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"peak alignment"

Jingyun Chen, Yi Li, Elizabeth Pirraglia, Nobuyuki Okamura, Henry Rusinek, Mony J de Leon
PURPOSE: Off-target binding in the reference region is a challenge for recent tau tracers 18 F-AV-1451 and 18 F-THK5351. The conventional standardized uptake value ratio (SUVR) method relies on the average uptake from an unaffected tissue sample, and therefore is susceptible to biases from off-target binding as well as variability among individuals in the reference region. We propose a new method, standardized uptake value peak-alignment (SUVP), to reduce the bias of the SUVR, and improve the quantitative assessment of tau deposition...
April 27, 2018: European Journal of Nuclear Medicine and Molecular Imaging
Min He, Pan Yan, Zhi-Yu Yang, Zhi-Min Zhang, Tian-Biao Yang, Liang Hong
Head Space/Solid Phase Micro-Extraction (HS-SPME) coupled with Gas Chromatography/Mass Spectrometer (GC/MS) was used to determine the volatile/heat-labile components in Ligusticum chuanxiong Hort - Cyperus rotundus rhizomes. Facing co-eluting peaks in k samples, a trilinear structure was reconstructed to obtain the second-order advantage. The retention time (RT) shift with multi-channel detection signals for different samples has been vital in maintaining the trilinear structure, thus a modified multiscale peak alignment (mMSPA) method was proposed in this paper...
March 15, 2018: Journal of Chromatography. B, Analytical Technologies in the Biomedical and Life Sciences
Hiroshi Tsugawa
Mass spectrometry (MS)-based metabolomics is the popular platform for metabolome analyses. Computational techniques for the processing of MS raw data, for example, feature detection, peak alignment, and the exclusion of false-positive peaks, have been established. The next stage of untargeted metabolomics would be to decipher the mass fragmentation of small molecules for the global identification of human-, animal-, plant-, and microbiota metabolomes, resulting in a deeper understanding of metabolisms. This review is an update on the latest computational metabolomics including known/expected structure databases, chemical ontology classifications, and mass spectrometry cheminformatics for the interpretation of mass fragmentations and for the elucidation of unknown metabolites...
January 29, 2018: Current Opinion in Biotechnology
Ryne C Ramaker, Emily Gordon, Sara J Cooper
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 few existing tools address this aspect of analysis and those that do have shortfalls in usability or performance...
December 21, 2017: Bioinformatics
Sven H F Jaeschke, Matthew D Robson, Aaron T Hess
PURPOSE: To establish a cardiac signal from scattering matrix or scattering coefficient measurements made on a 7T 8-channel parallel transmit (pTx) system, and to evaluate its use for cardiac gating. METHODS: Measurements of the scattering matrix and scattering coefficients were acquired using a monitoring pulse sequence and during a standard cine acquisition, respectively. Postprocessing used an independent component analysis and gating feature identification. The effect of the phase of the excitation radiofrequency (RF) field ( B1+ shim) on the cardiac signal was simulated for multiple B1+ shim configurations, and cine images were reconstructed from both the scattering coefficients and electrocardiogram (ECG)...
December 11, 2017: Magnetic Resonance in Medicine: Official Journal of the Society of Magnetic Resonance in Medicine
Ying Yan, Hui Zhao, Li-Si Zou, Xun-Hong Liu, Chuan Chai, Sheng-Nan Wang, Yu-Jiao Hua
In order to study the influence of ecological environment regarding the synthesis and accumulation of metabolites in Eucommiae Cortex, LC-QTOF MS/MS method combined with multivariate statistical analysis was used to analyze the differences of chemical constituents in Eucommiae Cortex from different habitats. Through the analysis of the multistage tandem mass spectrometry, the characteristic peaks were extracted with mass spectrometry data peak matching, peak alignment, and noise filtering. Principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) were used for data processing...
July 2017: Zhongguo Zhong Yao za Zhi, Zhongguo Zhongyao Zazhi, China Journal of Chinese Materia Medica
Yang Wang, Ruibing Feng, Ruibing Wang, Fengqing Yang, Peng Li, Jian-Bo Wan
Metabolite identification is one of the major bottlenecks in liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics owing to the difficulty of acquiring MS/MS information of most metabolites detected. Data dependent acquisition (DDA) has been currently used to acquire MS/MS data in untargeted metabolomics. When dealing with the complex biological samples, top-n-based DDA method selects only a small fraction of the ions for fragmentation, leading to low MS/MS coverage of metabolites in untargeted metabolomics...
