The Experts below are selected from a list of 19992 Experts worldwide ranked by ideXlab platform

Ron M A Heeren - One of the best experts on this subject based on the ideXlab platform.

  • Trends in Mass Spectrometry Imaging for cardiovascular diseases
    Analytical and Bioanalytical Chemistry, 2019
    Co-Authors: Stephanie T. P. Mezger, Alma M. A. Mingels, Otto Bekers, Berta Cillero-pastor, Ron M A Heeren
    Abstract:

    Mass Spectrometry Imaging (MSI) is a widely established technology; however, in the cardiovascular research field, its use is still emerging. The technique has the advantage of analyzing multiple molecules without prior knowledge while maintaining the relation with tissue morphology. Particularly, MALDI-based approaches have been applied to obtain in-depth knowledge of cardiac (dys)function. Here, we discuss the different aspects of the MSI protocols, from sample handling to instrumentation used in cardiovascular research, and critically evaluate these methods. The trend towards structural lipid analysis, identification, and “top-down” protein MSI shows the potential for implementation in (pre)clinical research and complementing the diagnostic tests. Moreover, new insights into disease progression are expected and thereby contribute to the understanding of underlying mechanisms related to cardiovascular diseases.

  • Automated, parallel Mass Spectrometry Imaging and structural identification of lipids
    Nature methods, 2018
    Co-Authors: Shane R. Ellis, Martin R. L. Paine, Gert B. Eijkel, Josch K. Pauling, Peter Husen, Mark W. Jervelund, Martin Hermansson, Christer S. Ejsing, Ron M A Heeren
    Abstract:

    We report a method that enables automated data-dependent acquisition of lipid tandem Mass Spectrometry data in parallel with a high-resolution Mass Spectrometry Imaging experiment. The method does not increase the total image acquisition time and is combined with automatic structural assignments. This lipidome-per-pixel approach automatically identified and validated 104 unique molecular lipids and their spatial locations from rat cerebellar tissue.

  • Imaging Mass Spectrometry: Methods and Protocols - Mass Spectrometry Imaging of Drugs of Abuse in Hair.
    Methods in molecular biology (Clifton N.J.), 2017
    Co-Authors: Bryn Flinders, Eva Cuypers, Tiffany Porta, Emmanuel Varesio, Gérard Hopfgartner, Ron M A Heeren
    Abstract:

    Hair testing is a powerful tool routinely used for the detection of drugs of abuse. The analysis of hair is highly advantageous as it can provide prolonged drug detectability versus that in biological fluids and chronological information about drug intake based on the average growth of hair. However, current methodology requires large amounts of hair samples and involves complex time-consuming sample preparation followed by gas or liquid chromatography coupled with Mass Spectrometry. Mass Spectrometry Imaging is increasingly being used for the analysis of single hair samples, as it provides more accurate and visual chronological information in single hair samples.Here, two methods for the preparation of single hair samples for Mass Spectrometry Imaging are presented.The first uses an in-house built cutting apparatus to prepare longitudinal sections, the second is a method for embedding and cryo-sectioning hair samples in order to prepare cross-sections all along the hair sample.

  • Spatial Autocorrelation in Mass Spectrometry Imaging.
    Analytical chemistry, 2016
    Co-Authors: Alberto Cassese, Ron M A Heeren, Liam A. Mcdonnell, Arn M. J. M. Van Den Maagdenberg, Shane R. Ellis, Axel Walch, Nina Ogrinc Potočnik, Elke Burgermeister, Matthias P. Ebert, Benjamin Balluff
    Abstract:

    Mass Spectrometry Imaging (MSI) is a powerful molecular Imaging technique. In microprobe MSI, images are created through a grid-wise interrogation of individual spots by Mass Spectrometry across a surface. Classical statistical tests for within-sample comparisons fail as close-by measurement spots violate the assumption of independence of these tests, which can lead to an increased false-discovery rate. For spatial data, this effect is referred to as spatial autocorrelation. In this study, we investigated spatial autocorrelation in three different matrix-assisted laser desorption/ionization MSI data sets. These data sets cover different molecular classes (metabolites/drugs, lipids, and proteins) and different spatial resolutions ranging from 20 to 100 μm. Significant spatial autocorrelation was detected in all three data sets and found to increase with decreasing pixel size. To enable statistical testing for differences in Mass signal intensities between regions of interest within MSI data sets, we propos...

