PhenDisco: phenotype discovery system for the database of genotypes and phenotypes |
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| Authors: | Son Doan Ko-Wei Lin Mike Conway Lucila Ohno-Machado Alex Hsieh Stephanie Feudjio Feupe Asher Garland Mindy K Ross Xiaoqian Jiang Seena Farzaneh Rebecca Walker Neda Alipanah Jing Zhang Hua Xu Hyeon-Eui Kim |
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| Affiliation: | 1.Division of Biomedical Informatics, University of California San Diego, La Jolla, California, USA;2.School of Biomedical Informatics, The University of Texas Health Science Center at, Houston, Houston, Texas, USA |
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| Abstract: | The database of genotypes and phenotypes (dbGaP) developed by the National Center for Biotechnology Information (NCBI) is a resource that contains information on various genome-wide association studies (GWAS) and is currently available via NCBI''s dbGaP Entrez interface. The database is an important resource, providing GWAS data that can be used for new exploratory research or cross-study validation by authorized users. However, finding studies relevant to a particular phenotype of interest is challenging, as phenotype information is presented in a non-standardized way. To address this issue, we developed PhenDisco (phenotype discoverer), a new information retrieval system for dbGaP. PhenDisco consists of two main components: (1) text processing tools that standardize phenotype variables and study metadata, and (2) information retrieval tools that support queries from users and return ranked results. In a preliminary comparison involving 18 search scenarios, PhenDisco showed promising performance for both unranked and ranked search comparisons with dbGaP''s search engine Entrez. The system can be accessed at http://pfindr.net. |
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| Keywords: | DBGAP Phenotype Standardization Information Retrieval Text Mining GWAS Natural Language Processing |
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