Coherent point drift peak alignment algorithms using distance and similarity measures for two‐dimensional gas chromatography mass spectrometry data
نویسندگان
چکیده
منابع مشابه
An optimal peak alignment for comprehensive two-dimensional gas chromatography mass spectrometry using mixture similarity measure
MOTIVATION Comprehensive two-dimensional gas chromatography mass spectrometry (GC × GC-MS) brings much increased separation capacity, chemical selectivity and sensitivity for metabolomics and provides more accurate information about metabolite retention times and mass spectra. However, there is always a shift of retention times in the two columns that makes it difficult to compare metabolic pro...
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Peak alignment is a critical procedure in mass spectrometry-based biomarker discovery in metabolomics. One of peak alignment approaches to comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) data is peak matching-based alignment. A key to the peak matching-based alignment is the calculation of mass spectral similarity scores. Various mass spectral similarity measures h...
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Summary Comprehensive two dimensional gas chromatography-mass spectrometry is a powerful method for analyzing complex mixtures of volatile compounds, but produces a large amount of raw data that requires downstream processing to align signals of interest (peaks) across multiple samples and match peak characteristics to reference standard libraries prior to downstream statistical analysis. Very ...
متن کاملGraph-based peak alignment algorithms for multiple liquid chromatography-mass spectrometry datasets
UNLABELLED Liquid chromatography coupled to mass spectrometry (LC-MS) is the dominant technological platform for proteomics. An LC-MS analysis of a complex biological sample can be visualized as a 'map' of which the positional coordinates are the mass-to-charge ratio (m/z) and chromatographic retention time (RT) of the chemical species profiled. Label-free quantitative proteomics requires the a...
متن کاملHDP-Align: Hierarchical Dirichlet Process Clustering for Multiple Peak Alignment of Liquid Chromatography Mass Spectrometry Data
Matching peak features across multiple LC-MS runs (alignment) is an integral part of all LC-MS data processing pipelines. Alignment is challenging due to variations in the retention time of peak features across runs and the large number of peak features produced by a single compound in the analyte. In this paper, we propose a Bayesian non-parametric model that aligns peaks via a hierarchical cl...
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ژورنال
عنوان ژورنال: Journal of Chemometrics
سال: 2020
ISSN: 0886-9383,1099-128X
DOI: 10.1002/cem.3236