Evidence map›Paper›PMID 12610778›Full record

ArticleAmerican journal of human genetics2003

On the identification of disease mutations by the analysis of haplotype similarity and goodness of fit.

Jung-Ying Tzeng, B Devlin, Larry Wasserman, Kathryn Roeder

Abstract readComparative Study
In one paragraph

Article in American journal of human genetics, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.

0numbers the graph read from it
0cells of the map it votes in
64citing 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

64 citing papers in PubMed.

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4 more citing papers are in PubMed but not listed here.

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

4 authors.

Jung-Ying TzengDepartment of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
B Devlin
Larry Wasserman
Kathryn Roeder

Funding

Genetics Association in Schizophrenia and Other DisordersR37MH057881 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI DEVLIN, BERNIE · 2013 to 2022
$5.4M
GENETIC ASSOCIATION IN SCHIZOPHRENIA AND OTHER DISORDERSR01MH057881 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI DEVLIN, BERNIE · 1998 to 2012
$4.8M
BAYESIAN METHODS IN BIOSTATISTICSR01CA054852 · NCI · CARNEGIE-MELLON UNIVERSITY · PI GREENHOUSE, JOEL B. · 1991 to 2002
$1.1M
NCI NIH HHS CA54852-07NIMH NIH HHS MH57881NIMH NIH HHS R01 MH057881NIMH NIH HHS R37 MH057881
6 · The paper itself

Abstract

The observation that haplotypes from a particular region of the genome differ between affected and unaffected individuals or between chromosomes transmitted to affected individuals versus those not transmitted is sound evidence for a disease-liability mutation in the region. Tests for differentiation of haplotype distributions often take the form of either Pearson's chi(2) statistic or tests based on the similarity among haplotypes in the different populations. In this article, we show that many measures of haplotype similarity can be expressed in the same quadratic form, and we give the general form of the variance. As we describe, these methods can be applied to either phase-known or phase-unknown data. We investigate the performance of Pearson's chi(2) statistic and haplotype similarity tests through use of evolutionary simulations. We show that both approaches can be powerful, but under quite different conditions. Moreover, we show that the power of both approaches can be enhanced by clustering rare haplotypes from the distributions before performing a test.

Indexed as

Models, GeneticMutationChromosomes, HumanGenetic Diseases, InbornGenetic MarkersHaplotypesHumansModels, StatisticalReproducibility of ResultsGenetic Markers

Identifiers

PMID12610778
PMCPMC1180352

What OpenQuestion holds

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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.