Evidence map›Paper›PMID 33281875›Full record

ArticleFrontiers in genetics2020

Mastermind: A Comprehensive Genomic Association Search Engine for Empirical Evidence Curation and Genetic Variant Interpretation.

Lauren M Chunn, Diane C Nefcy, Rachel W Scouten, Ryan P Tarpey, Gurinder Chauhan, Megan S Lim, Kojo S J Elenitoba-Johnson, Steven A Schwartz, Mark J Kiel

Abstract read
In one paragraph

Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.

0numbers the graph read from it
0cells of the map it votes in
54citing 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

54 citing papers in PubMed.

  1. Trial
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  8. NovelNeurology. Genetics · 2025
    Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Genetic Landscape of Dystonia in Asian Indians.Movement disorders clinical practice · 2025
    Article
  18. Article
  19. Clinical utility of panel-based genetic sequencing for von Willebrand disease.Research and practice in thrombosis and haemostasis · 2025
    Article
  20. 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

9 authors.

Lauren M ChunnGenomenon Inc., Ann Arbor, MI, United States.
Diane C NefcyGenomenon Inc., Ann Arbor, MI, United States.
Rachel W ScoutenGenomenon Inc., Ann Arbor, MI, United States.
Ryan P TarpeyThe Johns Hopkins Hospital, Department of Pharmacy, Baltimore, MD, United States.
Gurinder ChauhanGenomenon Inc., Ann Arbor, MI, United States.
Megan S LimDivision of Hematopathology, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Kojo S J Elenitoba-JohnsonDivision of Precision and Computational Diagnostics, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Steven A SchwartzGenomenon Inc., Ann Arbor, MI, United States.
Mark J KielGenomenon Inc., Ann Arbor, MI, United States.

Funding

Commercial Software Using High-throughput Computational Techniques to Improve Genome AnalysisR44HG009474 · NHGRI · GENOMENON, INC. · PI KIEL, MARK JULIN · 2017 to 2019
$1.7M
Micropublications for Automating Genome Sequence Variant Interpretation from Medical LiteratureR43HG010446 · NHGRI · GENOMENON, INC. · PI KIEL, MARK JULIN · 2019 to 2019
$153k
NHGRI NIH HHS R43 HG010446NHGRI NIH HHS R44 HG009474
6 · The paper itself

Abstract

Design and interpretation of genome sequencing assays in clinical diagnostics and research labs is complicated by an inability to identify information from the medical literature and related databases quickly, comprehensively and reproducibly. This challenge is compounded by the complexity and heterogeneity of nomenclatures used to describe diseases, genes and genetic variants. Mastermind is a widely-used bioinformatic platform of genomic associations that has indexed more than 7.5 M full-text articles and 2.5 M supplemental datasets. It has automatically identified, disambiguated and annotated >6.1 M genetic variants and identified >50 K disease-gene associations. Here, we describe how Mastermind improves the sensitivity and reproducibility of clinical variant interpretation and produces comprehensive genomic landscapes of genetic variants driving pharmaceutical research. We demonstrate an alarmingly high degree of heterogeneity across commercially available panels for hereditary cancer that is resolved by evidence from Mastermind. We further examined the sensitivity of Mastermind for variant interpretation by examining 108 clinically-encountered variants and comparing the results to alternate methods. Mastermind demonstrated a sensitivity of 98.4% compared to 4.4, 45.6, and 37.4% for alternatives PubMed, Google Scholar, and ClinVar, respectively, and a specificity of 98.5% compared to 45.1, 57.6, and 68.8% as well as an increase in content yield of 22.6-, 2.2-, and 2.6-fold. When curated for clinical significance, Mastermind identified more than 4.9-fold more pathogenic variants than ClinVar for representative genes. For structural variants, we compared Mastermind's ability to sensitively identify evidence for 10 representative disease-causing CNVs versus results identified in PubMed, as well as its ability to identify evidence for fusion events compared to COSMIC. Mastermind demonstrated a 4.0- to 43.9-fold increase in references for specific CNVs compared to PubMed, as well as 5.4-fold more fusion genes when compared with COSMIC's curated database. Additionally, Mastermind produced an 8.0-fold increase in reference citations for fusion events common to Mastermind and outside databases. Taken together, these results demonstrate the utility and superiority of Mastermind in terms of both sensitivity and specificity of automated results for clinical diagnostic variant interpretation for multiple genetic variant types and highlight the potential benefit in informing pharmaceutical research.

Indexed as

copy number variantgene fusionsgenome sequence analysisoncologyrare diseasevariant interpretation and classification

Identifiers

PMID33281875
PMCPMC7691534

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.