Combining peak- and chromatogram-based retention time alignment algorithms for multiple chromatography-mass spectrometry datasets.

ABSTRACT:

Background

Modern analytical methods in biology and chemistry use separation techniques coupled to sensitive detectors, such as gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). These hyphenated methods provide high-dimensional data. Comparing such data manually to find corresponding signals is a laborious task, as each experiment usually consists of thousands of individual scans, each containing hundreds or even thousands of distinct signals. In order to allow for successful identification of metabolites or proteins within such data, especially in the context of metabolomics and proteomics, an accurate alignment and matching of corresponding features between two or more experiments is required. Such a matching algorithm should captur

SUBMITTER: Hoffmann N 

PROVIDER: S-EPMC3546004 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature