Evidence map›Paper›PMID 41734277›Full record

ArticleBioinformatics (Oxford, England)2026

Managing workflow executions with WESkit.

Valentin Schneider-Lunitz, Philip R Kensche, Landfried Kraatz, Philipp Strubel, Stefan Borufka, Gurudeep Parala, Alexander Kanitz, Roland Eils, Ivo Buchhalter, Sven O Twardziok

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Bioinformatics (Oxford, England), 2026. 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

10 authors.

Valentin Schneider-LunitzBerlin Institute of Health at Charité-Universitätsmedizin Berlin, Center of Digital Health, Berlin 10117, Germany.
Philip R KenscheDivision Omics IT and Data Management Core Facility (ODCF), German Cancer Research Center (DKFZ) Heidelberg, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
Landfried KraatzBerlin Institute of Health at Charité-Universitätsmedizin Berlin, Center of Digital Health, Berlin 10117, Germany.
Philipp StrubelBerlin Institute of Health at Charité-Universitätsmedizin Berlin, Center of Digital Health, Berlin 10117, Germany.
Stefan BorufkaDivision Omics IT and Data Management Core Facility (ODCF), German Cancer Research Center (DKFZ) Heidelberg, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
Gurudeep ParalaDivision Omics IT and Data Management Core Facility (ODCF), German Cancer Research Center (DKFZ) Heidelberg, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
Alexander KanitzBiozentrum, University of Basel, Basel 4056, Switzerland.ORCID 0000-0002-3468-0652
Roland EilsBerlin Institute of Health at Charité-Universitätsmedizin Berlin, Center of Digital Health, Berlin 10117, Germany.
Ivo BuchhalterDivision Omics IT and Data Management Core Facility (ODCF), German Cancer Research Center (DKFZ) Heidelberg, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
Sven O TwardziokBerlin Institute of Health at Charité-Universitätsmedizin Berlin, Center of Digital Health, Berlin 10117, Germany.ORCID 0000-0002-0326-5704

Funding

BMFTRFederal Ministry of Research, Technology and Space (BMFTR)German Center for Child and Adolescent Health (DZKJ) 01GL2401AGerman Network for Bioinformatics Infrastructure 031A537AHeidelberg Center for Human Bioinformatics (HD-HuB)NBI/ELIXIR-DE W-de.NBI-001
6 · The paper itself

Abstract

summaryIn biomedical research, managing computational workflows across numerous projects-with varying parameters, tools, and environments-creates major challenges in scalability, reproducibility, and collaboration. Here, we present WESkit, an implementation of the Global Alliance for Genomics and Health (GA4GH) Workflow Execution Service (WES) interface, designed to streamline the execution, monitoring, and documentation of data processing workflows. It addresses the complexities involved in managing numerous executions with varying parameters across diverse research projects. Supporting both Snakemake and Nextflow, the system enables consistent automation and centralized monitoring, which benefits research groups aiming for long-term reproducibility and scalable collaboration. Its suitability for larger teams and service units is further enhanced by seamless integration into cloud environments, contributing to the GA4GH cloud framework. AVAILABILITY AND IMPLEMENTATION: The software WESkit is available under MIT license at the GitLab repository (https://gitlab.com/one-touch-pipeline/weskit). The WESkit main repository is archived at Software Heritage (https://archive.softwareheritage.org/browse/origin/directory/?origin_url=https://gitlab.com/one-touch-pipeline/weskit/api.git) and can be found using "one-touch-pipeline/weskit" term in the search section.

Indexed as

Computational BiologyGenomicsSoftwareWorkflow

Identifiers

PMID41734277
PMCPMC13032820

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.