Comparative evaluation of software for deconvolution of metabolomics data based on GC-TOF-MS

Traditional options available for deconvolution of data from gas chromatography-mass spectrometry (GC-MS) experiments have mostly been confined to semi-automated methods, which cannot compete with high-throughput and rapid analysis in metabolomics. In the present study, data sets acquired using GC with time-of-flight MS (GC-TOF-MS) were processed using three different deconvolution software packages (LECO ChromaTOF, AMDIS and SpectralWorks AnalyzerPro). We paid attention to the extent of detection, identification and agreement of qualitative results, and took interest in the flexibility and the productivity of these programs in their application. We made comparisons using data from the analysis of a test-mixture solution of 36 endogenous metabolites with a wide range of relative concentration ratios. We detected differences in the number of components identified and the accuracy of deconvolution. Using the AMDIS Search program, the resulting mass spectra after deconvolution were searched against the author-constructed retention index/mass spectral libraries containing both the mass spectra and the retention indices of derivatives of a set of metabolites. We based analyte identifications on both retention indices and spectral similarity. The results showed that there were large differences in the numbers of components identified and the qualitative results from the three programs. AMDIS and ChromaTOF produced a large number of false positives, while AnalyzerPro produced some false negatives. We found that, in these three software packages, component width is the most important parameter for predicting the accuracy of the deconvoluted result.