Evidence map›Paper›PMID 22128057›Full record

ArticleGenetic epidemiology2011

Population-based and family-based designs to analyze rare variants in complex diseases.

Rémi Kazma, Julia N Bailey

Abstract read
In one paragraph

Article in Genetic epidemiology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 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

2 authors.

Rémi KazmaDepartment of Epidemiology and Biostatistics and Institute for Human Genetics, University of California, San Francisco, CA 94143-3110, USA. KazmaR@humgen.ucsf.edu
Julia N Bailey

Funding

GENETIC ANALYSIS OF COMMON DISEASES: AN EVALUATIONR01GM031575 · NIGMS · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI ALMASY, LAURA A. · 1985 to 2016
$7.8M
Training in Molecular& Genetic Epidemiology of CancerR25CA112355 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WITTE, JOHN S. · 2005 to 2018
$6.5M
Discovering More Juvenile Myoclonic Epilepsy Genes by a ConsortiumR01NS055057 · NINDS · BRENTWOOD BIOMEDICAL RESEARCH INSTITUTE · PI BAILEY, JULIA N, DELGADO-ESCUETA, ANTONIO V. · 2010 to 2014
$2.4M
NCI NIH HHS R25 CA112355NIGMS NIH HHS R01 GM031575NINDS NIH HHS R01 NS055057
6 · The paper itself

Abstract

Genotyping of rare variants on a large scale is now possible using next-generation sequencing. Sample selection is a crucial step in designing the genetic study of a complex disease, and knowledge of the efficiency and limitations of population-based and family-based designs can help researchers make the appropriate choice. The nine contributions to Group 5 of Genetic Analysis Workshop 17 evaluate population-based and family-based designs by comparing the results obtained with various methods applied to the mini-exome simulations. These simulations consisted of 200 replicates composed of unrelated individuals and eight extended pedigrees with genotypes and various phenotypes. The methods tested for association with a population-based and/or a family-based design, tested for linkage with a family-based design, or estimated heritability. We summarize the strengths and weaknesses of both designs. Although population-based designs seem more suitable for detecting the effect of multiple rare variants, family-based designs can potentially enrich the sample in rare variants, for which the effect would be concealed at the population level. However, as of today, the main limitation is still the high cost of next-generation sequencing.

Indexed as

Genetic Predisposition to DiseaseCausalityExomeGenetic LinkageHuman Genome ProjectHumansModels, GeneticMolecular EpidemiologyRegression Analysis

Identifiers

PMID22128057
PMCPMC3393851

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

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 Socratic graph.