A systems biology approach for pathway level analysis.

By Sorin Draghici, Purvesh Khatri, Adi L. Tarca, Kashyap Amin, A. Done, Calin Voichita, C. Georgescu, R. Romero. 2007

1,220 citations recorded by the source corpus.

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).

Subfields: Computational Theory and Mathematics, Molecular Biology

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Citations in the corpus

A novel signaling pathway impact analysis (2009, background): “Conversely, if several genes are involved in a pathway but they only appear somewhere downstream, changes in their expression levels may not affect the given pathway as much.”
Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis (2016, methodology): “Among them, group-based significance tests and pathway analysis methods have gained widespread acceptance among many researchers involved in “omics” data analysis (Goeman et al., 2004; Subramanian et al., 2005; Draghici et al., 2007; Efron and Tibshirani, 2007; Goffard and Weiller, 2007).”
The bacterial signal indole increases epithelial-cell tight-junction resistance and attenuates indicators of inflammation (2009, methodology): “01) in expression relative to untreated controls were used to populate the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways with the Pathway Express software (19).”
miRSystem: An Integrated System for Characterizing Enriched Functions and Pathways of MicroRNA Targets (2012, background): “Yet, one major limitation in these algorithms is that the raw expression values of each gene are only used to identify the ranking or statistical differences among them [21].”
NetPath: a public resource of curated signal transduction pathways (2010, background): “A novel approach has been recently reported to measure the biological impact of perturbation of pathways in genomewide gene expression experiments [48].”
PathNet: a tool for pathway analysis using topological information (2012, positive): “More recently, some studies [7-9] have included such topological information for calculating enrichment of signaling pathways, by assigning different weights to genes based on their location in the pathway.”
Big Data Analytics in Healthcare (2015, methodology): “Pathway-Express [148] is an example of a third generation tool that combines the knowledge of differentially expressed genes with biologically meaningful changes on a given pathway to perform pathway analysis.”
Using MetaboAnalyst 4.0 for Comprehensive and Integrative Metabolomics Data Analysis (2019, methodology): “…significance tests and pathway analysis methods have gained widespread acceptance among many researchers involved in “omics” data analysis (Draghici et al., 2007; Efron & Tibshirani, 2007; Goeman, van de Geer, de Kort, & van Houwelingen, 2004; Goffard & Weiller, 2007; Subramanian et…”
MetPA: a web-based metabolomics tool for pathway analysis and visualization (2010, background): “Availability: Freely available at http://metpa.metabolomics.ca Contact: david.wishart@ualberta.ca Received on May 17, 2010; revised on June 22, 2010; accepted on July 8, 2010”
Ten Years of Pathway Analysis: Current Approaches and Outstanding Challenges (2012, methodology): “For example, IF analysis models each pathway as a linear system and propagates changes in gene expression as perturbations in the system via interactions between gene products [38–40 , 43 ].”