  • Automatic Generic Registration of Mass Spectrometry Imaging Data to Histology Using Nonlinear Stochastic Embedding
    Analytical chemistry, 2014
    Co-Authors: Walid M. Abdelmoula, Benjamin Balluff, Karolina Škrášková, Ricardo J. Carreira, Else A. Tolner, Boudewijn P. F. Lelieveldt, Laurens Van Der Maaten, Hans Morreau, Arn M. J. M. Van Den Maagdenberg, Ron M A Heeren
    Abstract:

    The combination of Mass Spectrometry Imaging and histology has proven a powerful approach for obtaining molecular signatures from specific cells/tissues of interest, whether to identify biomolecular changes associated with specific histopathological entities or to determine the amount of a drug in specific organs/compartments. Currently there is no software that is able to explicitly register Mass Spectrometry Imaging data spanning different ionization techniques or Mass analyzers. Accordingly, the full capabilities of Mass Spectrometry Imaging are at present underexploited. Here we present a fully automated generic approach for registering Mass Spectrometry Imaging data to histology and demonstrate its capabilities for multiple Mass analyzers, multiple ionization sources, and multiple tissue types.

Olivier Laprévote - One of the best experts on this subject based on the ideXlab platform.

  • Mass Spectrometry Imaging of biological tissue: an approach for multicenter studies
    Analytical and Bioanalytical Chemistry, 2015
    Co-Authors: Andreas Römpp, Bernhard Spengler, Alain Brunelle, Olivier Laprévote, Jean-pierre Both, Ron Heeren, Brendan Prideaux, Alexandre Seyer, Markus Stoeckli, Donald Smith
    Abstract:

    Mass Spectrometry Imaging has become a popular tool for probing the chemical complexity of biological surfaces. This led to the development of a wide range of instrumentation and preparation protocols. It is thus desirable to evaluate and compare the data output from different methodologies and Mass spectrometers. Here, we present an approach for the comparison of Mass Spectrometry Imaging data from different laboratories (often referred to as multicenter studies). This is exemplified by the analysis of mouse brain sections in five laboratories in Europe and the USA. The instrumentation includes matrix-assisted laser desorption/ionization (MALDI)-time-of-flight (TOF), MALDI-QTOF, MALDI-Fourier transform ion cyclotron resonance (FTICR), atmospheric-pressure (AP)-MALDI-Orbitrap, and cluster TOF-secondary ion Mass Spectrometry (SIMS). Experimental parameters such as measurement speed, Imaging bin width, and Mass spectrometric parameters are discussed. All datasets were converted to the standard data format imzML and displayed in a common open-source software with identical parameters for visualization, which facilitates direct comparison of MS images. The imzML conversion also allowed exchange of fully functional MS Imaging datasets between the different laboratories. The experiments ranged from overview measurements of the full mouse brain to detailed analysis of smaller features (depending on spatial resolution settings), but common histological features such as the corpus callosum were visible in all measurements. High spatial resolution measurements of AP-MALDI-Orbitrap and TOF-SIMS showed comparable structures in the low-micrometer range. We discuss general considerations for planning and performing multicenter studies in Mass Spectrometry Imaging. This includes details on the selection, distribution, and preparation of tissue samples as well as on data handling. Such multicenter studies in combination with ongoing activities for reporting guidelines, a common data format (imzML) and a public data repository can contribute to more reliability and transparency of MS Imaging studies.

