title: MARK-AGE data management: Cleaning, exploration and visualization of data.
abstract: Databases are an organized collection of data and necessary to investigate a wide spectrum of research questions. For data evaluation analyzers should be aware of possible data quality problems that can compromise results validity. Therefore data cleaning is an essential part of the data management process, which deals with the identification and correction of errors in order to improve data quality. In our cross-sectional study, biomarkers of ageing, analytical, anthropometric and demographic data from about 3000 volunteers have been collected in the MARK-AGE database. Although several preventive strategies were applied before data entry, errors like miscoding, missing values, batch problems etc., could not be avoided completely. Such errors can result in misleading information and affect the validity of the performed data analysis. Here we present an overview of the methods we applied for dealing with errors in the MARK-AGE database. We especially describe our strategies for the detection of missing values, outliers and batch effects and explain how they can be handled to improve data quality. Finally we report about the tools used for data exploration and data sharing between MARK-AGE collaborators.
authors.affiliation: Chair for Molecular Toxicology, University of Konstanz, 78457 Konstanz, Germany.
authors.forename: Jennifer
authors.initials: J
authors.lastname: Baur
authors.affiliation: Chair for Molecular Toxicology, University of Konstanz, 78457 Konstanz, Germany.
authors.forename: Maria
authors.initials: M
authors.lastname: Moreno-Villanueva
authors.affiliation: Chair for Bioinformatics and Information Mining, University of Konstanz, 78457 Konstanz, Germany.
authors.forename: Tobias
authors.initials: T
authors.lastname: Kötter
authors.affiliation: Chair for Molecular Toxicology, University of Konstanz, 78457 Konstanz, Germany.
authors.forename: Thilo
authors.initials: T
authors.lastname: Sindlinger
authors.affiliation: Chair for Molecular Toxicology, University of Konstanz, 78457 Konstanz, Germany. Electronic address: alexander.buerkle@uni-konstanz.de.
authors.forename: Alexander
authors.initials: A
authors.lastname: Bürkle
authors.affiliation: Chair for Bioinformatics and Information Mining, University of Konstanz, 78457 Konstanz, Germany.
authors.forename: Michael R
authors.initials: MR
authors.lastname: Berthold
authors.affiliation: Department for Mathematics and Statistics,University of Konstanz, 78457 Konstanz, Germany.
authors.forename: Michael
authors.initials: M
authors.lastname: Junk
mesh_terms: D000375:Aging / Q000378:metabolism*; D015415:Biomarkers / Q000378:metabolism; D003628:Database Management Systems; D016208:Databases, Factual; D005260:Female; D006801:Humans; D008297:Male
chemical_list: D015415:Biomarkers
keywords: Batch effects; Data cleaning; Data visualization; Missing data; Outliers