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Related Experiment Videos

The Shivplot: a graphical display for trend elucidation and exploratory analysis of microarray data.

Owen Z Woody1, Robert Nadon

  • 1McGill University and Genome Quebec Innovation Centre, 740 avenue du Docteur Penfield, Montreal, Quebec, H3A 1A4, Canada. owoody@uwaterloo.ca

Source Code for Biology and Medicine
|December 7, 2006
PubMed
Summary
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A new graphical tool called the shivplot integrates boxplots, density plots, and variability plots for high-throughput data analysis. This efficient visualization aids in assessing data quality and communicating experimental results from complex biological experiments.

Area of Science:

  • Life Sciences
  • Bioinformatics
  • Genomics

Background:

  • High-throughput systems generate complex, large-scale data.
  • Effective data analysis requires specialized graphical tools for quality assessment.
  • Interpretability and efficiency are key for data visualization utility.

Purpose of the Study:

  • To introduce the shivplot, a novel graphical technique.
  • To provide an efficient method for visualizing high-throughput data.
  • To enhance data quality assessment and interpretation.

Main Methods:

  • Developed the shivplot, a graphical technique.
  • Integrated boxplots, distribution density plots, and variability vs. intensity plots.
  • Applied the shivplot to replicated high-throughput datasets, including microarrays.

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Main Results:

  • The shivplot combines three established plotting graphics into a single representation.
  • Demonstrated utility with microarray data sets.
  • The plot retains information from individual plots while conserving space and minimizing redundancy.

Conclusions:

  • The shivplot effectively highlights data features difficult to discern from individual plots.
  • Recommended for exploratory data analysis in high-throughput studies.
  • Suitable for communicating experimental data in scientific publications.