  • Micrometric molecular histology of lipids by Mass Spectrometry Imaging
    Current opinion in chemical biology, 2011
    Co-Authors: David Touboul, Olivier Laprévote, Alain Brunelle
    Abstract:

    Time-Of-Flight Secondary Ion Mass Spectrometry is compared to other Mass Spectrometry Imaging techniques, and recent improvements of the experimental methods, driven by biological and biomedical applications, are described and discussed. This review shows that this method that can be considered as a micrometric molecular histology is particularly efficient for obtaining images of various lipid species at the surface of a tissue sample, without sample preparation, and with a routine spatial resolution of 1μm or less.

  • Localization of Flavonoids in Seeds by Cluster Time-of-Flight Secondary Ion Mass Spectrometry Imaging
    Analytical chemistry, 2010
    Co-Authors: Alexandre Seyer, Alain Brunelle, Jacques Einhorn, Olivier Laprévote
    Abstract:

    Time-of-flight secondary ion Mass Spectrometry Imaging has been used to map flavonoids in fresh seed sections of peas (Pisum sativum) and Arabidopsis thaliana. While for peas a very simple preparation method derived from mammalian tissue Imaging could be utilized, several preparation methods had to be tested for the A. thaliana seeds before obtaining tissue sections on which the diagnostic ions were not delocalized. For such small and stiff biological material, none of the methods currently used in histology or scanning electron microscopy could be transferred to Mass Spectrometry Imaging. Only the embedding of the fresh seeds in a polyester resin, followed by the analysis of the block after having obtained a flat surface section with a diamond blade, gave sensitive and reproducible results. Several flavonoid ions have been detected in the sections, showing increased concentrations of flavonoids in the seed coats. The method was finally applied to confirm the variations in the flavonoid content of seeds f...

  • Localization of Flavonoids in Seeds by Cluster Time-of-Flight Secondary Ion Mass Spectrometry Imaging.
    Analytical Chemistry, 2010
    Co-Authors: Alexandre Seyer, Alain Brunelle, Jacques Einhorn, Olivier Laprévote
    Abstract:

    Time-of-flight secondary ion Mass Spectrometry Imaging has been used to map flavonoids in fresh seed sections of peas ( Pisum sativum ) and Arabidopsis thaliana . While for peas a very simple preparation method derived from mammalian tissue Imaging could be utilized, several preparation methods had to be tested for the A. thaliana seeds before obtaining tissue sections on which the diagnostic ions were not delocalized. For such small and stiff biological material, none of the methods currently used in histology or scanning electron microscopy could be transferred to Mass Spectrometry Imaging. Only the embedding of the fresh seeds in a polyester resin, followed by the analysis of the block after having obtained a flat surface section with a diamond blade, gave sensitive and reproducible results. Several flavonoid ions have been detected in the sections, showing increased concentrations of flavonoids in the seed coats. The method was finally applied to confirm the variations in the flavonoid content of seeds from different A. thaliana mutants.

  • In situ primary metabolites localization on a rat brain section by chemical Mass Spectrometry Imaging
    Analytical Chemistry, 2009
    Co-Authors: Farida Benabdellah, David Touboul, Alain Brunelle, Olivier Laprévote
    Abstract:

    We describe here the detection and identification of 13 primary metabolites (AMP, ADP, ATP, UDP-GlcNAc, ...) directly from rat brain sections by chemical Mass Spectrometry Imaging. Matrix-assisted laser desorption/ionization tandem Mass Spectrometry (MALDI-MS/MS) was combined with 9-aminoacridine as a powerful matrix. We also demonstrate that a new robotic sprayer allows us to homogeneously coat the surface with the matrix, enabling the acquisition of chemical images at a 50 microm resolution, leading us to precisely and simultaneously localize each metabolite over the tissue surface. These experiments open a new field of investigation for chemical Mass Spectrometry Imaging and are of great interest for both chemists and biologists.

