Provides a statistical analysis software. MarkerView is an application that permits users to distil complex datasets, find statistically significant differences and reveal key insights. It includes several statistical tools, such as principle components analysis (PCA), principle components variable grouping (PCVG) and T-tests. This software enables users to interpret results through interactive plots.
Processes tandem MS files and builds MassBank records. RMassBank’s functions include automated extraction of tandem MS spectra, formula assignment to tandem MS fragments, recalibration of tandem MS spectra with assigned fragments, spectrum clean up, automated retrieval of compound information from Internet databases, and export to MassBank records.
Allows analysis of copolymer and homopolymer composition. Polymerix is a program permitting to study copolymer mixtures and deconvolution of homopolymer. This tool can find two sequential monoisotopic ions and compute assignment of spectral features to individual series components.
Proceeds to automatic batch-conversion of capillary electrophoresis coupled to mass spectrometry (CE-MS) files into an effective electrophoretic mobility scale. ROMANCE permits direct comparison of the measured electrophoretic mobility with values obtained in either the same or different laboratories from reference standards. It can be used for two kinds of background electrolyte (BGE) markers.
A powerful platform to discriminate biological features from the various noise sources prevalent in untargeted metabolomic data. The process is experimentally straightforward and can be easily implemented in any metabolomic laboratory. Feature credentialing reliably removes artifactual features such as those arising from chemical and informatic noise, thereby resulting in a valuable list of features of biological origin. These credentialed features address many of the drawbacks associated with feature counting in comparing method performance on the basis of metabolome coverage. As such, counting credentialed features can be used in the development and optimization of untargeted metabolomic approaches as demonstrated by the reoptimization of XCMS parameters. Credentialing features is also an effective data reduction strategy for untargeted metabolomic results such that a smaller number of peaks can be targeted for MS/MS analysis.