Evidence map›Paper›PMID 23755066›Full record

ArticleFrontiers in genetics2013

eQTL Epistasis - Challenges and Computational Approaches.

Yang Huang, Stefan Wuchty, Teresa M Przytycka

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
11.0field-weighted citation impact, top 2% of its field
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

18 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Evolutionary footprint of epistasis.PLoS computational biology · 2018
    Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Detecting epistasis in human complex traits.Nature reviews. Genetics · 2014
    Review
  16. Article
  17. Article
  18. Review
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 at 1 institution in 1 country.

Yang HuangNational Center for Biotechnology Information, National Library of Medicine, National Institutes of Health Bethesda, MD, USA.
Stefan Wuchty
Teresa M Przytycka
National Center for Biotechnology Information · US

Funding

Combinatorial and graph theoretical approach to systems biology and mol. evo.ZIALM200887 · NLM · NATIONAL LIBRARY OF MEDICINE · PI PRZYTYCKA, TERESA · 2009 to 2025
$24.4M
6 · The paper itself

Abstract

The determination of expression quantitative trait loci (eQTL) epistasis - a form of functional interaction between genetic loci that affect gene expression - is an important step toward the thorough understanding of gene regulation. Since gene expression has emerged as an "intermediate" molecular phenotype eQTL epistasis might help to explain the relationship between genotype and higher level organismal phenotypes such as diseases. A characteristic feature of eQTL analysis is the big number of tests required to identify associations between gene expression and genetic loci variability. This problem is aggravated, when epistatic effects between eQTLs are analyzed. In this review, we discuss recent algorithmic approaches for the detection of eQTL epistasis and highlight lessons that can be learned from current methods.

Indexed as

epistasiseQTLgenetic associationgenetic crossesnetwork modules

Identifiers

PMID23755066
PMCPMC3668133
OpenAlexW2024799373

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.