Evidence map›Paper›PMID 37277732›Full record

ArticleBMC bioinformatics2023

LAPIS is a fast web API for massive open virus sequencing data.

Chaoran Chen, Alexander Taepper, Fabian Engelniederhammer, Jonas Kellerer, Cornelius Roemer, Tanja Stadler

Abstract read
In one paragraph

Article in BMC bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Life (Basel, Switzerland) · 2026
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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.

Chaoran ChenDepartment of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland. chaoran.chen@bsse.ethz.ch.ORCID http://orcid.org/0000-0002-8763-2937
Alexander TaepperDepartment of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.ORCID http://orcid.org/0000-0002-2177-7092
Fabian EngelniederhammerTNG Technology Consulting GmbH, Unterföhring, Germany.ORCID http://orcid.org/0000-0003-2693-084X
Jonas KellererTNG Technology Consulting GmbH, Unterföhring, Germany.ORCID http://orcid.org/0000-0001-8033-2811
Cornelius RoemerSwiss Institute of Bioinformatics, Basel, Switzerland.ORCID http://orcid.org/0000-0002-6138-6539
Tanja StadlerDepartment of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland. tanja.stadler@bsse.ethz.ch.ORCID http://orcid.org/0000-0001-6431-535X

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 31CA30_196267
6 · The paper itself

Abstract

backgroundRecent epidemic outbreaks such as the SARS-CoV-2 pandemic and the mpox outbreak in 2022 have demonstrated the value of genomic sequencing data for tracking the origin and spread of pathogens. Laboratories around the globe generated new sequences at unprecedented speed and volume and bioinformaticians developed new tools and dashboards to analyze this wealth of data. However, a major challenge that remains is the lack of simple and efficient approaches for accessing and processing sequencing data.

resultsThe Lightweight API for Sequences (LAPIS) facilitates rapid retrieval and analysis of genomic sequencing data through a REST API. It supports complex mutation- and metadata-based queries and can perform aggregation operations on massive datasets. LAPIS is optimized for typical questions relevant to genomic epidemiology. Using a newly-developed in-memory database engine, it has a high speed and throughput: between 25 January and 4 February 2023, the SARS-CoV-2 instance of LAPIS, which contains 14.5 million sequences, processed over 20 million requests with a mean response time of 411 ms and a median response time of 1 ms. LAPIS is the core engine behind our dashboards on genspectrum.org and we currently maintain public LAPIS instances for SARS-CoV-2 and mpox.

conclusionsPowered by an optimized database engine and available through a web API, LAPIS enhances the accessibility of genomic sequencing data. It is designed to serve as a common backend for dashboards and analyses with the potential to be integrated into common database platforms such as GenBank.

Indexed as

COVID-19Mpox, MonkeypoxGenomeGenomicsHumansSARS-CoV-2

Identifiers

PMID37277732
PMCPMC10240112

What OpenQuestion holds

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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.