Download Metabolomics Workflow Guide

Prepare for an experiment
Introduction to the workflow
Features of example
experiments
The metabolomics workflow is illustrated using an experiment with two independent variables. In “Advanced operations” on page 117 some of the capabilities of
Mass Professional are illustrated with an experiment with a single independent variable. The processes used to generate results from these experiments helps you use
MassHunter Qualitative Analysis, Mass Profiler Professional, and ID Browser with
your experiments.
Definitions
Terms and definitions used in metabolomics and metabolomic analyses vary. It is
recommended that you refer to the “Definitions” on page 180 for a list of terms and
their definitions as used in Mass Profiler Professional and in this workflow.
One-variable experiment
The one-variable experiment presents an analysis of a metabolomic response to
changes in a single independent variable, also referred to as a parameter. The data
was acquired using four (4) parameter values for the independent variable. The
parameter values consist of a single control data set that represents the organism
without perturbation and data sets from three variations where the organism is subject to one of three conditions established by the experiment design. In summary,
the one-variable experiment contains a single parameter with four parameter values
and ten replicate samples for each parameter value.
An ideal experiment involves at least ten (10) replicates for each parameter value.
Thus an ideal experiment with a single parameter and four parameter values has a
data sample size of at least forty (40) samples. In this example the minimum sampling conditions are met.
Two-variable experiment
The two-variable experiment presents an analysis of a metabolomic response to
changes in two independent variables (parameters), each with two parameter values. The parameter values of the first parameter represent a control data set associated with the organism without perturbation and when the organism was subject to
a known perturbation. The parameter values of the second parameter represent a
pair of metabolite extraction techniques where the first parameter value represents
the current state-of-the-art extraction process and the second parameter value represent the addition of a step designed to improve metabolite extraction. In summary,
the two-variable experiment contains two parameters with two parameter values,
for a total of four permutations, and four replicate samples were obtained for each
permutation.
An ideal experiment involves at least ten (10) replicates for each parameter value.
Thus an ideal experiment with two parameters, each with two parameter values, has
a data sample size of forty (40) samples (See “Replicate data” on page 36). The ideal
sample size is calculated by multiplying 2 parameters by 2 parameter values for each
parameter and then multiplying by 10 replicates for an ideal minimum sample size of
forty (2 x 2 x 10 = 40) samples. In this example the minimum sampling conditions are
not met; four replicates exist for each permutation for a total of sixteen (16) samples. While the sampling falls short of the minimum sampling recommendation, the
strong correlation of cause and effect in this experiment overcomes the sampling
deficiency and provides support for further investment in the metabolomics question
being studied.
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