classes (Carbohydrates, Lipids, etc) as meta data, perform t tests, anovas and principle component analysis, and gather functional orthology and gene names from the KEGG database that are associated with the metabolites in a dataset. This package was developed with inexperienced R users in mind.

If your data do not yet have KEGG compound numbers you can acquire them by using the chemical translation service provided by the Fiehn lab here http://cts.fiehnlab.ucdavis.edu/

Data Analysis

Data Format

Included with Omu is an example metabolomics dataset of data from fecal samples collected from a two factor experiment with wild type c57B6J mice and c57B6J mice with a knocked out nos2 gene, that were either mock treated, or given streptomycin(an antibiotic), and a metadata file. To use Omu, you need a metabolomics count data frame in .csv format that resembles the example dataset, with the column headers Metabolite, KEGG, and then one for each of your samples. Row values are metabolite names in the Metabolite column, KEGG cpd numbers in the KEGG column, and numeric counts in the Sample columns.Additionally, for statistical analysis your data should already have undergone missing value imputation(eg. using random forest, k nearest neighbors, etc.). Here is a truncated version of the sample data in Omu as a visual example of this:

Metabolite KEGG C289_1
xylulose_NIST C00312 2424
xylose C00181 56311
xylonolactone_NIST C02266 637
xylonic_acid C00502 545

The meta data file should ha