Evidence map›Paper›PMID 29945968›Full record

ArticleG3 (Bethesda, Md.)2018

On the Relationship Between High-Order Linkage Disequilibrium and Epistasis.

Yanjun Zan, Simon K G Forsberg, Örjan Carlborg

Abstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Quinoa genome assembly employing genomic variation for guided scaffolding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021
    Article
  9. Article
  10. Article
  11. Article
  12. 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

3 authors.

Yanjun ZanDepartment of Medical Biochemistry and Microbiology, Uppsala University, SE-751 23 Uppsala, Sweden.ORCID 0000-0001-5571-4578
Simon K G ForsbergDepartment of Medical Biochemistry and Microbiology, Uppsala University, SE-751 23 Uppsala, Sweden.ORCID 0000-0002-7451-9222
Örjan CarlborgDepartment of Medical Biochemistry and Microbiology, Uppsala University, SE-751 23 Uppsala, Sweden orjan.carlborg@imbim.uu.se.ORCID 0000-0002-2722-5264

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A plausible explanation for statistical epistasis revealed in genome wide association analyses is the presence of high order linkage disequilibrium (LD) between the genotyped markers tested for interactions and unobserved functional polymorphisms. Based on findings in experimental data, it has been suggested that high order LD might be a common explanation for statistical epistasis inferred between local polymorphisms in the same genomic region. Here, we empirically evaluate how prevalent high order LD is between local, as well as distal, polymorphisms in the genome. This could provide insights into whether we should account for this when interpreting results from genome wide scans for statistical epistasis. An extensive and strong genome wide high order LD was revealed between pairs of markers on the high density 250k SNP-chip and individual markers revealed by whole genome sequencing in the

Indexed as

Epistasis, GeneticLinkage DisequilibriumAllelesArabidopsisGenetic Association StudiesGenetic MarkersGenome, PlantGenome-Wide Association StudyGenotypeHumansModels, GeneticPolymorphism, Single NucleotideQuantitative Trait, HeritableQuantitative Trait LociGenetic MarkersArabidopsis thalianaepistasishigh order linkage disequilibriumleafmolybdenum

Identifiers

PMID29945968
PMCPMC6071592

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.