Statistical methods for analyzing immunosignatures. 2011

Justin R Brown, and Phillip Stafford, and Stephen A Johnston, and Valentin Dinu
Department of Biomedical Informatics, Arizona State University, Mayo Clinic - Samuel C, Johnson Research Bldg, 13212 East Shea Boulevard, Scottsdale, AZ 85259, USA. jrbrown2@asu.edu

BACKGROUND Immunosignaturing is a new peptide microarray based technology for profiling of humoral immune responses. Despite new challenges, immunosignaturing gives us the opportunity to explore new and fundamentally different research questions. In addition to classifying samples based on disease status, the complex patterns and latent factors underlying immunosignatures, which we attempt to model, may have a diverse range of applications. METHODS We investigate the utility of a number of statistical methods to determine model performance and address challenges inherent in analyzing immunosignatures. Some of these methods include exploratory and confirmatory factor analyses, classical significance testing, structural equation and mixture modeling. RESULTS We demonstrate an ability to classify samples based on disease status and show that immunosignaturing is a very promising technology for screening and presymptomatic screening of disease. In addition, we are able to model complex patterns and latent factors underlying immunosignatures. These latent factors may serve as biomarkers for disease and may play a key role in a bioinformatic method for antibody discovery. CONCLUSIONS Based on this research, we lay out an analytic framework illustrating how immunosignatures may be useful as a general method for screening and presymptomatic screening of disease as well as antibody discovery.

UI MeSH Term Description Entries
D009369 Neoplasms New abnormal growth of tissue. Malignant neoplasms show a greater degree of anaplasia and have the properties of invasion and metastasis, compared to benign neoplasms. Benign Neoplasm,Cancer,Malignant Neoplasm,Tumor,Tumors,Benign Neoplasms,Malignancy,Malignant Neoplasms,Neoplasia,Neoplasm,Neoplasms, Benign,Cancers,Malignancies,Neoplasias,Neoplasm, Benign,Neoplasm, Malignant,Neoplasms, Malignant
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000906 Antibodies Immunoglobulin molecules having a specific amino acid sequence by virtue of which they interact only with the ANTIGEN (or a very similar shape) that induced their synthesis in cells of the lymphoid series (especially PLASMA CELLS).
D015233 Models, Statistical Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc. Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D019151 Peptide Library A collection of cloned peptides, or chemically synthesized peptides, frequently consisting of all possible combinations of amino acids making up an n-amino acid peptide. Phage Display Peptide Library,Random Peptide Library,Peptide Phage Display Library,Phage Display Library, Peptide,Synthetic Peptide Combinatorial Library,Synthetic Peptide Library,Libraries, Peptide,Libraries, Random Peptide,Libraries, Synthetic Peptide,Library, Peptide,Library, Random Peptide,Library, Synthetic Peptide,Peptide Libraries,Peptide Libraries, Random,Peptide Libraries, Synthetic,Peptide Library, Random,Peptide Library, Synthetic,Random Peptide Libraries,Synthetic Peptide Libraries
D040081 Protein Array Analysis Ligand-binding assays that measure protein-protein, protein-small molecule, or protein-nucleic acid interactions using a very large set of capturing molecules, i.e., those attached separately on a solid support, to measure the presence or interaction of target molecules in the sample. Protein Chips,Protein Microarrays,Protein Microchips,Protein Profiling Chips,Protein Array Assay,Protein Arrays,Protein Biochips,Protein Microarray Analysis,Protein Microarray Assay,Protein Profiling Microarrays,ProteinChip,Analyses, Protein Array,Analyses, Protein Microarray,Analysis, Protein Array,Analysis, Protein Microarray,Array Analyses, Protein,Array Analysis, Protein,Array Assay, Protein,Array Assays, Protein,Array, Protein,Arrays, Protein,Assay, Protein Array,Assay, Protein Microarray,Assays, Protein Array,Assays, Protein Microarray,Biochip, Protein,Biochips, Protein,Chip, Protein,Chip, Protein Profiling,Chips, Protein,Chips, Protein Profiling,Microarray Analyses, Protein,Microarray Analysis, Protein,Microarray Assay, Protein,Microarray Assays, Protein,Microarray, Protein,Microarray, Protein Profiling,Microarrays, Protein,Microarrays, Protein Profiling,Microchip, Protein,Microchips, Protein,Profiling Chip, Protein,Profiling Chips, Protein,Profiling Microarray, Protein,Profiling Microarrays, Protein,Protein Array,Protein Array Analyses,Protein Array Assays,Protein Biochip,Protein Chip,Protein Microarray,Protein Microarray Analyses,Protein Microarray Assays,Protein Microchip,Protein Profiling Chip,Protein Profiling Microarray,ProteinChips

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