Evidence map›Paper›PMID 22549767›Full record

ArticleGenetic epidemiology2012

Is it rare or common?

Kaustubh Adhikari, Taofik AlChawa, Kerstin Ludwig, Elisabeth Mangold, Nan Laird, Christoph Lange

Abstract read
In one paragraph

Article in Genetic epidemiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Kaustubh AdhikariDepartment of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA. kadhikar.hsph@gmail.com
Taofik AlChawa
Kerstin Ludwig
Elisabeth Mangold
Nan Laird
Christoph Lange

Funding

Genetic Epidemiology of COPDU01HL089897 · NHLBI · NATIONAL JEWISH HEALTH · PI CRAPO, JAMES D · 2007 to 2021
$56.9M
Genetic Epidemiology of COPDU01HL089856 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SILVERMAN, EDWIN K · 2007 to 2021
$20.7M
Novel Statistical Approaches to Mental Health Phenotype Analysis in GWA StudiesR01MH081862 · NIMH · HARVARD SCHOOL OF PUBLIC HEALTH · PI LANGE, CHRISTOPH · 2009 to 2014
$2.0M
A New Approach to Mental Health Phenotypes in Family Genomewide AssociationR01MH087590 · NIMH · HARVARD SCHOOL OF PUBLIC HEALTH · PI LANGE, CHRISTOPH · 2010 to 2013
$1.6M
NHLBI NIH HHS U01 HL089856NHLBI NIH HHS U01HL089856NHLBI NIH HHS U01 HL089897NHLBI NIH HHS U01HL089897NIMH NIH HHS R01 MH081862NIMH NIH HHS R01MH081862NIMH NIH HHS R01 MH087590NIMH NIH HHS R01MH087590
6 · The paper itself

Abstract

Many genome-wide association studies (GWAS) have signals with unknown etiology. This paper addresses the question-is such an association signal caused by rare or common variants that lead to increased disease risk? For a genomic region implicated by a GWAS, we use single nucleotide polymorphism (SNP) data in a case-control setting to predict how many common or rare variants there are, using a Bayesian analysis. Our objective is to compute posterior probabilities for configurations of rare and/or common variants. We use an extension of coalescent trees--the ancestral recombination graphs--to model the genealogical history of the samples based on marker data. As we expect SNPs to be in linkage disequilibrium with common disease variants, we can expect the trees to reflect the type of variants. To demonstrate the application, we apply our method to candidate gene sequencing data from a German case-control study on nonsyndromic cleft lip with or without cleft palate.

Indexed as

Bayes TheoremCase-Control StudiesGenetic MarkersGenetic VariationGermanyHaplotypesHumansLikelihood FunctionsLinkage DisequilibriumModels, GeneticModels, StatisticalModels, TheoreticalMolecular EpidemiologyMutationPolymorphism, Single NucleotideProbabilityGenetic Markers

Identifiers

PMID22549767
PMCPMC3641852

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.