Evidence map›Paper›PMID 9199574›Full record

ArticleAmerican journal of human genetics1997

Fine-scale genetic mapping based on linkage disequilibrium: theory and applications.

M Xiong, S W Guo

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 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

45 citing papers in PubMed.

  1. Article
  2. Review
  3. A fast expectation-maximum algorithm for fine-scale QTL mapping.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2012
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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.

M XiongDivision of Epidemiology, University of Minnesota, Minneapolis 55454-1015, USA.
S W Guo

Funding

STATISTICAL MODELS IN POPULATION &QUANTITATIVE GENETICSR01GM056515 · NIGMS · UNIVERSITY OF MINNESOTA TWIN CITIES · PI GUO, SUN-WEI · 1997 to 2000
$158k
STATISTICAL METHODS FOR MAPPING COMPLEX GENETIC TRAITSR29GM052205 · NIGMS · UNIVERSITY OF MINNESOTA TWIN CITIES · PI GUO, SUN-WEI · 1995 to 1999
–
NIGMS NIH HHS R01-GM56515NIGMS NIH HHS R29-GM52205
6 · The paper itself

Abstract

Linkage-disequilibrium mapping (LDM) recently has been hailed as a powerful statistical method for fine-scale mapping of disease genes. After reviewing its historical background and methodological development, we present a general, mathematical, and conceptually coherent framework for LDM that incorporates multilocus and multiallelic markers and mutational processes at the marker and disease loci. With this framework, we address several issues relevant to fine-scale mapping and propose some efficient computational methods for LDM. We implement various LDM methods that incorporate population growth, recurrent mutation, and marker mutations, on the basis of a general framework. We demonstrate these methods by applying them to published data on cystic fibrosis, Huntington disease, Friedreich ataxia, and progressive myoclonus epilepsy. Since the genes responsible for these diseases all have been cloned, we can evaluate the performance of our methods and can compare ours with that of other methods. Using the proposed methods, we successfully and accurately predicted the locations of genes responsible for these diseases, on the basis of published data only.

Indexed as

Chromosome MappingLinkage DisequilibriumModels, GeneticCystic FibrosisEpilepsies, MyoclonicFriedreich AtaxiaGenetic Diseases, InbornGenetic MarkersHumansHuntington DiseaseMathematicsGenetic Markers

Identifiers

PMID9199574
PMCPMC1716118

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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.