Contextual automated template alignment for 2D group type separations with univariate detection

Comprehensive two dimensional chromatography has the ability to elucidate highly complex mixtures. The conversion from measurement to (pseudo) compound identification and qualification is a crucial yet, complex and laborious step. Commonly, templates are used to achieve this. Unfortunately, these templates require frequent adjustment. Doing this manually is tedious and time consuming. The work presented in this paper aims to assist with this process by automating the adjustment of the templates by utilising contextual anchor points and point set registration. With this method, a 87.2% correct classification with a RSD of 6% was achieved relative to 43.5% correct classification with a RSD of 34.9% when no adjustments were made. These results were obtained from a study with 17 chromatograms and 17 templates. Each template was aligned to each chromatogram resulting in 289 scenarios. By Automating the alignment of templates in comprehensive two dimensional chromatography data, the time consumption and complexity of a comprehensive two dimensional analysis could be reduced, aiding in further adaptation of the technique.