November 1, 2017: Analytica Chimica Acta
Lili Li, Weijie Ren, Hongwei Kong, Chunxia Zhao, Xinjie Zhao, Xiaohui Lin, Xin Lu, Guowang Xu
Liquid chromatography-mass spectrometry (LC-MS) is an important analytical platform for metabolomics study. Peak alignment of metabolomics dataset is one of the keys for a successful metabolomics study. In this work, a MS/MS-based peak alignment method for LC-MS metabolomics data was developed. A rigorous strategy for screening endogenous reference variables was proposed. Firstly, candidate endogenous reference variables were selected based on MS, MS/MS and retention time in all samples. Multiple robust endogenous reference variables were obtained through further evaluation and confirmation...
October 16, 2017: Analytica Chimica Acta
Remy Gavard, David Rossell, Simon E F Spencer, Mark P Barrow
Fourier transform ion cyclotron resonance mass spectrometry affords the resolving power to determine an unprecedented number of components in complex mixtures, such as petroleum. The software tools required to also analyze these data struggle to keep pace with advancing instrument capabilities and increasing quantities of data, particularly in terms of combining information efficiently across multiple replicates. Improved confidence in data and the use of replicates is particularly important where strategic decisions will be based upon the analysis...
November 7, 2017: Analytical Chemistry
Hai-Yan Fu, Xiao-Ming Guo, Yue-Ming Zhang, Jing-Jing Song, Qing-Xia Zheng, Ping-Ping Liu, Peng Lu, Qian-Si Chen, Yong-Jie Yu, Yuanbin She
High-quality data analysis methodology remains a bottleneck for metabolic profiling analysis based on ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry. The present work aims to address this problem by proposing a novel data analysis strategy wherein (1) chromatographic peaks in the UPLC-QTOF data set are automatically extracted by using an advanced multiscale Gaussian smoothing-based peak extraction strategy; (2) a peak annotation stage is used to cluster fragment ions that belong to the same compound...
October 17, 2017: Analytical Chemistry
Hai-Yan Fu, Ou Hu, Yue-Ming Zhang, Li Zhang, Jing-Jing Song, Peang Lu, Qing-Xia Zheng, Ping-Ping Liu, Qian-Si Chen, Bing Wang, Xiao-Yu Wang, Lu Han, Yong-Jie Yu
Nontargeted metabolic profiling analysis is a difficult task in a routine investigation because hundreds of chromatographic peaks are eluted within a short time, and the time shift problem is severe across samples. To address these problems, the present work developed an automatic nontargeted metabolic profiling analysis (anTMPA) method. First, peaks from the total ion chromatogram were extracted using modified multiscale Gaussian smoothing method. Then, a novel peak alignment strategy was employed based on the mass spectra and retention times of the peaks in which the maximum mass spectral correlation coefficient path was extracted using a modified dynamic programming method...
September 1, 2017: Journal of Chromatography. A
Evita C Wiegers, Bart W J Philips, Arend Heerschap, Marinette van der Graaf
OBJECTIVE: J-difference editing is often used to select resonances of compounds with coupled spins in1 H-MR spectra. Accurate phase and frequency alignment prior to subtracting J-difference-edited MR spectra is important to avoid artefactual contributions to the edited resonance. MATERIALS AND METHODS: In-vivo J-difference-edited MR spectra were aligned by maximizing the normalized scalar product between two spectra (i.e., the correlation over a spectral region)...
December 2017: Magma
Leonardo Perez de Souza, Thomas Naake, Takayuki Tohge, Alisdair R Fernie
The grand challenge currently facing metabolomics is the expansion of the coverage of the metabolome from a minor percentage of the metabolic complement of the cell toward the level of coverage afforded by other post-genomic technologies such as transcriptomics and proteomics. In plants, this problem is exacerbated by the sheer diversity of chemicals that constitute the metabolome, with the number of metabolites in the plant kingdom generally considered to be in excess of 200 000. In this review, we focus on web resources that can be exploited in order to improve analyte and ultimately metabolite identification and quantification...
July 1, 2017: GigaScience
Binhua Tang, Xihan Wang, Victor X Jin
Sequencing data quality and peak alignment efficiency of ChIP-sequencing profiles are directly related to the reliability and reproducibility of NGS experiments. Till now, there is no tool specifically designed for optimal peak alignment estimation and quality-related genomic feature extraction for ChIP-sequencing profiles. We developed open-sourced COPAR, a user-friendly package, to statistically investigate, quantify, and visualize the optimal peak alignment and inherent genomic features using ChIP-seq data from NGS experiments...
