A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Nextpie: a web-based reporting tool and database for reproducible nextflow pipelines
Tekijät: Ghimire, Bishwa; Booth, Nicholas; Lönnberg, Tapio; Aittokallio, Tero
Toimittaja: Lengauer Thomas
Kustantaja: Oxford University Press (OUP)
Julkaisuvuosi: 2025
Lehti:Bioinformatics Advances
Artikkelin numero: vbaf252
Vuosikerta: 5
Numero: 1
eISSN: 2635-0041
DOI: https://doi.org/10.1093/bioadv/vbaf252
Verkko-osoite: https://doi.org/10.1093/bioadv/vbaf252
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/505185804
Motivation
High-throughput genomic data analysis consists of the inexorably intertwined inputs and outputs of a vast array of bioinformatic analysis tools. To guarantee streamlined and reproducible analyses, the often complex data analysis pipelines need to be run using workflow management tools. Nextflow is one popular tool commonly used to automate such pipelines. Nextflow records key pipeline data, such as the submission time, start time, completion time, CPU usage, memory usage, and disk usage for each task run. These data are stored in log files, often scattered across a file system. Therefore, aggregating information about resource usage critical for the optimization of Nextflow pipelines and improving reproducibility, as well as parsing and managing such log data, can quickly become cumbersome.
Results
Here, we present a web-based tool, Nextpie, which provides both a database and a reporting tool for Nextflow pipelines. Nextpie stores comprehensive resource usage information in a relational database, thus facilitating and accelerating the performance of a variety of data analyses and interactive visualizations, providing an easily comprehensible overview of a pipeline’s resource usage.
Availability and implementation
The Nextpie source code, user documentation, an SQLite database with test data, and a Nextflow example pipeline are available at GitHub (https://github.com/bishwaG/Nextpie).
Ladattava julkaisu This is an electronic reprint of the original article. |
Julkaisussa olevat rahoitustiedot:
This work was supported by the funds from Research Council of Finland [340141, 344698, and 34580 to T.A., 311081, 314557 and 335977 to T.L.]; Norwegian Health Authority South-East [2020026, 2023105 to T.A.]; and Norwegian Cancer Society [216104 and 273810 to T.A.].