Evidence map›Paper›PMID 35207663›Full record

ReviewJournal of personalized medicine2022

Computational Genomics in the Era of Precision Medicine: Applications to Variant Analysis and Gene Therapy.

Yung-Chun Wang, Yuchang Wu, Julie Choi, Garrett Allington, Shujuan Zhao, Mariam Khanfar, Kuangying Yang, Po-Ying Fu, Max Wrubel, Xiaobing Yu and 7 more

Abstract readReview
In one paragraph

Review in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. De NovoHuman mutation · 2026
    Article
  2. SomaticGenes · 2025
    Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Pathogenic variants in autism geneProceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. 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

17 authors.

Yung-Chun WangDepartment of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA.ORCID 0000-0002-8775-3472
Yuchang WuDepartment of Biostatistics & Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA.ORCID 0000-0002-6985-3998
Julie ChoiDepartment of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA.
Garrett AllingtonDepartment of Pathology, Yale School of Medicine, New Haven, CT 06510, USA.ORCID 0000-0002-5458-6129
Shujuan ZhaoDepartment of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA.
Mariam KhanfarDepartment of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA.
Kuangying YangDepartment of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA.ORCID 0000-0002-6992-9585
Po-Ying FuDepartment of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA.
Max WrubelDepartment of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA.
Xiaobing YuDepartment of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA.ORCID 0000-0003-3270-0573
Kedous Y MekbibDepartment of Neurosurgery, Yale University School of Medicine, New Haven, CT 06510, USA.
Jack OckenDepartment of Neurosurgery, Yale University School of Medicine, New Haven, CT 06510, USA.
Hannah SmithDepartment of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA.
John ShohfiDepartment of Neurosurgery, Yale University School of Medicine, New Haven, CT 06510, USA.
Kristopher T KahleDepartment of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA.
Qiongshi LuDepartment of Biostatistics & Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA.ORCID 0000-0002-4514-0969
Sheng Chih JinDepartment of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA.ORCID 0000-0002-5777-7262

Funding

WU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCESUL1TR002345 · NCATS · WASHINGTON UNIVERSITY · PI William G. Powderly · 2017 to 2026
$97.8M
NCATS NIH HHS UL1 TR002345
6 · The paper itself

Abstract

Rapid methodological advances in statistical and computational genomics have enabled researchers to better identify and interpret both rare and common variants responsible for complex human diseases. As we continue to see an expansion of these advances in the field, it is now imperative for researchers to understand the resources and methodologies available for various data types and study designs. In this review, we provide an overview of recent methods for identifying rare and common variants and understanding their roles in disease etiology. Additionally, we discuss the strategy, challenge, and promise of gene therapy. As computational and statistical approaches continue to improve, we will have an opportunity to translate human genetic findings into personalized health care.

Indexed as

bioinformaticscommon variantgene therapygenomicsprecision medicinerare variantstatistical genetics

Identifiers

PMID35207663
PMCPMC8878256

What OpenQuestion holds

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LicenceCC BY
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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.