title: Glia Open Access Database (GOAD): A comprehensive gene expression encyclopedia of glia cells in health and disease.
abstract: Recently, the number of genome-wide transcriptome profiles of pure populations of glia cells has drastically increased, resulting in an unprecedented amount of data that offer opportunities to study glia phenotypes and functions in health and disease. To make genome-wide transcriptome data easily accessible, we developed the Glia Open Access Database (GOAD), available via www.goad.education. GOAD contains a collection of previously published and unpublished transcriptome data, including datasets from isolated microglia, astrocytes and oligodendrocytes both at homeostatic and pathological conditions. It contains an intuitive web-based interface that consists of three features that enable searching, browsing, analyzing, and downloading of the data. The first feature is differential gene expression (DE) analysis that provides genes that are significantly up and down-regulated with the associated fold changes and p-values between two conditions of interest. In addition, an interactive Venn diagram is generated to illustrate the overlap and differences between several DE gene lists. The second feature is quantitative gene expression (QE) analysis, to investigate which genes are expressed in a particular glial cell type and to what degree. The third feature is a search utility, which can be used to find a gene of interest and depict its expression in all available expression data sets by generating a gene card. In addition, quality guidelines and relevant concepts for transcriptome analysis are discussed. Finally, GOAD is discussed in relation to several online transcriptome tools developed in neuroscience and immunology. In conclusion, GOAD is a unique platform to facilitate integration of bioinformatics in glia biology.
authors: Medical Physiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
authors: Inge R
authors: IR
authors: Holtman
authors: School for Life Science and Technology, Hanze University of Applied Sciences, Groningen, The Netherlands.
authors: Michiel
authors: M
authors: Noback
authors: School for Life Science and Technology, Hanze University of Applied Sciences, Groningen, The Netherlands.
authors: Marieke
authors: M
authors: Bijlsma
authors: School for Life Science and Technology, Hanze University of Applied Sciences, Groningen, The Netherlands.
authors: Kim N
authors: KN
authors: Duong
authors: School for Life Science and Technology, Hanze University of Applied Sciences, Groningen, The Netherlands.
authors: Marije A
authors: MA
authors: van der Geest
authors: School for Life Science and Technology, Hanze University of Applied Sciences, Groningen, The Netherlands.
authors: Peer T
authors: PT
authors: Ketelaars
authors: Medical Physiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
authors: Nieske
authors: N
authors: Brouwer
authors: Medical Physiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
authors: Ilia D
authors: ID
authors: Vainchtein
authors: Medical Physiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
authors: Bart J L
authors: BJ
authors: Eggen
authors: Medical Physiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
authors: Hendrikus W G M
authors: HW
authors: Boddeke
mesh_terms: D022126:Access to Information; D000818:Animals; D030541:Databases, Genetic; D006801:Humans; D020407:Internet; D009422:Nervous System Diseases / Q000235:genetics / Q000378:metabolism*; D009457:Neuroglia / Q000378:metabolism*; D059467:Transcriptome
keywords: RNA-seq; astrocytes; bioinformatics; microglia; oligodendrocytes; transcriptome analysis