Evidence map›Paper›PMID 28794857›Full record

ArticleF1000Research2017

Extending TCGA queries to automatically identify analogous genomic data from dbGaP.

Erin K Wagner, Satyajeet Raje, Liz Amos, Jessica Kurata, Abhijit S Badve, Yingquan Li, Ben Busby

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in F1000Research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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

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

7 authors.

Erin K WagnerBioStat Solutions, Frederick, USA.
Satyajeet RajeNational Library of Medicine, National Institutes of Health, Bethesda, USA.
Liz AmosNational Library of Medicine, National Institutes of Health, Bethesda, USA.
Jessica KurataDepartment of Molecular and Cellular Biology, City of Hope, Duarte, USA.
Abhijit S BadveGeneDx, Gaithersburg, USA.
Yingquan LiCorporate Executive Board (CEB), Arlington, USA.
Ben BusbyNational Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, USA.ORCID https://orcid.org/0000-0001-5267-4988

Funding

National Biomedical Information ServicesZIHLM200888 · NLM · NATIONAL LIBRARY OF MEDICINE · PI PALTOO, DINA · 2009 to 2025
$5200.7M
6 · The paper itself

Abstract

Data sharing is critical to advance genomic research by reducing the demand to collect new data by reusing and combining existing data and by promoting reproducible research. The Cancer Genome Atlas (TCGA) is a popular resource for individual-level genotype-phenotype cancer related data. The Database of Genotypes and Phenotypes (dbGaP) contains many datasets similar to those in TCGA. We have created a software pipeline that will allow researchers to discover relevant genomic data from dbGaP, based on matching TCGA metadata. The resulting research provides an easy to use tool to connect these two data sources.

Indexed as

cancerdatabasedbGaPGDCgenomeSRATCGAThe Cancer Genome Atlas

Identifiers

PMID28794857
PMCPMC5538035

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.