ScoreMetabolites is the first node of the metabotype analysis implemented in PheNoBo.
This node is the predecessor of the MetaboToGeno node.
The task of ScoreMetabolites is to compare the metabolite concentrations measured for a patient to a set of reference values. This comparison results in a score and a p value for each measured metabolite. A high score and a low p value hint at metabolites which strongly deviate from the expected values. Such metabolites are likely to be related to the patient's disease.
ScoreMetabolites requires 2 tables with input data: the reference values and the measured metabolite concentrations. For detailed information about the format of the tables have a look at the Input Port section and at the example files provided at https://github.com/marie-sophie/mapra.
The algorithm of ScoreMetabolites is able to calculate 2 types of scores depending on the missing values in the input data.
Z Score: This node calculates a Z Score for each metabolite that fulfills 2 conditions:
(1) There are sufficient control samples: low missingness in the reference values.
(2) The metabolite was measured for the patient: the concentration in the actual measurement is not missing.
The Z score is calculated as (concentration-mean)/standard deviation. The corresponding p value is calculated analytically by assuming a Normal distribution with mean 0 and standard deviation 1 for the Z scores. As the measured metabolite concentrations strongly depend on variables like age, sex and fasting state, the reference samples are divided into phenotype groups with separate mean and standard deviation values. The patient's measured concentration is then compared to the mean and standard deviation of the appropriate phenotype group during calculation of the Z score.
Binary Score: This node calculates a Binary Score, if the data of a metabolite do not meet the conditions for calculating a Z Score. The binary score can assume 2 different values: 0 and 1. The binary score is set to 1, if condition (2) is fulfilled but condition (1) does not hold: there are not sufficient reference values to interpret the measured concentration. The binary score is set to 0, if condition (2) is violated: the concentration of the metabolite in the patient's measurement is missing. The p value corresponding to a binary score is derived from the missingness in the control samples across all phenotype groups.
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