Evidence map›Paper›PMID 20015478›Full record

ArticleJournal of biomedical informatics2010

Evaluation of probabilistic and logical inference for a SNP annotation system.

Terry H Shen, Peter Tarczy-Hornoch, Landon T Detwiler, Eithon Cadag, Christopher S Carlson

Abstract readEvaluation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of biomedical informatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Current methodologies for translational bioinformatics.Journal of biomedical informatics · 2010
    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

5 authors.

Terry H ShenDepartment of Biomedical and Health Informatics, University of Washington, Seattle, WA 98195-7240, USA. hyshen@u.washington.edu
Peter Tarczy-Hornoch
Landon T Detwiler
Eithon Cadag
Christopher S Carlson

Funding

University of Washington Biomedical Informatics and Data Science Research Training ProgramT15LM007442 · NLM · UNIVERSITY OF WASHINGTON · PI JOHN H. GENNARI, Andrea L. Hartzler · 2002 to 2026
$19.6M
GENESEEK: DATA INTEGRATION SYSTEM FOR GENETIC DATABASESR01HG002288 · NHGRI · UNIVERSITY OF WASHINGTON · PI TARCZY-HORNOCH, PETER · 2000 to 2005
$2.0M
NHGRI NIH HHS R01 HG002288NHGRI NIH HHS R01 HG02288NLM NIH HHS T15 LM007442NLM NIH HHS T15 LM07442
6 · The paper itself

Abstract

Genome wide association studies (GWAS) are an important approach to understanding the genetic mechanisms behind human diseases. Single nucleotide polymorphisms (SNPs) are the predominant markers used in genome wide association studies, and the ability to predict which SNPs are likely to be functional is important for both a priori and a posteriori analyses of GWA studies. This article describes the design, implementation and evaluation of a family of systems for the purpose of identifying SNPs that may cause a change in phenotypic outcomes. The methods described in this article characterize the feasibility of combinations of logical and probabilistic inference with federated data integration for both point and regional SNP annotation and analysis. Evaluations of the methods demonstrate the overall strong predictive value of logical, and logical with probabilistic, inference applied to the domain of SNP annotation.

Indexed as

Models, StatisticalPolymorphism, Single NucleotideDatabases, GeneticGenome-Wide Association StudyLogic

Identifiers

PMID20015478
PMCPMC2878960

What OpenQuestion holds

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Registered trials

None linked

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.