Evidence map›Paper›PMID 21676240›Full record

ArticleBMC bioinformatics2011

Smith-Waterman peak alignment for comprehensive two-dimensional gas chromatography-mass spectrometry.

Seongho Kim, Imhoi Koo, Aiqin Fang, Xiang Zhang

Abstract read
In one paragraph

Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Seongho KimDepartment of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40292, USA. s0kim023@louisville.edu
Imhoi Koo
Aiqin Fang
Xiang Zhang

Funding

Mass Informatics of Two Dimensinoal Gas Chromatography Time-of-flight Mass SpectrR01GM087735 · NIGMS · UNIVERSITY OF LOUISVILLE · PI ZHANG, XIANG · 2009 to 2012
$1.4M
NIGMS NIH HHS 1R01GM087735NIGMS NIH HHS R01 GM087735
6 · The paper itself

Abstract

backgroundComprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC × GC-MS) is a powerful technique which has gained increasing attention over the last two decades. The GC × GC-MS provides much increased separation capacity, chemical selectivity and sensitivity for complex sample analysis and brings more accurate information about compound retention times and mass spectra. Despite these advantages, the retention times of the resolved peaks on the two-dimensional gas chromatographic columns are always shifted due to experimental variations, introducing difficulty in the data processing for metabolomics analysis. Therefore, the retention time variation must be adjusted in order to compare multiple metabolic profiles obtained from different conditions.

resultsWe developed novel peak alignment algorithms for both homogeneous (acquired under the identical experimental conditions) and heterogeneous (acquired under the different experimental conditions) GC × GC-MS data using modified Smith-Waterman local alignment algorithms along with mass spectral similarity. Compared with literature reported algorithms, the proposed algorithms eliminated the detection of landmark peaks and the usage of retention time transformation. Furthermore, an automated peak alignment software package was established by implementing a likelihood function for optimal peak alignment.

conclusionsThe proposed Smith-Waterman local alignment-based algorithms are capable of aligning both the homogeneous and heterogeneous data of multiple GC × GC-MS experiments without the transformation of retention times and the selection of landmark peaks. An optimal version of the SW-based algorithms was also established based on the associated likelihood function for the automatic peak alignment. The proposed alignment algorithms outperform the literature reported alignment method by analyzing the experiment data of a mixture of compound standards and a metabolite extract of mouse plasma with spiked-in compound standards.

Indexed as

AlgorithmsAnimalsGas Chromatography-Mass SpectrometryMetabolomicsMicePlasma

Identifiers

PMID21676240
PMCPMC3133553

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.