Benjamin Balluff - One of the best experts on this subject based on the ideXlab platform.

  • Experimental and Data Analysis Considerations for Three-Dimensional Mass Spectrometry Imaging in Biomedical Research
    Molecular Imaging and Biology, 2020
    Co-Authors: D. R. N. Vos, Benjamin Balluff, S. R. Ellis, R. M. A. Heeren
    Abstract:

    Mass Spectrometry Imaging (MSI) enables the visualization of molecular distributions on complex surfaces. It has been extensively used in the field of biomedical research to investigate healthy and diseased tissues. Most of the MSI studies are conducted in a 2D fashion where only a single slice of the full sample volume is investigated. However, biological processes occur within a tissue volume and would ideally be investigated as a whole to gain a more comprehensive understanding of the spatial and molecular complexity of biological samples such as tissues and cells. Mass Spectrometry Imaging has therefore been expanded to the 3D realm whereby molecular distributions within a 3D sample can be visualized. The benefit of investigating volumetric data has led to a quick rise in the application of single-sample 3D-MSI investigations. Several experimental and data analysis aspects need to be considered to perform successful 3D-MSI studies. In this review, we discuss these aspects as well as ongoing developments that enable 3D-MSI to be routinely applied to multi-sample studies.

  • Mass Spectrometry Imaging of Metabolites.
    Methods in molecular biology (Clifton N.J.), 2018
    Co-Authors: Benjamin Balluff, Liam A. Mcdonnell
    Abstract:

    Mass Spectrometry Imaging (MSI) is a technique which is gaining increasing interest in biomedical research due to its capacity to visualize molecules in tissues. First applied to the field of clinical proteomics, its potential for metabolite Imaging in biomedical studies is now being recognized. Here we describe how to set up experiments for Mass Spectrometry Imaging of metabolites in clinical tissues and how to tackle most of the obstacles in the subsequent analysis of the data.

  • Spatial Autocorrelation in Mass Spectrometry Imaging.
    Analytical chemistry, 2016
    Co-Authors: Alberto Cassese, Ron M A Heeren, Liam A. Mcdonnell, Arn M. J. M. Van Den Maagdenberg, Shane R. Ellis, Axel Walch, Nina Ogrinc Potočnik, Elke Burgermeister, Matthias P. Ebert, Benjamin Balluff
    Abstract:

    Mass Spectrometry Imaging (MSI) is a powerful molecular Imaging technique. In microprobe MSI, images are created through a grid-wise interrogation of individual spots by Mass Spectrometry across a surface. Classical statistical tests for within-sample comparisons fail as close-by measurement spots violate the assumption of independence of these tests, which can lead to an increased false-discovery rate. For spatial data, this effect is referred to as spatial autocorrelation. In this study, we investigated spatial autocorrelation in three different matrix-assisted laser desorption/ionization MSI data sets. These data sets cover different molecular classes (metabolites/drugs, lipids, and proteins) and different spatial resolutions ranging from 20 to 100 μm. Significant spatial autocorrelation was detected in all three data sets and found to increase with decreasing pixel size. To enable statistical testing for differences in Mass signal intensities between regions of interest within MSI data sets, we propos...

  • Automatic Generic Registration of Mass Spectrometry Imaging Data to Histology Using Nonlinear Stochastic Embedding
    Analytical chemistry, 2014
    Co-Authors: Walid M. Abdelmoula, Benjamin Balluff, Karolina Škrášková, Ricardo J. Carreira, Else A. Tolner, Boudewijn P. F. Lelieveldt, Laurens Van Der Maaten, Hans Morreau, Arn M. J. M. Van Den Maagdenberg, Ron M A Heeren
    Abstract:

    The combination of Mass Spectrometry Imaging and histology has proven a powerful approach for obtaining molecular signatures from specific cells/tissues of interest, whether to identify biomolecular changes associated with specific histopathological entities or to determine the amount of a drug in specific organs/compartments. Currently there is no software that is able to explicitly register Mass Spectrometry Imaging data spanning different ionization techniques or Mass analyzers. Accordingly, the full capabilities of Mass Spectrometry Imaging are at present underexploited. Here we present a fully automated generic approach for registering Mass Spectrometry Imaging data to histology and demonstrate its capabilities for multiple Mass analyzers, multiple ionization sources, and multiple tissue types.

