| |
Citation: Fong CC, Edward AK, Mark DW, Scott JT (2008) DataBiNS-Viz: A Web-Based Tool for Visualization of Non-Synonymous SNP Data. J Proteomics Bioinform 1: 233-236.
|
Copyright: © 2008 Fong CC, etal. This is an open-access article distributed under the terms of the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and
source are credited.
|
Abstract
Here we describe DataBiNS-Viz – a visualization and exploration environment for non-synonymous coding
single nucleotide polymorphisms (nsSNPs) data gathered by the BioMoby-based DataBiNS workflow. DataBiNSViz
enables execution of the DataBiNS workflow on proteins described by KEGG, PubMed, or OMIM identifiers,
followed by manual exploration of the integrated structure/function and pathway data for those proteins, with
a particular focus on nsSNP data in-context. The tool can be freely accessed at http://bioinfo.icapture.ubc.ca:8090/
DataBiNS (please use the Firefox or Safari web browsers). Examples of the retrieved data are given under the“Help on inputs” option. Detailed documentation can be accessed at: http://bioinfo.icapture.ubc.ca/mywiki/DataBiNS.
Key Words
Bioinformatics; Web services; Data mining; Visualization; Genomics; Single nucleotide polymorphisms
Introduction
Single nucleotide polymorphisms (SNPs) are single base
mutations in a genomic sequence that occur at a frequency
greater than 1% in a defined population. Codons are sets
of three DNA bases in a gene sequence that code for a
particular amino acid. Non-synonymous SNPs (nsSNPs)
are SNPs that occur within codons and that change the
encoded amino acid, sometimes ultimately affecting the protein
that is constructed from the gene blueprint. nsSNPs
are of great interest to researchers as they may be key to
identifying and understanding various human disease susceptibilities,
as well as disease and non-disease phenotypes
in many other species.
In silico analysis of the potential biological impact of
nsSNPs requires integration of data and knowledge from
various Web-based resources, both databases and analytical
tools. Manual retrieval and integration of this information
is error-prone and tedious. This provided the motivation for the original DataBiNS - data-mining workflow (Song,
et al., 2007) for the BioMOBY
(Wilkinson and Links, 2002)
and Taverna (Oinn, et al., 2004) environments which retrieved
and integrated data relating to nsSNPs and the biological
pathways affected by them. DataBiNS consumes
Kyoto Encyclopedia of Genes and Genomes [KEGG] Pathway
Identifiers (Kanehisa, et al., 2006), and retrieves a list
of publications, gene ontology annotations and nsSNP information
for each gene involved in the pathway. Although
the public DataBiNS workflow successfully retrieved and
integrated these data, lack of a visualization tool for the output
significantly limited its utility. We report here important
extensions to the original DataBiNS workflow and environment,
including retrieval of additional nsSNP data such as
mapping of SNPs to their altered amino acids on a 3D protein
structure, as well as easy to navigate web-based visualizations
of the global DataBiNS output.
Workflow Initialization
To facilitate interoperability between the various Web
resources, the workflow extensions we report here continue
to be provided through the BioMoby Web Services
framework. Rather than being limited to a single KEGG
identifier, the new services allow for different types of identifiers
to be used to initialize the workflow, including:
1. KEGG gene (http://www.genome.jp/kegg/)
2. PubMed (http://www.ncbi.nlm.nih.gov/pubmed/)
3.OMIM - Online Mendelian Inheritance in Man (http://www.ncbi.nlm.nih.gov/sites/entrez?db=omim)
4.UniGene(http://www.ncbi.nlm.nih.gov/sites/
entrez?db=unigene)
5. UniProt (http://www.pir.uniprot.org/)
6. GenBank (http://www.ncbi.nlm.nih.gov/Genbank/)
7. NCBI-GI
To initiate searches on multiple KEGG genes simultaneously,
a comma can be placed between the different identifiers
(e.g., hsa:7097, hsa:7098)
Extensions to Retrieved Data
Once the workflow has been initialized, the workflow
first visits KEGG, PDB (http://www.rcsb.org/pdb/home/
home.do), SwissProt (http://www.expasy.ch/sprot/), and
Entrez (http://www.ncbi.nlm.nih.gov/Entrez/), to find the
corresponding gene id(s) corresponding to the input identifier.
Once retrieved, the LS-SNP (http://alto.compbio.ucsf.edu/LS-SNP/) database
(Karchin, et al.,
2005) is initialized with the corresponding SwissProt id to
find all the nsSNPs for the gene. The PDB id is then used
on the coliSNP (http://yayoi.kansai.jaea.go.jp/colisnp/) database
(Kono, et al., 2008) to retrieve the 3D structure of
the protein (if available). The various SNPs associated with
this gene are already mapped onto this protein structure
(within coliSNP), providing an efficient technique to analyze
the location of SNPs on the protein. Supplementing
the SNP information are frequency pie-charts of each SNP
id from the HapMap (http://www.hapmap.org/) database
(Thorisson, et al., 2005). Detailed annotations about the
gene are retrieved from the Gene Ontology (http://www.geneontology.org/) website, and finally the most recently
relevant publications to the gene are retrieved from
PubMed.
