Sanjay Agravat

The minimum information required for a glycomics experiment (MIRAGE) project: improving the standards for reporting mass-spectrometry-based glycoanalytic data.

The MIRAGE guidelines are being developed in response to a critical need in the glycobiology community to clarify glycoanalytic results so that they are more readily evaluated (in terms of their scope and depth) and to facilitate the reproduction of important results in the laboratory. The molecular and biological complexity of the glycosylation process makes thorough reporting of the results of a glycomics experiment a highly challenging endeavor. The resulting data specify the identity and quantity of complex structures, the precise molecular features of which are sometimes inferred using prior knowledge, such as familiarity with a particular biosynthetic mechanism. Specifying the exact methods and assumptions that were used to assign and quantify reported structures allows the interested scientist to appreciate the scope and depth of the analysis. Mass spectrometry (MS) is the most widely used tool for glycomics experiments. The interpretation and reproducibility of MS-based glycomics data depend on comprehensive meta-data describing the instrumentation, instrument setup, and data acquisition protocols. The MIRAGE guidelines for MS-based glycomics have been designed to facilitate the collection and sharing of this critical information in order to assist the glycoanalyst in generating data sets with maximum information content and biological relevance.

MIRAGE: The minimum information required for a glycomics experiment

The MIRAGE (minimum information required for a glycomics experiment) initiative was founded in Seattle, WA, in November 2011 in order to develop guidelines for reporting the qualitative and quantitative results obtained by diverse types of glycomics analyses, including the conditions and techniques that were applied to prepare the glycans for analysis and generate the primary data along with the tools and parameters that were used to process and annotate this data. These guidelines must address a broad range of issues, as glycomics data are inherently complex and are generated using diverse methods, including mass spectrometry (MS), chromatography, glycan array-binding assays, nuclear magnetic resonance (NMR) and other rapidly developing technologies. The acceptance of these guidelines by scientists conducting research on biological systems in which glycans have a significant role will facilitate the evaluation and reproduction of glycomics experiments and data that is reported in scientific journals and uploaded to glycomics databases. As a first step, MIRAGE guidelines for glycan analysis by MS have been recently published (Kolarich D, Rapp E, Struwe WB, Haslam SM, Zaia J., et al. 2013. The minimum information required for a glycomics experiment (MIRAGE) project – Improving the standards for reporting mass spectrometry-based glycoanalytic data. Mol. Cell Proteomics. 12:991–995), allowing them to be implemented and evaluated in the context of real-world glycobiology research. In this paper, we set out the historical context, organization structure and overarching objectives of the MIRAGE initiative.

GlyTouCan 1.0 – The international glycan structure repository

Glycans are known as the third major class of biopolymers, next to DNA and proteins. They cover the surfaces of many cells, serving as the ‘face’ of cells, whereby other biomolecules and viruses interact. The structure of glycans, however, differs greatly from DNA and proteins in that they are branched, as opposed to linear sequences of amino acids or nucleotides. Therefore, the storage of glycan information in databases, let alone their curation, has been a difficult problem. This has caused many duplicated efforts when integration is attempted between different databases, making an international repository for glycan structures, where unique accession numbers are assigned to every identified glycan structure, necessary. As such, an international team of developers and glycobiologists have collaborated to develop this repository, called GlyTouCan and is available at http://glytoucan.org/, to provide a centralized resource for depositing glycan structures, compositions and topologies, and to retrieve accession numbers for each of these registered entries. This will thus enable researchers to reference glycan structures simply by accession number, as opposed to by chemical structure, which has been a burden to integrate glycomics databases in the past.

GlycoPattern: a web platform for glycan array mining

UNLABELLED GlycoPattern is Web-based bioinformatics resource to support the analysis of glycan array data for the Consortium for Functional Glycomics. This resource includes algorithms and tools to discover structural motifs, a heatmap visualization to compare multiple experiments, hierarchical clustering of Glycan Binding Proteins with respect to their binding motifs and a structural search feature on the experimental data. AVAILABILITY AND IMPLEMENTATION GlycoPattern is freely available on the Web at http://glycopattern.emory.edu with all major browsers supported.

The minimum information required for a glycomics experiment (MIRAGE) project: improving the standards for reporting glycan microarray-based data

Abstract MIRAGE (Minimum Information Required for A Glycomics Experiment) is an initiative that was created by experts in the fields of glycobiology, glycoanalytics and glycoinformatics to produce guidelines for reporting results from the diverse types of experiments and analyses used in structural and functional studies of glycans in the scientific literature. As a sequel to the guidelines for sample preparation (Struwe et al. 2016, Glycobiology, 26:907–910) and mass spectrometry data (Kolarich et al. 2013, Mol. Cell Proteomics, 12:991–995), here we present the first version of guidelines intended to improve the standards for reporting data from glycan microarray analyses. For each of eight areas in the workflow of a glycan microarray experiment, we provide guidelines for the minimal information that should be provided in reporting results. We hope that the MIRAGE glycan microarray guidelines proposed here will gain broad acceptance by the community, and will facilitate interpretation and reproducibility of the glycan microarray results with implications in comparison of data from different laboratories and eventual deposition of glycan microarray data in international databases.

Immunogenetic Management Software: a new tool for visualization and analysis of complex immunogenetic datasets

Here we describe the Immunogenetic Management Software (IMS) system, a novel web-based application that permits multiplexed analysis of complex immunogenetic traits that are necessary for the accurate planning and execution of experiments involving large animal models, including nonhuman primates. IMS is capable of housing complex pedigree relationships, microsatellite-based MHC typing data, as well as MHC pyrosequencing expression analysis of class I alleles. It includes a novel, automated MHC haplotype naming algorithm and has accomplished an innovative visualization protocol that allows users to view multiple familial and MHC haplotype relationships through a single, interactive graphical interface. Detailed DNA and RNA-based data can also be queried and analyzed in a highly accessible fashion, and flexible search capabilities allow experimental choices to be made based on multiple, individualized and expandable immunogenetic factors. This web application is implemented in Java, MySQL, Tomcat, and Apache, with supported browsers including Internet Explorer and Firefox on Windows and Safari on Mac OS. The software is freely available for distribution to noncommercial users by contacting Leslie.kean@emory.edu. A demonstration site for the software is available at http://typing.emory.edu/typing_demo, user name: imsdemo7@gmail.com and password: imsdemo.

BSMac: a MATLAB toolbox implementing a Bayesian spatial model for brain activation and connectivity.

We present a statistical and graphical visualization MATLAB toolbox for the analysis of functional magnetic resonance imaging (fMRI) data, called the Bayesian Spatial Model for activation and connectivity (BSMac). BSMac simultaneously performs whole-brain activation analyses at the voxel and region of interest (ROI) levels as well as task-related functional connectivity (FC) analyses using a flexible Bayesian modeling framework (Bowman et al., 2008). BSMac allows for inputting data in either Analyze or Nifti file formats. The user provides information pertaining to subgroup memberships, scanning sessions, and experimental tasks (stimuli), from which the design matrix is constructed. BSMac then performs parameter estimation based on Markov Chain Monte Carlo (MCMC) methods and generates plots for activation and FC, such as interactive 2D maps of voxel and region-level task-related changes in neural activity and animated 3D graphics of the FC results. The toolbox can be downloaded from http://www.sph.emory.edu/bios/CBIS/. We illustrate the BSMac toolbox through an application to an fMRI study of working memory in patients with schizophrenia.