Informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography and high-resolution mass spectrometry (GCxGC-HRMS)

Reichenbach, Stephen E; Tian, Xue; Tao, Qingping; Ledford, Edward B; Wu, Zhanpin; Fiehn, Oliver (2011). Informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography and high-resolution mass spectrometry (GCxGC-HRMS). Talanta, 83(4), pp. 1279-88. Amsterdam: Elsevier 10.1016/j.talanta.2010.09.057

Full text not available from this repository.

This paper describes informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography (GCxGC) and high-resolution mass spectrometry (HRMS). GCxGC-HRMS analysis produces large data sets that are rich with information, but highly complex. The size of the data and volume of information requires automated processing for comprehensive cross-sample analysis, but the complexity poses a challenge for developing robust methods. The approach developed here analyzes GCxGC-HRMS data from multiple samples to extract a feature template that comprehensively captures the pattern of peaks detected in the retention-times plane. Then, for each sample chromatogram, the template is geometrically transformed to align with the detected peak pattern and generate a set of feature measurements for cross-sample analyses such as sample classification and biomarker discovery. The approach avoids the intractable problem of comprehensive peak matching by using a few reliable peaks for alignment and peak-based retention-plane windows to define comprehensive features that can be reliably matched for cross-sample analysis. The informatics are demonstrated with a set of 18 samples from breast-cancer tumors, each from different individuals, six each for Grades 1-3. The features allow classification that matches grading by a cancer pathologist with 78% success in leave-one-out cross-validation experiments. The HRMS signatures of the features of interest can be examined for determining elemental compositions and identifying compounds.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Dermatology, Urology, Rheumatology, Nephrology, Osteoporosis (DURN) > Clinic of Rheumatology and Immunology

UniBE Contributor:

Reichenbach, Stephan

ISSN:

0039-9140

Publisher:

Elsevier

Language:

English

Submitter:

Factscience Import

Date Deposited:

04 Oct 2013 14:10

Last Modified:

05 Dec 2022 14:01

Publisher DOI:

10.1016/j.talanta.2010.09.057

PubMed ID:

21215864

Web of Science ID:

000286718700026

URI:

https://boris.unibe.ch/id/eprint/1690 (FactScience: 203571)

Actions (login required)

Edit item Edit item
Provide Feedback