Evidence map›Paper›PMID 36276986›Full record

ReviewFrontiers in genetics2022

Recent advances and challenges of rare variant association analysis in the biobank sequencing era.

Wenan Chen, Brandon J Coombes, Nicholas B Larson

Abstract readReview
In one paragraph

Review in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Article
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  8. BeyondFrontiers in genetics · 2026
    Review
  9. Identification of novel and known variants inFrontiers in cardiovascular medicine · 2026
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
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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.

Wenan ChenCenter for Applied Bioinformatics, St. Jude Children's Research Hospital, Memphis, TN, United States.
Brandon J CoombesDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States.
Nicholas B LarsonDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Causal variants for rare genetic diseases are often rare in the general population. Rare variants may also contribute to common complex traits and can have much larger per-allele effect sizes than common variants, although power to detect these associations can be limited. Sequencing costs have steadily declined with technological advancements, making it feasible to adopt whole-exome and whole-genome profiling for large biobank-scale sample sizes. These large amounts of sequencing data provide both opportunities and challenges for rare-variant association analysis. Herein, we review the basic concepts of rare-variant analysis methods, the current state-of-the-art methods in utilizing variant annotations or external controls to improve the statistical power, and particular challenges facing rare variant analysis such as accounting for population structure, extremely unbalanced case-control design. We also review recent advances and challenges in rare variant analysis for familial sequencing data and for more complex phenotypes such as survival data. Finally, we discuss other potential directions for further methodology investigation.

Indexed as

case-controlcomplex phenotypesexternal controlsfamily-based designpopulation structurerare variantsequencing datavariant annotations

Identifiers

PMID36276986
PMCPMC9582646

What Socratic 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 Socratic graph.