Evidence map›Paper›PMID 33757430›Full record

ArticleBMC bioinformatics2021

ATAV: a comprehensive platform for population-scale genomic analyses.

Zhong Ren, Gundula Povysil, Joseph A Hostyk, Hongzhu Cui, Nitin Bhardwaj, David B Goldstein

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
6.2field-weighted citation impact, top 3% of its field
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

30 citing papers in PubMed, 41 citations in OpenAlex.

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  7. Natural History and Clinicopathological Associations of TRPC6-Associated Podocytopathy.Journal of the American Society of Nephrology : JASN · 2025
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  19. Variants ofBiomedical reports · 2023
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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

6 authors at 2 institutions in 1 country.

Zhong RenInstitute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA. zhong.ren@hotmail.com.ORCID http://orcid.org/0000-0003-2446-8612
Gundula PovysilInstitute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA.
Joseph A HostykInstitute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA.
Hongzhu CuiInstitute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA.
Nitin BhardwajInstitute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA.
David B GoldsteinInstitute for Genomic Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA.
Columbia University · USColumbia University Irving Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA common approach for sequencing studies is to do joint-calling and store variants of all samples in a single file. If new samples are continually added or controls are re-used for several studies, the cost and time required to perform joint-calling for each analysis can become prohibitive.

resultsWe present ATAV, an analysis platform for large-scale whole-exome and whole-genome sequencing projects. ATAV stores variant and per site coverage data for all samples in a centralized database, which is efficiently queried by ATAV to support diagnostic analyses for trios and singletons, as well as rare-variant collapsing analyses for finding disease associations in complex diseases. Runtime logs ensure full reproducibility and the modularized ATAV framework makes it extensible to continuous development. Besides helping with the identification of disease-causing variants for a range of diseases, ATAV has also enabled the discovery of disease-genes by rare-variant collapsing on datasets containing more than 20,000 samples. Analyses to date have been performed on data of more than 110,000 individuals demonstrating the scalability of the framework. To allow users to easily access variant-level data directly from the database, we provide a web-based interface, the ATAV data browser ( http://atavdb.org/ ). Through this browser, summary-level data for more than 40,000 samples can be queried by the general public representing a mix of cases and controls of diverse ancestries. Users have access to phenotype categories of variant carriers, as well as predicted ancestry, gender, and quality metrics. In contrast to many other platforms, the data browser is able to show data of newly-added samples in real-time and therefore evolves rapidly as more and more samples are sequenced.

conclusionsThrough ATAV, users have public access to one of the largest variant databases for patients sequenced at a tertiary care center and can look up any genes or variants of interest. Additionally, since the entire code is freely available on GitHub, ATAV can easily be deployed by other groups that wish to build their own platform, database, and user interface.

Indexed as

Exome SequencingGenomicsSoftwareDatabases, GeneticGenetics, PopulationHumansPhenotypeReproducibility of ResultsAssociation testingDiagnosticGene discoveryGenome analysisWeb platform

Identifiers

PMID33757430
PMCPMC7988908
OpenAlexW3139057580

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.