Abstract
A database can be used to warehouse quantitative trait loci (QTL) data from multiple sources for comparison, genomic data mining, and meta-analysis. A robust database design involves sound data structure logistics, meaningful data transformations, normalization, and proper user interface designs. This chapter starts with a brief review of relational database basics and concentrates on issues associated with curation of QTL data into a relational database, with emphasis on the principles of data normalization and structure optimization. In addition, some simple examples of QTL data mining and meta-analysis are included. These examples are provided to help readers better understand the potential and importance of sound database design.
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Further Reading
Hernandez MJ (2003) Database design for mere mortals: a hands-on guide to relational database design. Addison-Wesley, Reading, MA, USA
Widenius M, Axmark D, Arno K (2002) MySQL reference manual—documentation from the source. O’Reilly Media, O'Reilly Media, Sebastopol, CA, USA
Chang E (2003) Practical perl with CGI applications. Addison Wesley, Reading, MA, USA
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Hu, ZL., Reecy, J.M., Wu, XL. (2012). Design Database for Quantitative Trait Loci (QTL) Data Warehouse, Data Mining, and Meta-Analysis. In: Rifkin, S. (eds) Quantitative Trait Loci (QTL). Methods in Molecular Biology, vol 871. Humana Press. https://doi.org/10.1007/978-1-61779-785-9_7
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DOI: https://doi.org/10.1007/978-1-61779-785-9_7
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