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

<p>Abstract</p> <p>Background</p> <p>Comprehensive 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.</p> <p>Results</p> <p>We 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.</p> <p>Conclusions</p> <p>The 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.</p

Reducing the Effects of Duplication on the UN’s Operation through the Delivering as One Initiative (Mozambique).

MM thesis - P&DMThe UN’s challenges and deficiencies such as the lack of; coherence, efficiency, effectiveness and relevance at country level is well documented, however there is silence in the literature on causality of these deficiencies. Duplication is mentioned as a problem however its characteristics and role in diminishing the effectiveness of UN’s operation in Mozambique is not explained adequately. This research project concludes based on evidence that Duplication is the cause of most of the UN’s deficiencies and challenges in Mozambique. Duplication is insidious, its feeds on itself and perpetuates itself at country level. The UN has designed an interesting solution and a smart construct in Delivering as One (DaO) to address the challenges and deficiencies. DaO by diminishing the effects of Duplication has increased the level of relevance, coherence and effectiveness of the UN in Mozambique. However DaO has limitations, it is a minimalist solution that does not address the core causes of duplication and this makes DaO a vulnerable solution. Its sustainability is suspect. The UN and DaO must address the core causes of duplication and its inherent structural challenges to achieve the goals it has set for itself i.e. coherence, efficiency and relevance and in the process these actions will create conditions for the UN to strategically reposition in the revised international assistance environment

Novel system for classifying chromatographic applications, exemplified by comprehensive two-dimensional gas chromatography and multivariate analysis

For practical chromatographers it is extremely difficult to judge the merits and limitations of new technological developments. On the other hand, it is nearly impossible for those at the forefront of technology to judge the implications of their efforts for all specific applications of chromatography. Both chromatographers and researchers can be aided by a classification of the numerous specific applications into a few well-defined categories. In this paper, we propose such a classification of all chemical analysis by chromatography into three generic types of applications, viz. target-compound analysis, group-type separation, and fingerprinting. The requirements for each type are discussed in general terms. The classification scheme is applied to assess the benefits and limitations of comprehensive two-dimensional gas chromatography (GCxGC) and the possible additional benefits of using multivariate-analysis (MVA) techniques for each type of application. The conclusions pertaining to the generic types of applications are indicative for the implications of new developments for specific chemical analysis by chromatography. © 2004 Elsevier B.V. All rights reserved

Quantitative analysis of target components by comprehensive two-dimensional gas chromatography

Quantitative analysis using comprehensive two-dimensional (2D) gas chromatography (GC) is still rarely reported. This is largely due to a lack of suitable software. The objective of the present study is to generate quantitative results from a large GC x GC data set, consisting of 32 chromatograms. In this data set, six target components need to be quantified. We compare the results of conventional integration with those obtained using so-called "multiway analysis methods". With regard to accuracy and precision, integration performs slightly better than Parallel Factor (PARAFAC) analysis. In terms of speed and possibilities for automation, multiway methods in general are far superior to traditional integration. © 2003 Elsevier B.V. All rights reserved

Quantitative analysis of target components by comprehensive two-dimensional gas chromatography

Quantitative analysis using comprehensive two-dimensional (2D) gas chromatography (GC) is still rarely reported. This is largely due to a lack of suitable software. The objective of the present study is to generate quantitative results from a large GC x GC data set, consisting of 32 chromatograms. In this data set, six target components need to be quantified. We compare the results of conventional integration with those obtained using so-called "multiway analysis methods". With regard to accuracy and precision, integration performs slightly better than Parallel Factor (PARAFAC) analysis. In terms of speed and possibilities for automation, multiway methods in general are far superior to traditional integratio