Web-Based Visualization
Rather than being limited to the default Taverna nestedfolder
browsing, or export of the data from Taverna as an
Excel spreadsheet, both of which are problematic for manual exploration of these complex data networks, we have created
a task-specific Web-based visualization and exploration
environment for DataBiNS. The application is built
using the Java Platform, Enterprise (J2EE) and is accessed
by end-users through an intuitive Web page. The user simply
enters an identifier of interest (i.e., KEGG PATHWAY,
OMIM, etc.), and then presses the “Execute Workflow”
button. In the backend, the Taverna workflow execution
engine is triggered to execute the modified DataBiNS
workflow. The results of the workflow are then cached on
the server to allow rapid browsing of results, and are
browsable via the Web interface (Figure 1). There is an
option on the front page to re-execute the workflow, where
the tool will ignore any saved results and retrieve new, possibly
updated data.
In addition to displaying all the results using standard
Web technologies, two navigation tools/methods have been
added to the web-application to help with the study of the
data. First, a “search publication abstract” option allows
for users to quickly search the retrieved publications for
keywords. If a retrieved publication has the keyword, the
publication will be highlighted allowing the user to focus on
that publication. The PubCloud (http://bioinfo.icapture.ubc.ca:8090/PubCloud/) application has also
been integrated into the web-application. The user can select
a group of the retrieved publications and quickly use
the PubCloud keyword tag-cloud visualization system to find
possible correlations between the publications.
In a significant advance over prior exploration/browsing
environments, the Web interface intuitively associates multiple
inputs with their respective outputs. Thus the Webapplication
displays all data about each gene in a discrete
section of the browser window; on a given results page
there can be several genes and each gene will have its associated
information clearly and intuitively organized and
displayed. This approach eliminates the user’s need to backtrack
through the results to correlate inputs to outputs, as
was required in earlier versions of DataBiNS, thus allowing
them to quickly analyze and use the retrieved data.
Future
Though the framework we have developed to display
the data is specific for the DataBiNS workflow, it can be
generalized to accept any Taverna-based workflow, displaying
the results as a browsable Web page and facilitating
exploration of results from Taverna-based workflows. The
modularized nature of workflows allows one to develop new
BioMoby services to add to DataBiNS in order to expand
the information retrieved and displayed.
|
Figure 1: DataBiNS-Viz Outputs. Examples of retrieved data and visualizations from a DataBiNS-Viz workflow search
of nsSNP information related to the KEGG gene hsa:3661 (interferon regulatory factor 3 from H. sapiens).
|
One lingering question is always the validity of the data
being retrieved. The workflow is designed to retrieve information
from a specified group of web resources. The
validity of the information obtained from the web resources
is not checked by the workflow and thus there is currently
no way to verify the integrity of the information across the
different resources, without a great deal of manual data
inspection. Future developments may lead to automation of
such processes with electronic flags highlighting inconsistencies
in data between different web resources.
Acknowledgements
This research was supported by the National Sanitarium
Association (Canada), AllerGen NCE, and the Michael Smith
Foundation for Health Research. EK is supported by an
award to MDW from Genome Alberta, in part through Genome
Canada.
Conflict of Interest: none declared.
Reference
-
Kanehisa M , Goto S, Hattori M, Aoki KKF,
Itoh M, Kawashima S, Katayama T, Araki M,
Hirakawa M (2006) From genomics to chemical genomics:
new developments in KEGG Nucleic Acids Res 34: D354-
357. [ FIND THIS ARTICLE ONLINE ]
-
Karchin R , Diekhans M, Kelly L, Thomas DJ,
Pieper U, Eswar N, Haussler D, Sali A (2005) LSSNP:
large-scale annotation of coding non-synonymous
SNPs based on multiple information sources Bioinformatics
21: 2814-2820. [ FIND THIS ARTICLE ONLINE ]
-
Kono H , Yuasa T, Nishiue S, Yura K (2008)
coliSNP database server mapping nsSNPs on protein structures,
Nucleic Acids Res 36: D409-413. [ FIND THIS ARTICLE ONLINE ]
-
Oinn T , Addis M, Ferris J, Marvin D, Senger M,
Greenwood M, Carver T, Glover K, Pocock MR, Wipat
A, Li P (2004) Taverna: a tool for the composition and
enactment of bioinformatics workflows Bioinformatics 20:
3045-3054. [ FIND THIS ARTICLE ONLINE ]
-
Song YC , Kawas E, Good BM, Wilkinson MD, Tebbutt SJ (2007) DataBiNS: a BioMoby-based datamining
workflow for biological pathways and non-synonymous
SNPs Bioinformatics 23: 780-782. [ FIND THIS ARTICLE ONLINE ]
-
Thorisson GA , Smith AV, Krishnan L, Stein LD
(2005) The International HapMap Project Web site Genome
Res 15: 1592-1593. [ FIND THIS ARTICLE ONLINE ]
-
Wilkinson MD , Links M (2002) BioMOBY: an
open source biological web services proposal Brief
Bioinform 3: 331-341. [ FIND THIS ARTICLE ONLINE ]
Top
|
|