2017: BioMed Research International
Jeramie D Watrous, Mir Henglin, Brian Claggett, Kim A Lehmann, Martin G Larson, Susan Cheng, Mohit Jain
Untargeted liquid-chromatography-mass spectrometry (LC-MS)-based metabolomics analysis of human biospecimens has become among the most promising strategies for probing the underpinnings of human health and disease. Analysis of spectral data across population scale cohorts, however, is precluded by day-to-day nonlinear signal drifts in LC retention time or batch effects that complicate comparison of thousands of untargeted peaks. To date, there exists no efficient means of visualization and quantitative assessment of signal drift, correction of drift when present, and automated filtering of unstable spectral features, particularly across thousands of data files in population scale experiments...
February 7, 2017: Analytical Chemistry
Owen E Branson, Michael A Freitas
Label-free quantitative methods are advantageous in bottom-up (shotgun) proteomics because they are robust and can easily be applied to different workflows without additional cost. Both label-based and label-free approaches are routinely applied to discovery-based proteomics experiments and are widely accepted as semiquantitative. Label-free quantitation approaches are segregated into two distinct approaches: peak-abundance-based approaches and spectral counting (SpC). Peak abundance approaches like MaxLFQ, which is integrated into the MaxQuant environment, require precursor peak alignment that is computationally intensive and cannot be routinely applied to low-resolution data...
December 2, 2016: Journal of Proteome Research
Beichuan Deng, Seongho Kim, Hengguang Li, Elisabeth Heath, Xiang Zhang
Comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC[Formula: see text][Formula: see text][Formula: see text]GC-MS) has been used to analyze multiple samples in a metabolomics study. However, due to some uncontrollable experimental conditions, such as the differences in temperature or pressure, matrix effects on samples and stationary phase degradation, there is always a shift of retention times in the two GC columns between samples. In order to correct the retention time shifts in GC[Formula: see text][Formula: see text][Formula: see text]GC-MS, the peak alignment is a crucial data analysis step to recognize the peaks generated by the same metabolite in different samples...
December 2016: Journal of Bioinformatics and Computational Biology
Ibrahim Karaman, Diana L S Ferreira, Claire L Boulangé, Manuja R Kaluarachchi, David Herrington, Anthony C Dona, Raphaële Castagné, Alireza Moayyeri, Benjamin Lehne, Marie Loh, Paul S de Vries, Abbas Dehghan, Oscar H Franco, Albert Hofman, Evangelos Evangelou, Ioanna Tzoulaki, Paul Elliott, John C Lindon, Timothy M D Ebbels
Large-scale metabolomics studies involving thousands of samples present multiple challenges in data analysis, particularly when an untargeted platform is used. Studies with multiple cohorts and analysis platforms exacerbate existing problems such as peak alignment and normalization. Therefore, there is a need for robust processing pipelines that can ensure reliable data for statistical analysis. The COMBI-BIO project incorporates serum from ∼8000 individuals, in three cohorts, profiled by six assays in two phases using both (1)H NMR and UPLC-MS...
December 2, 2016: Journal of Proteome Research
Benjamin C Rowland, Huijun Liao, Fatah Adan, Laura Mariano, John Irvine, Alexander P Lin
PURPOSE: Averaging multiple repetitions to improve signal-to-noise ratio is common practice in magnetic resonance spectroscopy (MRS). However, temporal variations in scanner B0 due to motion or gradient heating may cause spectra to become misaligned, broadening and distorting peaks and impacting on processing and quantification. We present a comparison using in vivo data of different methods for correcting these errors. METHODS: Three different correction methods were applied to 53 brain scans: residual water peak alignment, creatine fitting, and spectral registration...
January 2017: Journal of Neuroimaging: Official Journal of the American Society of Neuroimaging
Yu-Jen Liang, Yu-Ting Lin, Chia-Wei Chen, Chien-Wei Lin, Kun-Mao Chao, Wen-Harn Pan, Hsin-Chou Yang
Metabolomics data provide unprecedented opportunities to decipher metabolic mechanisms by analyzing hundreds to thousands of metabolites. Data quality concerns and complex batch effects in metabolomics must be appropriately addressed through statistical analysis. This study developed an integrated analysis tool for metabolomics studies to streamline the complete analysis flow from initial data preprocessing to downstream association analysis. We developed Statistical Metabolomics Analysis-An R Tool (SMART), which can analyze input files with different formats, visually represent various types of data features, implement peak alignment and annotation, conduct quality control for samples and peaks, explore batch effects, and perform association analysis...
June 21, 2016: Analytical Chemistry
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