Evidence map›Paper›PMID 11591648›Full record

ArticleGenome research2001

Bayesian analysis of haplotypes for linkage disequilibrium mapping.

J S Liu, C Sabatti, J Teng, B J Keats, N Risch

Abstract read
In one paragraph

Article in Genome research, 2001. 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. Trial
  2. Article
  3. Tree-based QTL mapping with expected local genetic relatedness matrices.bioRxiv : the preprint server for biology · 2023
    Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. The limits of fine-scale mapping.Genetic epidemiology · 2009
    Article
  9. Article
  10. Article
  11. A survey on haplotyping algorithms for tightly linked markers.Journal of bioinformatics and computational biology · 2008
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

5 authors.

J S LiuDepartment of Statistics, Harvard University, Cambridge, Massachusetts 02138, USA. jliu@stat.harvard.edu
C Sabatti
J Teng
B J Keats
N Risch

Funding

Theoretical Studies of Linkage DisequilibriumP01GM057672 · NIGMS · YALE UNIVERSITY · PI KIDD, JUDITH R · 1998 to 2008
$11.0M
NIGMS NIH HHS GM057672NIGMS NIH HHS P01 GM057672
6 · The paper itself

Abstract

Haplotype analysis of disease chromosomes can help identify probable historical recombination events and localize disease mutations. Most available analyses use only marginal and pairwise allele frequency information. We have developed a Bayesian framework that utilizes full haplotype information to overcome various complications such as multiple founders, unphased chromosomes, data contamination, and incomplete marker data. A stochastic model is used to describe the dependence structure among several variables characterizing the observed haplotypes, for example, the ancestral haplotypes and their ages, mutation rate, recombination events, and the location of the disease mutation. An efficient Markov chain Monte Carlo algorithm was developed for computing the estimates of the quantities of interest. The method is shown to perform well in both real data sets (cystic fibrosis data and Friedreich ataxia data) and simulated data sets. The program that implements the proposed method, BLADE, as well as the two real datasets, can be obtained from http://www.fas.harvard.edu/~junliu/TechRept/01folder/diseq_prog.tar.gz.

Indexed as

Bayes TheoremChromosome MappingComputer SimulationCystic FibrosisFriedreich AtaxiaHaplotypesHumansLinkage DisequilibriumModels, Statistical

Identifiers

PMID11591648
PMCPMC311130

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.