2013
DOI: 10.1089/omi.2013.0010
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Evaluation of Normalization Methods to Pave the Way Towards Large-Scale LC-MS-Based Metabolomics Profiling Experiments

Abstract: Combining liquid chromatography-mass spectrometry (LC-MS)-based metabolomics experiments that were collected over a long period of time remains problematic due to systematic variability between LC-MS measurements. Until now, most normalization methods for LC-MS data are model-driven, based on internal standards or intermediate quality control runs, where an external model is extrapolated to the dataset of interest. In the first part of this article, we evaluate several existing data-driven normalization approa… Show more

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Cited by 100 publications
(100 citation statements)
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“…On the other hand, it should not be too crude such that biological effects are distorted. Several methods are available to normalize data, such as cyclic LOESS, quantile, and median normalization, etc (43,50). However, when comparing isobaric labeled data from multiple experimental designs, these methods have their shortcomings or require reference samples in each experimental setup to allow for cross-set comparison (51 Therefore, we propose a new and easy to use normalization method, called CONSTANd, which allows accurate normalization of multiplexed, isobaric labeled samples in a datadriven and global manner.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…On the other hand, it should not be too crude such that biological effects are distorted. Several methods are available to normalize data, such as cyclic LOESS, quantile, and median normalization, etc (43,50). However, when comparing isobaric labeled data from multiple experimental designs, these methods have their shortcomings or require reference samples in each experimental setup to allow for cross-set comparison (51 Therefore, we propose a new and easy to use normalization method, called CONSTANd, which allows accurate normalization of multiplexed, isobaric labeled samples in a datadriven and global manner.…”
Section: Discussionmentioning
confidence: 99%
“…This type of inaccuracies can be remediated by data normalization. Luckily, a plethora of data normalization methods exist that can be borrowed from micro-array, LC-MS or NMR data analysis (12)(13)(14)(15). Some of these normalization techniques are already implemented in software packages dedicated for mass spectral data, as the case for the DAPAR implemented in R Bioconductor.…”
mentioning
confidence: 99%
“…Each individual ion was finally normalized (if necessary according to the drift of equivalent ion of pooled samples) and injection order (van der Kloet et al 2009). Data were calibrated between batches (inter-batch calibration for the study of spatial patterns) by dividing each ion by the intra-batch mean value of pooled-sample ions, and multiplying by the total mean value for all batches (Ejigu et al 2013). Metabolites were annotated with constructor software (Bruker Compass DataAnalysis 4.3).…”
Section: Data Analysesmentioning
confidence: 99%
“…[96] For example, if the lab receives ~0.5 ml of a biofluid (serum/plasma/urine), 50 µl should be taken from each and combined to make a pooled sample that is well mixed and then divided into aliquot volumes that are the same as those to be used for analysis of the unknown samples. These aliquots are frozen along with the unknown samples and thawed once when needed to be included for analysis.…”
Section: Sample Poolingmentioning
confidence: 99%