Minimum Information about a Genotyping Experiment (MIGEN). Issue 2 (September 2011)

• Record Type: Journal Article
• Authors: Huang, Jie; Mirel, Daniel; Pugh, Elizabeth; Xing, Chao; Robinson, Peter; Pertsemlidis, Alexander; Ding, LiangHao; Kozlitina, Julia; Maher, Joseph; Rios, Jonathan; Story, Michael; Marthandan, Nishanth; Scheuermann, Richard
• Is Part Of: Standards in genomic sciences. Volume 5:Issue 2(2011)
• Page Start: 224
• Page End: 229
• Publication Date: 2011-09
• Subjects: Genomics -- Periodicals; Genomics -- Periodicals; Genomics; Periodicals; 572.8605
• DOI: 10.4056/sigs.1994602
• Languages: English
• ISSNs: 1944-3277

Abstract

Abstract Genotyping experiments are widely used in clinical and basic research laboratories to identify associations between genetic variations and normal/abnormal phenotypes. Genotyping assay techniques vary from single genomic regions that are interrogated using PCR reactions to high throughput assays examining genome-wide sequence and structural variation. The resulting genotype data may include millions of markers of thousands of individuals, requiring various statistical, modeling or other data analysis methodologies to interpret the results. To date, there are no standards for reporting genotyping experiments. Here we present theM inimumI nformation about aGen otyping Experiment (MIGen) standard, defining the minimum information required for reporting genotyping experiments. MIGen standard covers experimental design, subject description, genotyping procedure, quality control and data analysis. MIGen is a registered project under MIBBI (Minimum Information for Biological and Biomedical Investigations) and is being developed by an interdisciplinary group of experts in basic biomedical science, clinical science, biostatistics and bioinformatics. To accommodate the wide variety of techniques and methodologies applied in current and future genotyping experiment, MIGen leverages foundational concepts from the Ontology for Biomedical Investigations (OBI) for the description of the various types of planned processes and implements a hierarchical document structure. The adoption of MIGen by the research community will facilitate consistent genotyping data interpretation and independent data validation. MIGen can also serve as a framework for the development of data models for capturing and storing genotyping results and experiment metadata in a structured way, to facilitate the exchange of metadata.