Highly sensitive feature detection for high resolution LC/MS.

ABSTRACT:

Background

Liquid chromatography coupled to mass spectrometry (LC/MS) is an important analytical technology for e.g. metabolomics experiments. Determining the boundaries, centres and intensities of the two-dimensional signals in the LC/MS raw data is called feature detection. For the subsequent analysis of complex samples such as plant extracts, which may contain hundreds of compounds, corresponding to thousands of features -- a reliable feature detection is mandatory.

Results

We developed a new feature detection algorithm centWave for high-resolution LC/MS data sets, which collects regions of interest (partial mass traces) in the raw-data, and applies continuous wavelet transformation and optionally Gauss-fitting in the chromatographic domain. We evaluated our feature detec

SUBMITTER: Tautenhahn R 

PROVIDER: S-EPMC2639432 | biostudies-literature | 2008 Nov

REPOSITORIES: biostudies-literature