Evidence map›Paper›PMID 19432954›Full record

ArticleBMC bioinformatics2009

eCOMPAGT -- efficient combination and management of phenotypes and genotypes for genetic epidemiology.

Sebastian Schönherr, Hansi Weissensteiner, Stefan Coassin, Günther Specht, Florian Kronenberg, Anita Brandstätter

Abstract read
In one paragraph

Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

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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

6 authors.

Sebastian SchönherrDepartment of Database and Information Systems, Institute of Computer Science, University of Innsbruck, Innsbruck, Austria. sebastian.schoenherr@uibk.ac.at
Hansi Weissensteiner
Stefan Coassin
Günther Specht
Florian Kronenberg
Anita Brandstätter

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHigh-throughput genotyping and phenotyping projects of large epidemiological study populations require sophisticated laboratory information management systems. Most epidemiological studies include subject-related personal information, which needs to be handled with care by following data privacy protection guidelines. In addition, genotyping core facilities handling cooperative projects require a straightforward solution to monitor the status and financial resources of the different projects. DESCRIPTION: We developed a database system for an efficient combination and management of phenotypes and genotypes (eCOMPAGT) deriving from genetic epidemiological studies. eCOMPAGT securely stores and manages genotype and phenotype data and enables different user modes with different rights. Special attention was drawn on the import of data deriving from TaqMan and SNPlex genotyping assays. However, the database solution is adjustable to other genotyping systems by programming additional interfaces. Further important features are the scalability of the database and an export interface to statistical software.

conclusioneCOMPAGT can store, administer and connect phenotype data with all kinds of genotype data and is available as a downloadable version at (http://dbis-informatik.uibk.ac.at/ecompagt).

Indexed as

Database Management SystemsGenotypePhenotypeSoftwareComputational BiologyMolecular EpidemiologyPolymorphism, Single NucleotideUser-Computer Interface

Identifiers

PMID19432954
PMCPMC2685123

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.