A Suite of Tools for Biologists That Improve Accessibility and Visualization of Large Systems Genetics Datasets: Applications to the Hybrid Mouse Diversity Panel

  • Christoph D. Rau
  • Mete Civelek
  • Calvin Pan
  • Aldons J. Lusis
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1488)

Abstract

In this chapter we address the recent explosion in large multilevel population studies such as the METSIM study in humans as well as large panels of animal models such as the Hybrid Mouse Diversity Panel or the BXD set of recombinant inbred strains. These studies have harnessed the increasing affordability of large-scale high-throughput profiling to gather massive quantities of data. These datasets, spread across different -omics levels (genome, transcriptome, etc.), different tissues (e.g. heart, plasma, bone) and different environmental factors (e.g. diet, drugs) each individually have led to a number of novel findings relevant to a variety of complex diseases and other phenotypes. The analysis of these results, however, is often limited to individuals with a comprehensive understanding of database languages such as SQL. In this chapter, we describe the development of a GUI-based database analysis suite, using the Hybrid Mouse Diversity Panel as an example to lay out a series of methods for visualization and integration of large systems genetics datasets. The database is based on the Shiny suite of tools in R, and is transferrable to other SQL-based datasets.

Key words

Analysis tools in systems genetics GUI-based database analysis suite Multilevel population studies Hybrid mouse diversity panel BxD recombinant inbred strains METSIM in humans 

Supplementary material

333402_1_En_7_MOESM1_ESM.docx (921 kb)
Supplemental Material_9 Figures (DOCX 922 KB)

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Christoph D. Rau
    • 1
  • Mete Civelek
    • 2
  • Calvin Pan
    • 1
  • Aldons J. Lusis
    • 1
  1. 1.Department of Medicine/Division of CardiologyUniversity of CaliforniaLos AngelesUSA
  2. 2.Center for Public Health Genomics, Department of Biomedical EngineeringUniversity of VirginiaCharlottesvilleUSA

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