40 samples data analysis - metabolite correlation

The MycoSynVac project AIMS at using cutting-edge synthetic biology methodologies to engineer Mycoplasma pneumoniae as a universal chassis for vaccination.
Designing a universal Mycoplasma chassis that can be deployed as single- or multi-vaccine in a range of animal hosts. Annually, infections caused by Mycoplasma species in poultry, cows, and pigs result in multimillion Euro losses in the USA and Europe.
There is no effective vaccination against many Mycoplasmas that infect pets, humans and farm
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1. To develop a whole-cell dynamic model framework of the metabolism of M. pneumoniae
2. To build upon M. pneumoniae models to develop a genome-scale, constraint-based model of M.
hyopneumoniae for vaccine optimization
3. To deploy the metabolic model(s) to: 1) the rational design and optimization of the vaccine chassis; 2)
aid the development of a higher-growth rate chassis; 3) assist the development of a nutrient optimized a
serum-free growth medium and; 4) assess, at genome scale, the metabolic
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Internal metabolites concentrations for time series data (not pulse experiments) and for mutant OE, KO mutants and perturbations
External metabolite concentrations for time series data (not pulse experiments) and for mutant OE, KO mutants and perturbations
Mutant (OE, KO, perturbation) metabolite measurements

Contains relative metabolite concentrations for 40 samples based on technical triplicates. Medium and SD values were calculated and used for 1000 sampled simmulations (sampling from the measurement distribution per metabolite) per sample.
Also contains annotion to link metabolite concentrations and protein fold change measurements for OE and KO mutants to the model as well as external glucose, acetate and lactate concentrations. A SBtab like format was used to easily load the MEAN and SD metabolite
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Contains the FC metabolite concentration values data and a R script to perform PCA, generate hetamaps and a correlation network.