A systems biology approach for pathway level analysis

  1. Sorin Draghici1,2,4,
  2. Purvesh Khatri2,
  3. Adi Laurentiu Tarca1,2,3,
  4. Kashyap Amin2,
  5. Arina Done2,
  6. Calin Voichita2,
  7. Constantin Georgescu2, and
  8. Roberto Romero3
  1. 1 Karmanos Cancer Institute, Wayne State University, Detroit, Michigan 48202, USA;
  2. 2 Department of Computer Science, Wayne State University, Detroit, Michigan 48202, USA;
  3. 3 Perinatology Research Branch, NIH/NICHD, Detroit, Michigan 48201, USA

Abstract

A common challenge in the analysis of genomics data is trying to understand the underlying phenomenon in the context of all complex interactions taking place on various signaling pathways. A statistical approach using various models is universally used to identify the most relevant pathways in a given experiment. Here, we show that the existing pathway analysis methods fail to take into consideration important biological aspects and may provide incorrect results in certain situations. By using a systems biology approach, we developed an impact analysis that includes the classical statistics but also considers other crucial factors such as the magnitude of each gene’s expression change, their type and position in the given pathways, their interactions, etc. The impact analysis is an attempt to a deeper level of statistical analysis, informed by more pathway-specific biology than the existing techniques. On several illustrative data sets, the classical analysis produces both false positives and false negatives, while the impact analysis provides biologically meaningful results. This analysis method has been implemented as a Web-based tool, Pathway-Express, freely available as part of the Onto-Tools (http://vortex.cs.wayne.edu).

Footnotes

  • 4 Corresponding author.

    4 E-mail sod{at}cs.wayne.edu; fax (313) 577-0868.

  • [Supplemental material is available online at www.genome.org.]

  • Article published online before print. Article and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.6202607

    • Received December 11, 2006.
    • Accepted June 28, 2007.
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