Performance evaluation of tile based Fisher Ratio analysis using a benchmark yeast metabolome dataset.
Performance of tile based Fisher Ratio (F ratio) data analysis, recently developed for discovery based studies using comprehensive two dimensional gas chromatography coupled with time of flight mass spectrometry (GCxGC TOFMS) is evaluated with a metabolomics dataset that had been previously analyzed in great detail, but while taking a brute force approach. The previously analyzed data (referred to herein as the benchmark dataset) were intracellular extracts from Saccharomyces cerevisiae (yeast) either metabolizing glucose (repressed) or ethanol (derepressed) which define the two classes in the discovery based analysis to find metabolites that are statistically different in concentration between the two classes. Beneficially, this previously analyzed dataset provides a concrete means to validate the tile based F ratio software. Herein, we demonstrate and validate the significant benefits of applying tile based F ratio analysis. The yeast metabolomics data are analyzed more rapidly in about one week versus one year for the prior studies with this dataset. Furthermore, a null distribution analysis is implemented to statistically determine an adequate F ratio threshold, whereby the variables with F ratio values below the threshold can be ignored as not class distinguishing, which provides the analyst with confidence when analyzing the hit table. Forty six of the fifty four benchmarked changing metabolites were discovered by the new methodology while consistently excluding all but one of the benchmarked nineteen false positive metabolites previously identified.
Journal of chromatography. A