Evidence map›Paper›PMID 26714792›Full record

ArticleBMC bioinformatics2015

BigQ: a NoSQL based framework to handle genomic variants in i2b2.

Matteo Gabetta, Ivan Limongelli, Ettore Rizzo, Alberto Riva, Daniele Segagni, Riccardo Bellazzi

Abstract read
In one paragraph

Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. A review of harmonization methods for studying dietary patterns.Smart health (Amsterdam, Netherlands) · 2022
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  6. Review
  7. Benchmarking database systems for Genomic Selection implementation.Database : the journal of biological databases and curation · 2019
    Article
  8. Article
  9. Ad Hoc Information Extraction for Clinical Data Warehouses.Methods of information in medicine · 2018
    Article
  10. Article
  11. Article
  12. Review
  13. 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

6 authors.

Matteo GabettaDipartimento di Ingegneria Industriale e dell'Informazione and Center for Health Technologies, Università di Pavia, Pavia, Italy. matteo.gabetta@unipv.it.
Ivan LimongelliDipartimento di Ingegneria Industriale e dell'Informazione and Center for Health Technologies, Università di Pavia, Pavia, Italy. ivan.limongelli@unipv.it.
Ettore RizzoDipartimento di Ingegneria Industriale e dell'Informazione and Center for Health Technologies, Università di Pavia, Pavia, Italy. ettore.rizzo@unipv.it.
Alberto RivaInterdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, FL, USA. ariva@ufl.edu.
Daniele SegagniIRCCS Fondazione S. Maugeri, Pavia, Italy. daniele.segagni@fsm.it.
Riccardo BellazziDipartimento di Ingegneria Industriale e dell'Informazione and Center for Health Technologies, Università di Pavia, Pavia, Italy. riccardo.bellazzi@unipv.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrecision medicine requires the tight integration of clinical and molecular data. To this end, it is mandatory to define proper technological solutions able to manage the overwhelming amount of high throughput genomic data needed to test associations between genomic signatures and human phenotypes. The i2b2 Center (Informatics for Integrating Biology and the Bedside) has developed a widely internationally adopted framework to use existing clinical data for discovery research that can help the definition of precision medicine interventions when coupled with genetic data. i2b2 can be significantly advanced by designing efficient management solutions of Next Generation Sequencing data.

resultsWe developed BigQ, an extension of the i2b2 framework, which integrates patient clinical phenotypes with genomic variant profiles generated by Next Generation Sequencing. A visual programming i2b2 plugin allows retrieving variants belonging to the patients in a cohort by applying filters on genomic variant annotations. We report an evaluation of the query performance of our system on more than 11 million variants, showing that the implemented solution scales linearly in terms of query time and disk space with the number of variants.

conclusionsIn this paper we describe a new i2b2 web service composed of an efficient and scalable document-based database that manages annotations of genomic variants and of a visual programming plug-in designed to dynamically perform queries on clinical and genetic data. The system therefore allows managing the fast growing volume of genomic variants and can be used to integrate heterogeneous genomic annotations.

Indexed as

GenomicsSoftwareDatabases, FactualHigh-Throughput Nucleotide SequencingHumansInformation Storage and Retrieval

Identifiers

PMID26714792
PMCPMC4696314

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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.