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Bioinformatics Advance Access published online on April 17, 2009
Bioinformatics, doi:10.1093/bioinformatics/btp259
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©2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Application and evaluation of automated semantic annotation of gene expression experiments

Leon French 1, Suzanne Lane 2, Tamryn Law 2, Lydia Xu 2 and Paul Pavlidis 2,3,*

1Bioinformatics Graduate Program
2Department of Psychiatry
3Centre for High-Throughput Biology
University of British Columbia, Vancouver BC, Canada

*To whom correspondence should be addressed. Dr. Paul Pavlidis, E-mail: paul{at}bioinformatics.ubc.ca


  Abstract

Motivation: Many microarray datasets are available online with formalized standards describing the probe sequences and expres-sion values. Unfortunately, the description, conditions and parame-ters of the experiments are less commonly formalized and often occur as natural language text. This hinders searching, high-throughput analysis, organization and integration of the datasets.

Results: We use the lexical resources and software tools from the Unified Medical Language System (UMLS) to extract concepts from text. We then link the UMLS concepts to classes in open biomedical ontologies. The result is accessible and clear semantic annotations of gene expression experiments. We applied the method to 595 expression experiments from Gemma, a resource for re-use and meta-analysis of gene expression profiling data. We evaluated and corrected all stages of the annotation process. The majority of missed annotations were due to a lack of cross-references. The most error prone stage was the extraction of concepts from phrases. Final review of the annotations in context of the experiments re-vealed 89% precision. A naive system, lacking the phrase to con-cept corrections is 68% precise. We have integrated this annotation pipeline into Gemma.

Availability: The source code, documentation and supplementary materials are available at http://www.chibi.ubc.ca/GEOMMTX. The results of the manual evaluations are provided as supplementary material. Both manual and predicted annotations can be viewed and searched via the Gemma website at http://www.chibi.ubc.ca/Gemma. The complete set of predicted an-notations is available as a machine readable RDF graph.

Contact: paul{at}chibi.ubc.ca

Associate Editor: Prof. Alfonso Valencia

Received on December 16, 2008; revised on March 9, 2009; accepted on April 10, 2009

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