Citation: Fei Tang, Yi Chen, Tie-Gang Li, Jiu-Ming He, Zeper Abliz, Gang Huang, Xiao-Hao Wang. A quick and effective multivariate statistical strategy for imaging mass spectrometry[J]. Chinese Chemical Letters, ;2014, 25(10): 1331-1335. doi: 10.1016/j.cclet.2014.04.028 shu

A quick and effective multivariate statistical strategy for imaging mass spectrometry

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a State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing 100084, China;
2.
b State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China;
3.
c National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing 100094, China

Corresponding author: Xiao-Hao Wang,
Received Date: 18 February 2014
Available Online: 9 April 2014
Fund Project:

A new multivariate statistical strategy for analyzing large datasets that are produced by imaging mass spectrometry (IMS) techniques is reported. The strategy divides the whole datacube of the sample into several subsets and analyses them one by one to obtain the results. Instead of analyzing the whole datacube at one time, the strategy makes the analysis easier and decreases the computation time greatly. In this report, the IMS data are produced by the air flow-assisted ionization IMS (AFAI-IMS). The strategy can be used in combination with most multivariate statistical analysis methods. In this paper, the strategy was combined with the principal component analysis (PCA) and partial least square analysis (PLS). It was proven to be effective by analyzing the handwriting sample. By using the strategy, the m/z corresponding to the specific lipids in rat brain tissue were distinguished successfully. Moreover the analysis time grew linearly instead of exponentially as the size of sample increased. The strategy developed in this study has enormous potential for searching for the m/z of potential biomarkers quickly and effectively.
- Imaging mass spectrometry,
- Multivariate statistical analysis,
- Potential biomarkers,
- Quick and effective
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