  • Automatic Registration of Mass Spectrometry Imaging Data Sets to the Allen Brain Atlas
    Analytical chemistry, 2014
    Co-Authors: Walid M. Abdelmoula, Benjamin Balluff, Liam A. Mcdonnell, Ricardo J. Carreira, Else A. Tolner, Boudewijn P. F. Lelieveldt, Arn M. J. M. Van Den Maagdenberg, René J. M. Van Zeijl, Reinald Shyti, Jouke Dijkstra
    Abstract:

    Mass Spectrometry Imaging holds great potential for understanding the molecular basis of neurological disease. Several key studies have demonstrated its ability to uncover disease-related biomolecular changes in rodent models of disease, even if highly localized or invisible to established histological methods. The high analytical reproducibility necessary for the biomedical application of Mass Spectrometry Imaging means it is widely developed in Mass Spectrometry laboratories. However, many lack the expertise to correctly annotate the complex anatomy of brain tissue, or have the capacity to analyze the number of animals required in preclinical studies, especially considering the significant variability in sizes of brain regions. To address this issue, we have developed a pipeline to automatically map Mass Spectrometry Imaging data sets of mouse brains to the Allen Brain Reference Atlas, which contains publically available data combining gene expression with brain anatomical locations. Our pipeline enable...

Alain Brunelle - One of the best experts on this subject based on the ideXlab platform.

  • Mass Spectrometry Imaging of biological tissue: an approach for multicenter studies
    Analytical and Bioanalytical Chemistry, 2015
    Co-Authors: Andreas Römpp, Bernhard Spengler, Alain Brunelle, Olivier Laprévote, Jean-pierre Both, Ron Heeren, Brendan Prideaux, Alexandre Seyer, Markus Stoeckli, Donald Smith
    Abstract:

    Mass Spectrometry Imaging has become a popular tool for probing the chemical complexity of biological surfaces. This led to the development of a wide range of instrumentation and preparation protocols. It is thus desirable to evaluate and compare the data output from different methodologies and Mass spectrometers. Here, we present an approach for the comparison of Mass Spectrometry Imaging data from different laboratories (often referred to as multicenter studies). This is exemplified by the analysis of mouse brain sections in five laboratories in Europe and the USA. The instrumentation includes matrix-assisted laser desorption/ionization (MALDI)-time-of-flight (TOF), MALDI-QTOF, MALDI-Fourier transform ion cyclotron resonance (FTICR), atmospheric-pressure (AP)-MALDI-Orbitrap, and cluster TOF-secondary ion Mass Spectrometry (SIMS). Experimental parameters such as measurement speed, Imaging bin width, and Mass spectrometric parameters are discussed. All datasets were converted to the standard data format imzML and displayed in a common open-source software with identical parameters for visualization, which facilitates direct comparison of MS images. The imzML conversion also allowed exchange of fully functional MS Imaging datasets between the different laboratories. The experiments ranged from overview measurements of the full mouse brain to detailed analysis of smaller features (depending on spatial resolution settings), but common histological features such as the corpus callosum were visible in all measurements. High spatial resolution measurements of AP-MALDI-Orbitrap and TOF-SIMS showed comparable structures in the low-micrometer range. We discuss general considerations for planning and performing multicenter studies in Mass Spectrometry Imaging. This includes details on the selection, distribution, and preparation of tissue samples as well as on data handling. Such multicenter studies in combination with ongoing activities for reporting guidelines, a common data format (imzML) and a public data repository can contribute to more reliability and transparency of MS Imaging studies.

