OAT The Ontology Annotation Tree browser tool

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OAT - The Ontology Annotation Tree browser tool
Motivation for OAT
1. Submit probe sets
Technical Components
The microarray technique has gained enormous
popularity both among the major pharmaceutical
companies and academic institutions. Even though
all the benefits of the technique, we have to
face the problems of that the amount of resulting
information of microarray analysis is of such
magni-tude that it is difficult to get an
overview of the data. The need of condensing the
information of an analysis is therefore evident.
In order to address this challenge we have
developed the Ontology Annotation Tree browser
tool (OAT-tool). The OAT-tool utilizes the two
ontologies of Medical Subject Headings (MeSH) and
Gene Ontology (GO) to represent the information.
The OAT-tool runs from a web server. It is
written in Perl and CGI. All data are stored in
the OAT database (OATdb) and for each query a
Query Specific database (QSdb) is generated. The
information flow of OATs three main scripts is
outlined below to the right.
2. Browse the Ontology
The information flow of OAT
Checkbox for terms which are to be included in
the report
Significance of the Annotation
Number of probe set annotated with this term
MeSH is the National Library of Medicine's
controlled vo-cabulary thesaurus. Thesauri are
carefully constructed sets of terms often
connected by broader-than, narrower-than,
Number of probe set below
Number of annotations below
Link to MeSH description
and related links. These links show the
relationships between related terms and provide a
hierarchical structure that permits searching at
various levels of specificity from narrower to
broader. There are more than 19,000 terms in MeSH
3. Make a report
The goal of the Gene OntologyTM Consort-ium is to
produce a dynamic controlled vocabulary that can
be applied to all organ-
At the home page of OAT (a) a link to the query
form is found. (b) The probe sets and the tree
option is sent to the tree setup script. The
relevant information of the query is (c)
extracted from OATdb and (d) stored in QSdb. The
tree browser script (e) reads data from QSdb and
(f) visualises it as a web page. For each
modification of the tree visualisation (g) the
tree browser script is reloaded with the new
data. By marking terms and clicking on the submit
button (h) the report information is sent to (i)
a redirection script. The report scripts, one
each for the sorting of data in terms of genes or
term strings, (j) reads data from QSdb and (k)
generates a report web page.
Work flow of the OAT-tool
Link to Affymetrix DB
isms. The terms are structured in three
ontologies Molecular Function, Biological
Process and Cellular Componet.
Link to MeSH DB
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For each query of probe sets we extract a subset
of the ontology and assign the annotated genes to
the different terms in the ontology. The user
browse the ontology in a hierarchical way from
the top-level terms and down to the more detailed
ones. When a satisfying level of detail is
reached the user have the ability of summarizing
the information in a report which could be used
for further studies.
Link to MEDLINE
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The source of information
The gene information is collected from
AffymeterixTM-files. Ontology information is
collected from MeSH and GO. Annotations is
collected from EMBL/MEDLINE and Gene Ontology
Annotation Campaign (GOAC).
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A more detailed description of the work is given
in Interpretion of microarray expression data
using ontology browsing, a master thesis report
(LiTH-IDA-Ex-02/75) from Linköpings Universitet
by Anders Bresell.

• Anders Bresell1, Bo Servenius2
• Department of Computer and Information Science,
  Linköpings Universitet, Linköping, Sweden.
• Department of Molecular Sciences, AstraZeneca RD
  Lund, Lund Sweden.
• URL http//bioinfo.selu.astrazeneca.net/ext_abl
  /html/atb/