Evidence map›Paper›PMID 37311148›Full record

ArticleDatabase : the journal of biological databases and curation2023

GeniePool: genomic database with corresponding annotated samples based on a cloud data lake architecture.

Noam Hadar, Grisha Weintraub, Ehud Gudes, Shlomi Dolev, Ohad S Birk

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

5 authors.

Noam HadarThe Morris Kahn Laboratory of Human Genetics at the National Institute of Biotechnology in the Negev and Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva 84105, Israel.ORCID 0000-0003-2483-2090
Grisha WeintraubDepartment of Computer Science, Faculty of Natural Sciences, Ben Gurion University of the Negev, Beer Sheva 84105, Israel.ORCID 0000-0003-4823-4757
Ehud GudesDepartment of Computer Science, Faculty of Natural Sciences, Ben Gurion University of the Negev, Beer Sheva 84105, Israel.
Shlomi DolevDepartment of Computer Science, Faculty of Natural Sciences, Ben Gurion University of the Negev, Beer Sheva 84105, Israel.
Ohad S BirkThe Morris Kahn Laboratory of Human Genetics at the National Institute of Biotechnology in the Negev and Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva 84105, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, there are a huge influx of genomic data and a growing need for its phenotypic correlations, yet existing genomic databases do not allow easy storage and accessibility to the combined phenotypic-genotypic information. Freely accessible allele frequency (AF) databases, such as gnomAD, are crucial for evaluating variants but lack correlated phenotype data. The Sequence Read Archive (SRA) accumulates hundreds of thousands of next-generation sequencing (NGS) samples tagged by their submitters and various attributes. However, samples are stored in large raw format files, inaccessible for a common user. To make thousands of NGS samples and their corresponding additional attributes easily available to clinicians and researchers, we generated a pipeline that continuously downloads raw human NGS data uploaded to SRA using SRAtoolkit and preprocesses them using GATK pipeline. Data are then stored efficiently in a cloud data lake and can be accessed via a representational state transfer application programming interface (REST API) and a user-friendly website. We thus generated GeniePool, a simple and intuitive web service and API for querying NGS data from SRA with direct access to information related to each sample and related studies, providing significant advantages over existing databases for both clinical and research usages. Utilizing data lake infrastructure, we were able to generate a multi-purpose tool that can serve many clinical and research use cases. We expect users to explore the meta-data served via GeniePool both in daily clinical practice and in versatile research endeavours. Database URL https://geniepool.link.

Indexed as

GenomicsHigh-Throughput Nucleotide SequencingDatabases, FactualGene FrequencyHumansPhenotype

Identifiers

PMID37311148
PMCPMC10263466

What OpenQuestion holds

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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.