  • Micrometric molecular histology of lipids by Mass Spectrometry Imaging
    Current opinion in chemical biology, 2011
    Co-Authors: David Touboul, Olivier Laprévote, Alain Brunelle
    Abstract:

    Time-Of-Flight Secondary Ion Mass Spectrometry is compared to other Mass Spectrometry Imaging techniques, and recent improvements of the experimental methods, driven by biological and biomedical applications, are described and discussed. This review shows that this method that can be considered as a micrometric molecular histology is particularly efficient for obtaining images of various lipid species at the surface of a tissue sample, without sample preparation, and with a routine spatial resolution of 1μm or less.

  • Localization of Flavonoids in Seeds by Cluster Time-of-Flight Secondary Ion Mass Spectrometry Imaging
    Analytical chemistry, 2010
    Co-Authors: Alexandre Seyer, Alain Brunelle, Jacques Einhorn, Olivier Laprévote
    Abstract:

    Time-of-flight secondary ion Mass Spectrometry Imaging has been used to map flavonoids in fresh seed sections of peas (Pisum sativum) and Arabidopsis thaliana. While for peas a very simple preparation method derived from mammalian tissue Imaging could be utilized, several preparation methods had to be tested for the A. thaliana seeds before obtaining tissue sections on which the diagnostic ions were not delocalized. For such small and stiff biological material, none of the methods currently used in histology or scanning electron microscopy could be transferred to Mass Spectrometry Imaging. Only the embedding of the fresh seeds in a polyester resin, followed by the analysis of the block after having obtained a flat surface section with a diamond blade, gave sensitive and reproducible results. Several flavonoid ions have been detected in the sections, showing increased concentrations of flavonoids in the seed coats. The method was finally applied to confirm the variations in the flavonoid content of seeds f...

  • Localization of Flavonoids in Seeds by Cluster Time-of-Flight Secondary Ion Mass Spectrometry Imaging.
    Analytical Chemistry, 2010
    Co-Authors: Alexandre Seyer, Alain Brunelle, Jacques Einhorn, Olivier Laprévote
    Abstract:

    Time-of-flight secondary ion Mass Spectrometry Imaging has been used to map flavonoids in fresh seed sections of peas ( Pisum sativum ) and Arabidopsis thaliana . While for peas a very simple preparation method derived from mammalian tissue Imaging could be utilized, several preparation methods had to be tested for the A. thaliana seeds before obtaining tissue sections on which the diagnostic ions were not delocalized. For such small and stiff biological material, none of the methods currently used in histology or scanning electron microscopy could be transferred to Mass Spectrometry Imaging. Only the embedding of the fresh seeds in a polyester resin, followed by the analysis of the block after having obtained a flat surface section with a diamond blade, gave sensitive and reproducible results. Several flavonoid ions have been detected in the sections, showing increased concentrations of flavonoids in the seed coats. The method was finally applied to confirm the variations in the flavonoid content of seeds from different A. thaliana mutants.

  • In situ primary metabolites localization on a rat brain section by chemical Mass Spectrometry Imaging
    Analytical Chemistry, 2009
    Co-Authors: Farida Benabdellah, David Touboul, Alain Brunelle, Olivier Laprévote
    Abstract:

    We describe here the detection and identification of 13 primary metabolites (AMP, ADP, ATP, UDP-GlcNAc, ...) directly from rat brain sections by chemical Mass Spectrometry Imaging. Matrix-assisted laser desorption/ionization tandem Mass Spectrometry (MALDI-MS/MS) was combined with 9-aminoacridine as a powerful matrix. We also demonstrate that a new robotic sprayer allows us to homogeneously coat the surface with the matrix, enabling the acquisition of chemical images at a 50 microm resolution, leading us to precisely and simultaneously localize each metabolite over the tissue surface. These experiments open a new field of investigation for chemical Mass Spectrometry Imaging and are of great interest for both chemists and biologists.

