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iCOSSY: An Online Tool for Context-Specific Subnetwork Discovery from Gene Expression Data.

Saha A, Jeon M, Tan AC, Kang J - PLoS ONE (2015)

Bottom Line: Users can upload their gene expression datasets, and discover important subnetworks of closely interacting molecules to differentiate between two phenotypes (context).They can also interactively visualize the resulting subnetworks. iCOSSY is a web server that finds subnetworks that are differentially expressed in two phenotypes.Users can visualize the subnetworks to understand the biology of the difference.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Engineering, Korea University, Seoul, Korea.

ABSTRACT
Pathway analyses help reveal underlying molecular mechanisms of complex biological phenotypes. Biologists tend to perform multiple pathway analyses on the same dataset, as there is no single answer. It is often inefficient for them to implement and/or install all the algorithms by themselves. Online tools can help the community in this regard. Here we present an online gene expression analytical tool called iCOSSY which implements a novel pathway-based COntext-specific Subnetwork discoverY (COSSY) algorithm. iCOSSY also includes a few modifications of COSSY to increase its reliability and interpretability. Users can upload their gene expression datasets, and discover important subnetworks of closely interacting molecules to differentiate between two phenotypes (context). They can also interactively visualize the resulting subnetworks. iCOSSY is a web server that finds subnetworks that are differentially expressed in two phenotypes. Users can visualize the subnetworks to understand the biology of the difference.

No MeSH data available.


Related in: MedlinePlus

Subnetwork visualization.A top MIS in the leukemia dataset. Red and green colored nodes represent over- and under-expressed genes, respectively.
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pone.0131656.g001: Subnetwork visualization.A top MIS in the leukemia dataset. Red and green colored nodes represent over- and under-expressed genes, respectively.

Mentions: Last, we implemented a new visualization interface for iCOSSY, and developed an automatic approach that “stitches” different MISs together to form a new hypothesis for down-stream analysis and validation. iCOSSY visualizes the analysis results as a network where nodes and edges represent genes and interactions, respectively. It allows users to intuitively interpret the results. Differentially expressed genes are represented as red (high) or green (low) nodes. As a default, iCOSSY shows the top MIS result in the web interface (Fig 1). As illustrated in Fig 1, there are checkboxes, on the right side of iCOSSY’s web interface, for customizing the results. Using them, users can view different top MIS results. The lower checkbox allows users to stitch multiple MISs together. To stitch subnetworks together, iCOSSY uses the molecular interaction network that the user chose in the beginning (e.g., KEGG, STRING or Pathway API). If two isolated subnetworks can be linked by extra edges, iCOSSY adds them and provides one large network. Otherwise, iCOSSY searches the shortest paths between each pair of genes from each subnetwork based on the molecular interaction network. The shortest paths are ordered by the lengths of the paths, fold differences, and the PageRank scores of the nodes in the paths. Then, we add a few top paths and link the subnetworks. The length of the shortest path is 4 at most.


iCOSSY: An Online Tool for Context-Specific Subnetwork Discovery from Gene Expression Data.

Saha A, Jeon M, Tan AC, Kang J - PLoS ONE (2015)

Subnetwork visualization.A top MIS in the leukemia dataset. Red and green colored nodes represent over- and under-expressed genes, respectively.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4492968&req=5

pone.0131656.g001: Subnetwork visualization.A top MIS in the leukemia dataset. Red and green colored nodes represent over- and under-expressed genes, respectively.
Mentions: Last, we implemented a new visualization interface for iCOSSY, and developed an automatic approach that “stitches” different MISs together to form a new hypothesis for down-stream analysis and validation. iCOSSY visualizes the analysis results as a network where nodes and edges represent genes and interactions, respectively. It allows users to intuitively interpret the results. Differentially expressed genes are represented as red (high) or green (low) nodes. As a default, iCOSSY shows the top MIS result in the web interface (Fig 1). As illustrated in Fig 1, there are checkboxes, on the right side of iCOSSY’s web interface, for customizing the results. Using them, users can view different top MIS results. The lower checkbox allows users to stitch multiple MISs together. To stitch subnetworks together, iCOSSY uses the molecular interaction network that the user chose in the beginning (e.g., KEGG, STRING or Pathway API). If two isolated subnetworks can be linked by extra edges, iCOSSY adds them and provides one large network. Otherwise, iCOSSY searches the shortest paths between each pair of genes from each subnetwork based on the molecular interaction network. The shortest paths are ordered by the lengths of the paths, fold differences, and the PageRank scores of the nodes in the paths. Then, we add a few top paths and link the subnetworks. The length of the shortest path is 4 at most.

Bottom Line: Users can upload their gene expression datasets, and discover important subnetworks of closely interacting molecules to differentiate between two phenotypes (context).They can also interactively visualize the resulting subnetworks. iCOSSY is a web server that finds subnetworks that are differentially expressed in two phenotypes.Users can visualize the subnetworks to understand the biology of the difference.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Engineering, Korea University, Seoul, Korea.

ABSTRACT
Pathway analyses help reveal underlying molecular mechanisms of complex biological phenotypes. Biologists tend to perform multiple pathway analyses on the same dataset, as there is no single answer. It is often inefficient for them to implement and/or install all the algorithms by themselves. Online tools can help the community in this regard. Here we present an online gene expression analytical tool called iCOSSY which implements a novel pathway-based COntext-specific Subnetwork discoverY (COSSY) algorithm. iCOSSY also includes a few modifications of COSSY to increase its reliability and interpretability. Users can upload their gene expression datasets, and discover important subnetworks of closely interacting molecules to differentiate between two phenotypes (context). They can also interactively visualize the resulting subnetworks. iCOSSY is a web server that finds subnetworks that are differentially expressed in two phenotypes. Users can visualize the subnetworks to understand the biology of the difference.

No MeSH data available.


Related in: MedlinePlus