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Online genetic databases informing human genome epidemiology

BACKGROUND: With the advent of high throughput genotyping technology and the information available via projects such as the human genome sequencing and the HapMap project, more and more data relevant to the study of genetics and disease risk will be produced. Systematic reviews and meta-analyses of...

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Autores principales: Frodsham, Angela J, Higgins, Julian PT
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1929117/
https://www.ncbi.nlm.nih.gov/pubmed/17610726
http://dx.doi.org/10.1186/1471-2288-7-31
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author Frodsham, Angela J
Higgins, Julian PT
author_facet Frodsham, Angela J
Higgins, Julian PT
author_sort Frodsham, Angela J
collection PubMed
description BACKGROUND: With the advent of high throughput genotyping technology and the information available via projects such as the human genome sequencing and the HapMap project, more and more data relevant to the study of genetics and disease risk will be produced. Systematic reviews and meta-analyses of human genome epidemiology studies rely on the ability to identify relevant studies and to obtain suitable data from these studies. A first port of call for most such reviews is a search of MEDLINE. We examined whether this could be usefully supplemented by identifying databases on the World Wide Web that contain genetic epidemiological information. METHODS: We conducted a systematic search for online databases containing genetic epidemiological information on gene prevalence or gene-disease association. In those containing information on genetic association studies, we examined what additional information could be obtained to supplement a MEDLINE literature search. RESULTS: We identified 111 databases containing prevalence data, 67 databases specific to a single gene and only 13 that contained information on gene-disease associations. Most of the latter 13 databases were linked to MEDLINE, although five contained information that may not be available from other sources. CONCLUSION: There is no single resource of structured data from genetic association studies covering multiple diseases, and in relation to the number of studies being conducted there is very little information specific to gene-disease association studies currently available on the World Wide Web. Until comprehensive data repositories are created and utilized regularly, new data will remain largely inaccessible to many systematic review authors and meta-analysts.
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spelling pubmed-19291172007-07-21 Online genetic databases informing human genome epidemiology Frodsham, Angela J Higgins, Julian PT BMC Med Res Methodol Research Article BACKGROUND: With the advent of high throughput genotyping technology and the information available via projects such as the human genome sequencing and the HapMap project, more and more data relevant to the study of genetics and disease risk will be produced. Systematic reviews and meta-analyses of human genome epidemiology studies rely on the ability to identify relevant studies and to obtain suitable data from these studies. A first port of call for most such reviews is a search of MEDLINE. We examined whether this could be usefully supplemented by identifying databases on the World Wide Web that contain genetic epidemiological information. METHODS: We conducted a systematic search for online databases containing genetic epidemiological information on gene prevalence or gene-disease association. In those containing information on genetic association studies, we examined what additional information could be obtained to supplement a MEDLINE literature search. RESULTS: We identified 111 databases containing prevalence data, 67 databases specific to a single gene and only 13 that contained information on gene-disease associations. Most of the latter 13 databases were linked to MEDLINE, although five contained information that may not be available from other sources. CONCLUSION: There is no single resource of structured data from genetic association studies covering multiple diseases, and in relation to the number of studies being conducted there is very little information specific to gene-disease association studies currently available on the World Wide Web. Until comprehensive data repositories are created and utilized regularly, new data will remain largely inaccessible to many systematic review authors and meta-analysts. BioMed Central 2007-07-04 /pmc/articles/PMC1929117/ /pubmed/17610726 http://dx.doi.org/10.1186/1471-2288-7-31 Text en Copyright © 2007 Frodsham and Higgins; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Frodsham, Angela J
Higgins, Julian PT
Online genetic databases informing human genome epidemiology
title Online genetic databases informing human genome epidemiology
title_full Online genetic databases informing human genome epidemiology
title_fullStr Online genetic databases informing human genome epidemiology
title_full_unstemmed Online genetic databases informing human genome epidemiology
title_short Online genetic databases informing human genome epidemiology
title_sort online genetic databases informing human genome epidemiology
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1929117/
https://www.ncbi.nlm.nih.gov/pubmed/17610726
http://dx.doi.org/10.1186/1471-2288-7-31
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