Josephine Bunch - One of the best experts on this subject based on the ideXlab platform.

  • Direct Tissue Mass Spectrometry Imaging by Atmospheric Pressure UV-Laser Desorption Plasma Postionization.
    Journal of the American Society for Mass Spectrometry, 2020
    Co-Authors: Bin Yan, Teresa Murta, Efstathios A. Elia, Rory T. Steven, Josephine Bunch
    Abstract:

    Matrix-assisted laser desorption ionization (MALDI) operated at atmospheric pressure has been shown to be a promising technique for Mass Spectrometry Imaging of biological tissues at high spatial r...

  • Exploring Ion Suppression in Mass Spectrometry Imaging of a Heterogeneous Tissue
    Analytical chemistry, 2018
    Co-Authors: Adam J. Taylor, Alex Dexter, Josephine Bunch
    Abstract:

    In this study we have explored several aspects of regional analyte suppression in Mass Spectrometry Imaging (MSI) of a heterogeneous sample, transverse cryosections of mouse brain. Olanzapine was homogeneously coated across the section prior to desorption electrospray ionization (DESI) and matrix-assisted laser desorption ionization (MALDI) Mass Spectrometry Imaging. We employed the concept of a tissue extinction coefficient (TEC) to assess suppression of an analyte on tissue relative to its intensity in an off tissue region. We expanded the use of TEC, by first segmenting anatomical regions using graph-cuts clustering and calculating a TEC for each cluster. The single ion image of the olanzapine [M + H]+ ion was seen to vary considerably across the image, with anatomical features such as the white matter and hippocampus visible. While trends in regional ion suppression were conserved across MSI modalities, significant changes in the magnitude of relative regional suppression effects between techniques we...

  • testing for multivariate normality in Mass Spectrometry Imaging data a robust statistical approach for clustering evaluation and the generation of synthetic Mass Spectrometry Imaging data sets
    Analytical Chemistry, 2016
    Co-Authors: Alex Dexter, Alan M Race, Iain B Styles, Josephine Bunch
    Abstract:

    Spatial clustering is a powerful tool in Mass Spectrometry Imaging (MSI) and has been demonstrated to be capable of differentiating tumor types, visualizing intratumor heterogeneity, and segmenting anatomical structures. Several clustering methods have been applied to Mass Spectrometry Imaging data, but a principled comparison and evaluation of different clustering techniques presents a significant challenge. We propose that testing whether the data has a multivariate normal distribution within clusters can be used to evaluate the performance when using algorithms that assume normality in the data, such as k-means clustering. In cases where clustering has been performed using the cosine distance, conversion of the data to polar coordinates prior to normality testing should be performed to ensure normality is tested in the correct coordinate system. In addition to these evaluations of internal consistency, we demonstrate that the multivariate normal distribution can then be used as a basis for statistical ...

  • The Use of Random Projections for the Analysis of Mass Spectrometry Imaging Data
    Journal of the American Society for Mass Spectrometry, 2014
    Co-Authors: Andrew Palmer, Josephine Bunch, Iain B Styles
    Abstract:

    The ‘curse of dimensionality’ imposes fundamental limits on the analysis of the large, information rich datasets that are produced by Mass Spectrometry Imaging. Additionally, such datasets are often too large to be analyzed as a whole and so dimensionality reduction is required before further analysis can be performed. We investigate the use of simple random projections for the dimensionality reduction of Mass Spectrometry Imaging data and examine how they enable efficient and fast segmentation using k-means clustering. The method is computationally efficient and can be implemented such that only one spectrum is needed in memory at any time. We use this technique to reveal histologically significant regions within MALDI images of diseased human liver. Segmentation results achieved following a reduction in the dimensionality of the data by more than 99% (without peak picking) showed that histologic changes due to disease can be automatically visualized from molecular images.