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MSRC Mass Spectrometry Research and Development

EXIMS: an improved data analysis pipeline based on a new peak picking method for EXploring Imaging Mass Spectrometry data.

AUTHORS

Wijetunge CDChalini D , Saeed I Isaam , Boughton BA Berin A , Spraggins JM Jeffrey M , Caprioli RM Richard M , Bacic A Antony , Roessner U Ute , Halgamuge SK Saman K . Bioinformatics (Oxford, England). 2015 10 1; 31(19). 3198-206

ABSTRACT

Matrix Assisted Laser Desorption Ionization-Imaging Mass Spectrometry (MALDI-IMS) in ‘omics’ data acquisition generates detailed information about the spatial distribution of molecules in a given biological sample. Various data processing methods have been developed for exploring the resultant high volume data. However, most of these methods process data in the spectral domain and do not make the most of the important spatial information available through this technology. Therefore, we propose a novel streamlined data analysis pipeline specifically developed for MALDI-IMS data utilizing significant spatial information for identifying hidden significant molecular distribution patterns in these complex datasets.

Matrix Assisted Laser Desorption Ionization-Imaging Mass Spectrometry (MALDI-IMS) in ‘omics’ data acquisition generates detailed information about the spatial distribution of molecules in a given biological sample. Various data processing methods have been developed for exploring the resultant high volume data. However, most of these methods process data in the spectral domain and do not make the most of the important spatial information available through this technology. Therefore, we propose a novel streamlined data analysis pipeline specifically developed for MALDI-IMS data utilizing significant spatial information for identifying hidden significant molecular distribution patterns in these complex datasets.