Evidence map›Paper›PMID 16685642›Full record

ArticleAmerican journal of human genetics2006

Multilocus association mapping using variable-length Markov chains.

Sharon R Browning

Abstract read
In one paragraph

Article in American journal of human genetics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed, 1 pooled it
–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

76 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  13. A spatial haplotype copying model with applications to genotype imputation.Journal of computational biology : a journal of computational molecular cell biology · 2015
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16 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

1 author.

Sharon R BrowningDepartment of Statistics, The University of Auckland, Auckland 92019, New Zealand. browning@stat.auckland.ac.nz

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

I propose a new method for association-based gene mapping that makes powerful use of multilocus data, is computationally efficient, and is straightforward to apply over large genomic regions. The approach is based on the fitting of variable-length Markov chain models, which automatically adapt to the degree of linkage disequilibrium (LD) between markers to create a parsimonious model for the LD structure. Edges of the fitted graph are tested for association with trait status. This approach can be thought of as haplotype testing with sophisticated windowing that accounts for extent of LD to reduce degrees of freedom and number of tests while maximizing information. I present analyses of two published data sets that show that this approach can have better power than single-marker tests or sliding-window haplotypic tests.

Indexed as

Markov ChainsChromosome MappingCrohn DiseaseCystic FibrosisGenetic MarkersHumansLinkage DisequilibriumPolymorphism, Restriction Fragment LengthGenetic Markers

Identifiers

PMID16685642
PMCPMC1474089

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.