Evidence map›Paper›PMID 35901513›Full record

SynthesisBriefings in bioinformatics2022

A systematic review of analytical methods used in genetic association analysis of the X-chromosome.

Nick Keur, Isis Ricaño-Ponce, Vinod Kumar, Vasiliki Matzaraki

Abstract readSystematic Review
In one paragraph

Synthesis in Briefings in bioinformatics, 2022. 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
–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

18 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Sex Bias in Autoimmunity: New Findings and New Opportunities.JID innovations : skin science from molecules to population health · 2025
    Review
  6. Article
  7. Article
  8. Article
  9. Hepatic immune regulation and sex disparities.Nature reviews. Gastroenterology & hepatology · 2024
    Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  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

4 authors.

Nick KeurDepartment of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 HP, Nijmegen, The Netherlands.
Isis Ricaño-PonceDepartment of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 HP, Nijmegen, The Netherlands.
Vinod KumarDepartment of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 HP, Nijmegen, The Netherlands.
Vasiliki MatzarakiDepartment of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 HP, Nijmegen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic association studies have been very successful at elucidating the genetic background of many complex diseases/traits. However, the X-chromosome is often neglected in these studies because of technical difficulties and the fact that most tools only utilize genetic data from autosomes. In this review, we aim to provide an overview of different practical approaches that are followed to incorporate the X-chromosome in association analysis, such as Genome-Wide Association Studies and Expression Quantitative Trait Loci Analysis. In general, the choice of which test statistics is most appropriate will depend on three main criteria: (1) the underlying X-inactivation model, (2) if Hardy-Weinberg equilibrium holds and sex-specific allele frequencies are expected and (3) whether adjustment for confounding variables is required. All in all, it is recommended that a combination of different association tests should be used for the analysis of X-chromosome.

Indexed as

Chromosomes, Human, XGenome-Wide Association StudyFemaleGene FrequencyHumansMalePhenotypePolymorphism, Single NucleotideQuantitative Trait LociX Chromosome Inactivationassociation analysiseQTLGWASlinear regressionX-chromosomeX-inactivation

Identifiers

PMID35901513
PMCPMC9764208

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.