Evidence map›Paper›PMID 27896972›Full record

ArticlePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing2017

DATA SHARING AND REPRODUCIBLE CLINICAL GENETIC TESTING: SUCCESSES AND CHALLENGES.

Shan Yang, Melissa Cline, Can Zhang, Benedict Paten, Stephen E Lincoln

Abstract read
In one paragraph

Article in Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Sources of discordance among germ-line variant classifications in ClinVar.Genetics in medicine : official journal of the American College of Medical Genetics · 2017
    Article
  3. A new era in the interpretation of human genomic variation.Genetics in medicine : official journal of the American College of Medical Genetics · 2017
    Article
  4. Consistency ofJCO precision oncology · 2017
    Article
  5. METHODS TO ENSURE THE REPRODUCIBILITY OF BIOMEDICAL RESEARCH.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2017
    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

5 authors.

Shan YangInvitae, San Francisco, California, USA, shan.yang@invitae.com.
Melissa Cline
Can Zhang
Benedict Paten
Stephen E Lincoln

Funding

Training SubprojectU54HG007990 · NHGRI · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI HAUSSLER, DAVID H, PATTERSON, DAVID · 2014 to 2018
$14.8M
NHGRI NIH HHS U54 HG007990
6 · The paper itself

Abstract

Open sharing of clinical genetic data promises to both monitor and eventually improve the reproducibility of variant interpretation among clinical testing laboratories. A significant public data resource has been developed by the NIH ClinVar initiative, which includes submissions from hundreds of laboratories and clinics worldwide. We analyzed a subset of ClinVar data focused on specific clinical areas and we find high reproducibility (>90% concordance) among labs, although challenges for the community are clearly identified in this dataset. We further review results for the commonly tested BRCA1 and BRCA2 genes, which show even higher concordance, although the significant fragmentation of data into different silos presents an ongoing challenge now being addressed by the BRCA Exchange. We encourage all laboratories and clinics to contribute to these important resources.

Indexed as

Computational BiologyDatabases, GeneticGenes, BRCA1Genes, BRCA2Genetic TestingGenetic VariationHumansInformation DisseminationNational Institutes of Health (U.S.)Reproducibility of ResultsUnited States

Identifiers

PMID27896972
PMCPMC5340191

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.