title: Differential Expression and Functional Analysis of High-Throughput -Omics Data Using Open Source Tools.
abstract: Today, -omics analyses, including the systematic cataloging of messenger RNA and microRNA sequences or DNA methylation patterns in a cell population, organ, or tissue sample, allow for an unbiased, comprehensive genome-level analysis of complex diseases, offering a large advantage over earlier "candidate" gene or pathway analyses. A primary goal in the analysis of these high-throughput assays is the detection of those features among several thousand that differ between different groups of samples. In the context of oral biology, our group has successfully utilized -omics technology to identify key molecules and pathways in different diagnostic entities of periodontal disease.A major issue when inferring biological information from high-throughput -omics studies is the fact that the sheer volume of high-dimensional data generated by contemporary technology is not appropriately analyzed using common statistical methods employed in the biomedical sciences.In this chapter, we outline a robust and well-accepted bioinformatics workflow for the initial analysis of -omics data generated using microarrays or next-generation sequencing technology using open-source tools. Starting with quality control measures and necessary preprocessing steps for data originating from different -omics technologies, we next outline a differential expression analysis pipeline that can be used for data from both microarray and sequencing experiments, and offers the possibility to account for random or fixed effects. Finally, we present an overview of the possibilities for a functional analysis of the obtained data.
authors.affiliation: Department of Periodontology, Operative and Preventive Dentistry, Faculty of Medicine, University of Bonn, Welschnonnenstr. 17, Bonn, D-53111, Germany. moritz.kebschull@uni-bonn.de.|Division of Periodontics, Section of Oral, Diagnostic and Rehabilitation Sciences, Columbia University College of Dental Medicine, New York, NY, USA. moritz.kebschull@uni-bonn.de.
authors.forename: Moritz
authors.initials: M
authors.lastname: Kebschull
authors.affiliation: Department of Periodontology, Operative and Preventive Dentistry, University of Bonn, Welschnonnenstr. 17, Bonn, D-53111, Germany.
authors.forename: Melanie Julia
authors.initials: MJ
authors.lastname: Fittler
authors.affiliation: Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA.
authors.forename: Ryan T
authors.initials: RT
authors.lastname: Demmer
authors.affiliation: Division of Periodontics, Section of Oral, Diagnostic and Rehabilitation Sciences, Columbia University College of Dental Medicine, New York, NY, USA.
authors.forename: Panos N
authors.initials: PN
authors.lastname: Papapanou
mesh_terms: D019295:Computational Biology / Q000379:methods*; D030561:Databases, Nucleic Acid; D020869:Gene Expression Profiling / Q000379:methods; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing; D017423:Sequence Analysis, RNA / Q000379:methods; D012984:Software; D064878:Web Browser
keywords: DNA methylation; Differential expression analysis; Functional groups; Gene expression; Gingiva; Microarray; Next-generation sequencing; Periodontal disease; Transcriptome; microRNA