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DanteR: an extensible R-based tool for quantitative analysis of -omics data.

Tom Taverner1, Yuliya V Karpievitch, Ashoka D Polpitiya

  • 1Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA.

Bioinformatics (Oxford, England)
|July 21, 2012
PubMed
Summary
This summary is machine-generated.

DanteR is a new R package designed for analyzing complex proteomics data. It offers statistical tools for normalization, imputation, and hypothesis testing, enhancing data exploration.

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Area of Science:

  • Proteomics
  • Bioinformatics
  • Computational Biology

Background:

  • Mass spectrometry-based proteomics generates large and complex datasets.
  • Statistical analysis and exploration software are crucial for interpreting these data.

Purpose of the Study:

  • To introduce DanteR, a novel R package for quantitative proteomics data analysis.
  • To provide a user-friendly graphical interface with comprehensive statistical and diagnostic functions.

Main Methods:

  • DanteR is a graphical R package.
  • It includes functions for normalization, imputation, hypothesis testing, and visualization.
  • Users can extend functionality with custom algorithms via an Add-On tab.

Main Results:

  • DanteR offers extensive statistical and diagnostic capabilities for proteomics data.
  • Features include normalization, imputation, hypothesis testing, and interactive visualization.
  • The package supports peptide-to-protein rollup for comprehensive analysis.

Conclusions:

  • DanteR provides a powerful and extensible platform for quantitative proteomics data analysis.
  • Its user-friendly interface and comprehensive functions facilitate deeper insights into complex proteomic datasets.