Evidence map›Paper›PMID 33181822›Full record

ArticleDatabase : the journal of biological databases and curation2020

Color Data v2: a user-friendly, open-access database with hereditary cancer and hereditary cardiovascular conditions datasets.

Mark J Berger, Hannah E Williams, Ryan Barrett, Anjali D Zimmer, Wendy McKennon, Huy Hong, Jeremy Ginsberg, Alicia Y Zhou, Cynthia L Neben

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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.

Mark J BergerColor Genomics, 831 Mitten Road, Suite 100, Burlingame, CA, 94010, USA.
Hannah E WilliamsColor Genomics, 831 Mitten Road, Suite 100, Burlingame, CA, 94010, USA.
Ryan BarrettColor Genomics, 831 Mitten Road, Suite 100, Burlingame, CA, 94010, USA.
Anjali D ZimmerColor Genomics, 831 Mitten Road, Suite 100, Burlingame, CA, 94010, USA.
Wendy McKennonColor Genomics, 831 Mitten Road, Suite 100, Burlingame, CA, 94010, USA.
Huy HongColor Genomics, 831 Mitten Road, Suite 100, Burlingame, CA, 94010, USA.
Jeremy GinsbergColor Genomics, 831 Mitten Road, Suite 100, Burlingame, CA, 94010, USA.
Alicia Y ZhouColor Genomics, 831 Mitten Road, Suite 100, Burlingame, CA, 94010, USA.
Cynthia L NebenColor Genomics, 831 Mitten Road, Suite 100, Burlingame, CA, 94010, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Publicly available genetic databases promote data sharing and fuel scientific discoveries for the prevention, treatment and management of disease. In 2018, we built Color Data, a user-friendly, open access database containing genotypic and self-reported phenotypic information from 50 000 individuals who were sequenced for 30 genes associated with hereditary cancer. In a continued effort to promote access to these types of data, we launched Color Data v2, an updated version of the Color Data database. This new release includes additional clinical genetic testing results from more than 18 000 individuals who were sequenced for 30 genes associated with hereditary cardiovascular conditions as well as polygenic risk scores for breast cancer, coronary artery disease and atrial fibrillation. In addition, we used self-reported phenotypic information to implement the following four clinical risk models: Gail Model for 5-year risk of breast cancer, Claus Model for lifetime risk of breast cancer, simple office-based Framingham Coronary Heart Disease Risk Score for 10-year risk of coronary heart disease and CHARGE-AF simple score for 5-year risk of atrial fibrillation. These new features and capabilities are highlighted through two sample queries in the database. We hope that the broad dissemination of these data will help researchers continue to explore genotype-phenotype correlations and identify novel variants for functional analysis, enabling scientific discoveries in the field of population genomics. Database URL: https://data.color.com/.

Indexed as

Breast NeoplasmsGenetic Predisposition to DiseaseDatabases, FactualFemaleGenetic Association StudiesGenotypeHumans

Identifiers

PMID33181822
PMCPMC7661094

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.