Evidence map›Paper›PMID 38281099›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2024

Comparison of literature mining tools for variant classification: Through the lens of 50 RYR1 variants.

Zara Wermers, Seeley Yoo, Bailey Radenbaugh, Amber Douglass, Leslie G Biesecker, Jennifer J Johnston

Erratum issuedAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Zara WermersCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD.
Seeley YooCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD.
Bailey RadenbaughCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD.
Amber DouglassCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD.
Leslie G BieseckerCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD.
Jennifer J JohnstonCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD. Electronic address: jjohnsto@mail.nih.gov.

Funding

Rare & Mosaic Disorders - Clinical ResearchZIAHG200388 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI BIESECKER, LESLIE · 2013 to 2025
$17.3M
Genomic Ascertainment - Clinical and Behavioral AspectsZIAHG200387 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI BIESECKER, LESLIE · 2013 to 2025
$15.5M
Intramural NIH HHS Z99 HG999999Intramural NIH HHS ZIA HG200387Intramural NIH HHS ZIA HG200388
6 · The paper itself

Abstract

purposeThe American College of Medical Genetics and Genomics and the Association for Molecular Pathology have outlined a schema that allows for systematic classification of variant pathogenicity. Although gnomAD is generally accepted as a reliable source of population frequency data and ClinGen has provided guidance on the utility of specific bioinformatic predictors, there is no consensus source for identifying publications relevant to a variant. Multiple tools are available to aid in the identification of relevant variant literature, including manually curated databases and literature search engines. We set out to determine the utility of 4 literature mining tools used for ascertainment to inform the discussion of the use of these tools.

methodsFour literature mining tools including the Human Gene Mutation Database, Mastermind, ClinVar, and LitVar 2.0 were used to identify relevant variant literature for 50 RYR1 variants. Sensitivity and precision were determined for each tool.

resultsSensitivity among the 4 tools ranged from 0.332 to 0.687. Precision ranged from 0.389 to 0.906. No single tool retrieved all relevant publications.

conclusionAt the current time, the use of multiple tools is necessary to completely identify the literature relevant to curate a variant.

Indexed as

Data MiningGenetic VariationRyanodine Receptor Calcium Release ChannelGene FrequencyGenetic TestingHumansMutationRyanodine Receptor Calcium Release ChannelACMG guidelinesBiocurationLiterature miningRYR1Variant classification

Identifiers

PMID38281099
PMCPMC12266334

What OpenQuestion holds

Textmetadata
LicenceTDM
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.