Evidence map›Paper›PMID 10053022›Full record

ArticleAmerican journal of human genetics1999

Analysis of affected sib pairs, with covariates--with and without constraints.

C M Greenwood, S B Bull

Abstract read
In one paragraph

Article in American journal of human genetics, 1999. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
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  3. Article
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  6. Article
  7. A novel framework for sib pair linkage analysis.American journal of human genetics · 2006
    Article
  8. Article
  9. A genome wide search for alcoholism susceptibility genes.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2004
    Article
  10. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

C M GreenwoodDivision of Medical Genetics, Montreal General Hospital, L10-109, 1650 Cedar Avenue, Montreal, Quebec H3G 1A4, Canada. celia@utstat.utoronto.ca
S B Bull

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Covariate models have previously been developed as an extension to affected-sib-pair methods in which the covariate effects are jointly estimated with the degree of excess allele sharing. These models can estimate the differences in sib-pair allele sharing that are associated with measurable environment or genes. When there are no covariates, the pattern of identical-by-descent allele sharing in affected sib pairs is expected to fall within a small triangular region of the potential parameter space, under most genetic models. By restriction of the estimated allele sharing to this triangle, improved power is obtained in tests for genetic linkage. When the affected-sib-pair model is generalized to allow for covariates that affect allele sharing, however, new constraints and new methods for the application of constraints are required. Three generalized constraint methods are proposed and evaluated by use of simulated data. The results compare the power of the different methods, with and without covariates, for a single-gene model with age-dependent onset and for quantitative and qualitative gene-environment and gene-gene interaction models. Covariates can improve the power to detect linkage and can be particularly valuable when there are qualitative gene-environment interactions. In most situations, the best strategy is to assume that there is no dominance variance and to obtain constrained estimates for covariate models under this assumption.

Indexed as

AllelesModels, GeneticModels, StatisticalAge of OnsetFamilyGenetic LinkageHeterozygoteHumansLod ScorePenetranceStatistics as Topic

Identifiers

PMID10053022
PMCPMC1377805

What OpenQuestion holds

Texttitle and abstract
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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.