Evidence map›Paper›PMID 17610726›Full record

ArticleBMC medical research methodology2007

Online genetic databases informing human genome epidemiology.

Angela J Frodsham, Julian P T Higgins

Abstract read
In one paragraph

Article in BMC medical research methodology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Guideline
  3. Registered access: a 'Triple-A' approach.European journal of human genetics : EJHG · 2016
    Article
  4. Toward modernizing the systematic review pipeline in genetics: efficient updating via data mining.Genetics in medicine : official journal of the American College of Medical Genetics · 2012
    Article
  5. Article
  6. Review
  7. A literature search tool for intelligent extraction of disease-associated genes.Journal of the American Medical Informatics Association : JAMIA
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Angela J FrodshamPublic Health Genetics Unit, Strangeways Research Laboratory, Cambridge, UK. angelaf@mrc-bsu.cam.ac.uk
Julian P T Higgins

Funding

Medical Research Council MC_U105285807
6 · The paper itself

Abstract

backgroundWith 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.

methodsWe 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.

resultsWe 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.

conclusionThere 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.

Indexed as

Databases, GeneticEpidemiologic StudiesGenetic VariationInformation Storage and RetrievalInternetMEDLINEMeta-Analysis as TopicGenome, HumanGenotypeHumansPhenotypePrevalence

Identifiers

PMID17610726
PMCPMC1929117

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.