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Protein Microarray for Disease Analysis

Volume 723 of the series Methods in Molecular Biology pp 337-347

Date:

Data Processing and Analysis for Protein Microarrays

  • David S. DeLucaAffiliated withCancer Vaccine Center, Department of Medical Oncology, Dana-Farber Cancer Institute
  • , Ovidiu MarinaAffiliated withDepartment of Radiation Oncology, William Beaumont Hospital
  • , Surajit RayAffiliated withDepartment of Mathematics and Statistics, Boston University
  • , Guang Lan ZhangAffiliated withCancer Vaccine Center, Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School Email author 
  • , Catherine J. WuAffiliated withDivision of Hematologic Neoplasia, Department of Medical Oncology, Cancer Vaccine Center, Dana-Farber Cancer Institute
  • , Vladimir BrusicAffiliated withCancer Vaccine Center, Department of Medical Oncology, Dana-Farber Cancer Institute

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Abstract

Protein microarrays are a high-throughput technology capable of generating large quantities of proteomics data. They can be used for general research or for clinical diagnostics. Bioinformatics and statistical analysis techniques are required for interpretation and reaching biologically relevant conclusions from raw data. We describe essential algorithms for processing protein microarray data, including spot-finding on slide images, Z score, and significance analysis of microarrays (SAM) calculations, as well as the concentration dependent analysis (CDA). We also describe available tools for protein microarray analysis, and provide a template for a step-by-step approach to performing an analysis centered on the CDA method. We conclude with a discussion of fundamental and practical issues and considerations.

Key words

Protein microarray Concentration dependent analysis Z score Differential expression analysis Bioinformatics