Evidence map›Paper›PMID 9042930›Full record

ArticleAmerican journal of human genetics1997

Power studies for the transmission/disequilibrium tests with multiple alleles.

N L Kaplan, E R Martin, B S Weir

Abstract read
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 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

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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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  17. Transmission/disequilibrium tests for multiallelic loci.American journal of human genetics · 1997
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

N L KaplanBiostatistics Branch, NIEHS, Research Triangle Park, NC 27709, USA. norm@seth.niehs.nih.gov
E R Martin
B S Weir

Funding

THEORETICAL QUANTITATIVE GENETICSP01GM045344 · NIGMS · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI GIBSON, GREGORY C. · 1991 to 2005
$7.2M
TRAINING IN MOLECULAR AND QUANTITATIVE GENETICST32GM008443 · NIGMS · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI MACKAY, TRUDY F. · 1992 to 2013
$1.7M
NA+ CHANNELS IN NORMAL &ABNORMAL NERVE MEMBRANER01NS023360 · NINDS · UNIVERSITY OF CHICAGO · PI ROGART, RICHARD B · 1989 to 1993
–
NIGMS NIH HHS P01 GM45344NIGMS NIH HHS T32 GM08443NINDS NIH HHS R01 NS23360
6 · The paper itself

Abstract

Case-control studies compare marker-allele distributions in affected and unaffected individuals, and significant results suggest linkage but may simply reflect population structure. For markers with m alleles (m > or = 2), a McNemar-like statistic, I, estimates the level of population association between marker and disease loci. To test for linkage after significant case-control tests, within-family tests are performed. These operate on the contingency table, with i, jth element equal to the number of parents that transmit marker allele Mi and do not transmit marker allele Mi to an affected offspring. The dimension of the table is the number of alleles at the marker locus. Three test statistics have recently been proposed in the literature: Tc compares symmetric pairs of cells (i, j) and (j, i), Tm compares row and column totals for the same marker allele, and a likelihood ratio statistic Tl uses all the cells in the table. In addition, we consider a new statistic, Tmhet, that uses only the heterozygous parents and is approximately chi2 with (m - 1) df. We use a Monte Carlo test to guarantee valid tests and to demonstrate the inferiority of Tc and the equality of Tm and Tl in terms of power. The power of the Tmhet test is close but not always equal to the power of the Tm test. We also show that under the alternative hypothesis of linkage, Tm is approximately noncentral chi2 with (m - 1) df and noncentrality parameter 2NT(1 - 2theta)2I*, when data on single affecteds in NT families are used. If the disease has a low population frequency, then I* is estimated using the case-control statistic I. This offers a basis for choosing sample size, or choosing a marker system.

Indexed as

AllelesLinkage DisequilibriumFemaleGenetic MarkersGenetic TechniquesHumansMaleModels, GeneticModels, StatisticalMonte Carlo MethodGenetic Markers

Identifiers

PMID9042930
PMCPMC1712498

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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.