Evidence map›Paper›PMID 9106544›Full record

ArticleAmerican journal of human genetics1997

Strategies for mapping heterogeneous recessive traits by allele-sharing methods.

E Feingold, D O Siegmund

Abstract readComparative Study
In one paragraph

Article in American journal of human genetics, 1997. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Simple, robust linkage tests for affected sibs.American journal of human genetics · 1998
    Article
  8. 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

2 authors.

E FeingoldDepartment of Biostatistics, Emory University, Atlanta, GA 30322, USA. feingold@sph.emory.edu
D O Siegmund

Funding

STATISTICAL METHODS FOR IDENTITY-BY-DESCENT MAPSR01HG000848 · NHGRI · STANFORD UNIVERSITY · PI SIEGMUND, DAVID O · 1994 to 2008
$691k
NHGRI NIH HHS R01 HG00848-01A1
6 · The paper itself

Abstract

We investigate strategies for detecting linkage of recessive and partially recessive traits, using sibling pairs and inbred individuals. We assume that a genomewide search is being conducted and that locus heterogeneity of the trait is likely. For sibling pairs, we evaluate the efficiency of different statistics under the assumption that one does not know the true degree of recessiveness of the trait. We recommend a sibling-pair statistic that is a linear compromise between two previously suggested statistics. We also compare the power of sibling pairs to that of more distant relatives, such as cousins. For inbred individuals, we evaluate the power of offspring of different types of matings and compare them to sibling pairs. Over a broad range of trait etiologies, sibling pairs are more powerful than inbred individuals, but for traits caused by very rare alleles, particularly in the case of heterogeneity, inbred individuals can be much more powerful. The models we develop can also be used to examine specific situations other than those we look at. We present this analysis in the idealized context of a dense set of highly polymorphic markers. In general, incorporation of real-world complexities makes inbred individuals, particularly offspring of distant relatives, look slightly less useful than our results imply.

Indexed as

Genes, RecessiveGenetic HeterogeneityModels, GeneticChromosome MappingConsanguinityFemaleGenetic MarkersGenome, HumanHumansMaleMarkov ChainsNormal DistributionNuclear FamilyPolymorphism, GeneticResearch DesignGenetic Markers

Identifiers

PMID9106544
PMCPMC1712456

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.