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. 2007 Jul;35(Web Server issue):W206-11.
doi: 10.1093/nar/gkm327. Epub 2007 Jun 21.

Onto-Tools: new additions and improvements in 2006

Purvesh Khatri  1 , Calin Voichita, Khalid Kattan, Nadeem Ansari, Avani Khatri, Constantin Georgescu, Adi L Tarca, Sorin Draghici
Affiliations

Onto-Tools: new additions and improvements in 2006

Purvesh Khatri et al. Nucleic Acids Res. 2007 Jul.

Abstract

Onto-Tools is a freely available web-accessible software suite, composed of an annotation database and nine complementary data-mining tools. This article describes a new tool, Onto-Express-to-go (OE2GO), as well as some new features implemented in Pathway-Express and Onto-Miner over the past year. Pathway-Express (PE) has been enhanced to identify significantly perturbed pathways in a given condition using the differentially expressed genes in the input. OE2GO is a tool for functional profiling using custom annotations. The development of this tool was aimed at the researchers working with organisms for which annotations are not yet available in the public domain. OE2GO allows researchers to use either annotation data from the Onto-Tools database, or their own custom annotations. By removing the necessity to use any specific database, OE2GO makes the functional profiling available for all organisms, with annotations using any ontology. The Onto-Tools are freely available at http://vortex.cs.wayne.edu/projects.htm.

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Figures

Figure 1.
Figure 1.
OE2GO input interface for using custom annotations. When the user selects ‘my own annotations’, OE2GO allows the user to specify the name of the annotation file in GO format and the ontology file in OBO format. When using custom annotations, OE2GO assumes that the identifiers in the input file are of the same type as those used in the annotations file.
Figure 2.
Figure 2.
An example OBO formatted ontology file that contains a header, a term stanza and a typedef stanza. Each stanza starts with either ‘[Term]’ or ‘[Typedef]’. The header and the stanzas contain a set of tag-value pairs in : format. The complete list of allowed tags for each type of stanza and the header are described on GO web site.
Figure 3.
Figure 3.
Pathway-Express advanced options. Pathway-Express allows the users to choose advanced options such as the distribution to use for calculating significance of pathways, the type of correction to apply for multiple hypotheses, whether to use P-values or corrected P-values for calculating impact factor, etc. It also allows a user to specify different weights for different types of interactions (e.g. activation, binding, repression, phosphorylation, etc.) between genes on the pathways.
Figure 4.
Figure 4.
Pathway-Express output. PE output is organized in four panels. Panel A summarizes the results as a bar graph. Panel B provides details about each pathway including: (i) number of genes on the pathway, (ii) number of genes found in the reference array that are on the pathway, (iii) number of input genes found on the pathway, (iv) its impact factor, (v) database identifier of the pathway, etc. Panel C provides input details including the input ID, its corresponding gene name and symbol, number of pathways the gene is found on, and the fold change as provided by the user. Double-clicking a pathway name in panel B provides a list of genes on that pathway in panel D along with their perturbation factor.
Figure 5.
Figure 5.
The apoptosis pathway as described by KEGG (panel A) and its internal representation, as constructed by Pathway-Express (panel B). PE can save this internal representation in a GML file that can be exported to any other visualization application. In this internal representation, each node corresponds to a gene, and each edge represents an interaction between two genes. In this example, the up-regulated input gene FADD is highlighted with red color and down-regulated gene RELA is highlighted with blue color in both panels. The internal graph also shows how PE propagates the perturbation through the pathway, where the direction of an arrow represents the direction of propagation. Note that in some cases, a gene in KEGG diagram may represent a group of genes. For instance, gene PI3K in the KEGG diagram in fact corresponds to a group of eight nodes in PE's internal representation: PIK3R5, PIK3CA, PIK3CB, PIK3CD, PIK3CG, PIK3R1, PIK3R2 and PIK3R3.
Figure 6.
Figure 6.
New Onto-Miner input interface. OM automatically retrieves the results from the Onto-Tools server and saves them into the output file specified by the user.
See this image and copyright information in PMC

References

    1. Khatri P, Draghici S, Ostermeier GC, Krawetz SA. Profiling gene expression using onto-express. Genomics. 2002;79:266–270. - PubMed
    1. Draghici S, Khatri P, Bhavsar P, Shah A, Krawetz SA, Tainsky MA. Onto-tools, the toolkit of the modern biologist: Onto-express, onto-compare, onto-design and onto-translate. Nucleic Acids Res. 2003;31:3775–3781. - PMC - PubMed
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    1. Khatri P, Bhavsar P, Bawa G, Draghici S. Onto-tools: an ensemble of web-accessible, ontology-based tools for the functional design and interpretation of high-throughput gene expression experiments. Nucleic Acids Res. 2004;32:W449–W456. - PMC - PubMed
    1. Khatri P, Sellamuthu S, Malhotra P, Amin K, Done A, Draghici S. Recent additions and improvements to the onto-tools. Nucleic Acids Res. 2005;33:W762–W765. - PMC - PubMed

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