Warping and alignment technologies for inter-sample feature correspondence in 1D H-NMR, chromatography-, and capillary electrophoresis-mass spectrometry data

Abstract

Comprehensive analysis is an emerging and interesting mode of analyzing biological samples. The hypothesis is that by measuring the abundance of as many analytes as possible in samples of biological origin, new knowledge about biological regulation and pathways and can be gained. This hypothesis is one of the cornerstones of the -omics sciences. The comprehensive measurements are usually performed by H-NMR or hyphenated mass spectrometry of almost intact biofluids and tissues. The data generated from these measurements are very complex, containing thousands of analyte signals, necessitating automatic information extraction. The success of this information extraction is dependent on many steps and a most crucial step is solving the inter-sample correspondence problem, i.e. that analytes from different samples are unsynchronized in the measured data. This problem hampers the data-analysis pipeline by introducing errors in the resulting extracted abundance data. The remedy is usually tedious manual inspection for analyte synchronization. In this paper, we address automated methods for addressing the inter-sample correspondence problem when analyzing data from comprehensive measurements, i.e. synchronization methods. We here present a review based on methods taxonomy, complexity, and an overview of current solution technologies available.