Metabolite profiling in LC-DAD using multivariate curve resolution: the alsace package in R

For those chemical compounds absorbing in the UV–Vis region and not readily applicable to routine mass spectrometry ionisation methods, liquid chromatography coupled to diode array detection is a convenient platform to perform metabolite profiling. Data processing by hand is labour-intensive and error prone. In the present study a strategy based on multivariate curve resolution, and its implementation in an R package called alsace are described. The final result of an analysis is a table containing peak heights or peak areas for all features of the individual injections. The capabilities of the software, providing elements such as splitting the data into separate, possibly overlapping time windows, merging the results of the individual time windows, and parametric time warping to align features, are illustrated using a cassava-derived data set.