ArticleBMC bioinformatics2019
uap: reproducible and robust HTS data analysis.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- A reliable transcriptomic risk-score applicable to formalin-fixed paraffin-embedded biopsies improves outcome prediction in localized prostate cancer.Molecular medicine (Cambridge, Mass.) · 2024Article
- Transcriptomic signatures reveal a shift towards an anti-inflammatory gene expression profile but also the induction of type I and type II interferon signaling networks through aryl hydrocarbon receptor activation in murine macrophages.Frontiers in immunology · 2023Article
- HBEGF-TNF induce a complex outer retinal pathology with photoreceptor cell extrusion in human organoids.Nature communications · 2022Article
- RNA sequencing of glioblastoma tissue slice cultures reveals the effects of treatment at the transcriptional level.FEBS open bio · 2022Article
- Computational Methods for the Discovery and Annotation of Viral Integrations.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Discovery of novel community-relevant small proteins in a simplified human intestinal microbiome.Microbiome · 2021Article
- A Multi-Omics Analysis of Mucosal-Associated-Invariant T Cells Reveals Key Drivers of Distinct Modes of Activation.Frontiers in immunology · 2021Article
- Mouse Retinal Organoid Growth and Maintenance in Longer-Term Culture.Frontiers in cell and developmental biology · 2021Article
- Low Energy Electron Irradiation Is a Potent Alternative to Gamma Irradiation for the Inactivation of (CAR-)NK-92 Cells in ATMP Manufacturing.Frontiers in immunology · 2021Article
- The Role of lncRNAs TAPIR-1 and -2 as Diagnostic Markers and Potential Therapeutic Targets in Prostate Cancer.Cancers · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundA lack of reproducibility has been repeatedly criticized in computational research. High throughput sequencing (HTS) data analysis is a complex multi-step process. For most of the steps a range of bioinformatic tools is available and for most tools manifold parameters need to be set. Due to this complexity, HTS data analysis is particularly prone to reproducibility and consistency issues. We have defined four criteria that in our opinion ensure a minimal degree of reproducible research for HTS data analysis. A series of workflow management systems is available for assisting complex multi-step data analyses. However, to the best of our knowledge, none of the currently available work flow management systems satisfies all four criteria for reproducible HTS analysis.
resultsHere we present uap, a workflow management system dedicated to robust, consistent, and reproducible HTS data analysis. uap is optimized for the application to omics data, but can be easily extended to other complex analyses. It is available under the GNU GPL v3 license at https://github.com/yigbt/uap.
conclusionsuap is a freely available tool that enables researchers to easily adhere to reproducible research principles for HTS data analyses.
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Registered trials
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.