Simple Analysis of Deposited Gene Expression Datasets for the Non-Bioinformatician: How to Use GEO for Fibrosis Research
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Abstract
In the past decade, high-throughput techniques have facilitated the “-omics” research. Transcriptomic study, for instance, has advanced our understanding on the expression landscape of different human diseases and cellular mechanisms. The National Center for Biotechnology Center (NCBI) initialized Genetic Expression Omnibus (GEO) to promote the sharing of transcriptomic data to facilitate biomedical research. In this chapter, we will illustrate how to use GEO to search and analyze the public available transcriptomic data, and we will provide easy to follow protocol for researchers to data mine the powerful resources in GEO to retrieve relevant information that can be valuable for fibrosis research.
Key words
RNA-seq Microarray Transcriptomic GEO Data analysisNotes
Acknowledgments
LCT is supported by the University of Michigan Babcock Endowment Fund, the Dermatology Foundation, National Psoriasis Foundation, and the Arthritis National Research Foundation. The authors acknowledge the support from the Undergraduate Research Opportunity Program from the University of Michigan.
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